Contents¶

Getting started¶

Installing¶

Linux¶

PyTango is available on linux as an official debian/ubuntu package:

$ sudo apt-get install python-pytango

RPM packages are also available for RHEL & CentOS:

PyPi¶

You can also install the latest version from PyPi.

First, make sure you have the following packages already installed (all of them are available from the major official distribution repositories):

boost-python (including boost-python-dev)
numpy

Then install PyTango either from pip:

$ pip install PyTango

or easy_install:

$ easy_install -U PyTango

Windows¶

First, make sure Python and numpy are installed.

PyTango team provides a limited set of binary PyTango distributables for Windows XP/Vista/7/8. The complete list of binaries can be downloaded from PyPI.

Select the proper windows package, download it and finally execute the installion wizard.

Compiling¶

Linux¶

Since PyTango 9 the build system used to compile PyTango is the standard python setuptools.

Besides the binaries for the three dependencies mentioned above, you also need the development files for the respective libraries.

You can get the latest .tar.gz from PyPI or directly the latest SVN checkout:

$ git clone https://github.com/tango-cs/pytango.git
$ cd pytango
$ python setup.py build
$ sudo python setup.py install

This will install PyTango in the system python installation directory. (Since PyTango9, ITango has been removed to a separate project and it will not be installed with PyTango.) If you whish to install in a different directory, replace the last line with:

$ # private installation to your user (usually ~/.local/lib/python<X>.<Y>/site-packages)
$ python setup.py install --user

$ # or specific installation directory
$ python setup.py install --prefix=/home/homer/local

Windows¶

On windows, PyTango must be built using MS VC++. Since it is rarely needed and the instructions are so complicated, I have choosen to place the how-to in a separate text file. You can find it in the source package under doc/windows_notes.txt.

Testing¶

To test the installation, import tango and check tango.Release.version:

$ python -c "import tango; print(tango.Release.version)"
9.3.3

Next steps: Check out the Quick tour.

Quick tour¶

This quick tour will guide you through the first steps on using PyTango.

Fundamental TANGO concepts¶

Before you begin there are some fundamental TANGO concepts you should be aware of.

Tango consists basically of a set of devices running somewhere on the network.

A device is identified by a unique case insensitive name in the format <domain>/<family>/<member>. Examples: LAB-01/PowerSupply/01, ID21/OpticsHutch/energy.

Each device has a series of attributes, pipes, properties and commands.

An attribute is identified by a name in a device. It has a value that can be read. Some attributes can also be changed (read-write attributes). Each attribute has a well known, fixed data type.

A pipe is a kind of attribute. Unlike attributes, the pipe data type is strucured (in the sence of C struct) and it is dynamic.

A property is identified by a name in a device. Usually, devices properties are used to provide a way to configure a device.

A command is also identified by a name. A command may or not receive a parameter and may or not return a value when it is executed.

Any device has at least a State and Status attributes and State, Status and Init commands. Reading the State or Status attributes has the same effect as executing the State or Status commands.

Each device as an associated TANGO Class. Most of the times the TANGO class has the same name as the object oriented programming class which implements it but that is not mandatory.

TANGO devices live inside a operating system process called TANGO Device Server. This server acts as a container of devices. A device server can host multiple devices of multiple TANGO classes. Devices are, therefore, only accessible when the corresponding TANGO Device Server is running.

A special TANGO device server called the TANGO Database Server will act as a naming service between TANGO servers and clients. This server has a known address where it can be reached. The machines that run TANGO Device Servers and/or TANGO clients, should export an environment variable called TANGO_HOST that points to the TANGO Database server address. Example: TANGO_HOST=homer.lab.eu:10000

Minimum setup¶

This chapter assumes you have already installed PyTango.

To explore PyTango you should have a running Tango system. If you are working in a facility/institute that uses Tango, this has probably already been prepared for you. You need to ask your facility/institute tango contact for the TANGO_HOST variable where Tango system is running.

If you are working in an isolate machine you first need to make sure the Tango system is installed and running (see tango how to).

Most examples here connect to a device called sys/tg_test/1 that runs in a TANGO server called TangoTest with the instance name test. This server comes with the TANGO installation. The TANGO installation also registers the test instance. All you have to do is start the TangoTest server on a console:

$ TangoTest test
Ready to accept request

Note

if you receive a message saying that the server is already running, it just means that somebody has already started the test server so you don’t need to do anything.

Client¶

Finally you can get your hands dirty. The first thing to do is start a python console and import the tango module. The following example shows how to create a proxy to an existing TANGO device, how to read and write attributes and execute commands from a python console:

>>> import tango

>>> # create a device object
>>> test_device = tango.DeviceProxy("sys/tg_test/1")

>>> # every device has a state and status which can be checked with:
>>> print(test_device.state())
RUNNING

>>> print(test_device.status())
The device is in RUNNING state.

>>> # this device has an attribute called "long_scalar". Let's see which value it has...
>>> data = test_device.read_attribute("long_scalar")

>>> # ...PyTango provides a shortcut to do the same:
>>> data = test_device["long_scalar"]

>>> # the result of reading an attribute is a DeviceAttribute python object.
>>> # It has a member called "value" which contains the value of the attribute
>>> data.value
136

>>> # Check the complete DeviceAttribute members:
>>> print(data)
DeviceAttribute[
data_format = SCALAR
      dim_x = 1
      dim_y = 0
 has_failed = False
   is_empty = False
       name = 'long_scalar'
    nb_read = 1
 nb_written = 1
    quality = ATTR_VALID
r_dimension = AttributeDimension(dim_x = 1, dim_y = 0)
       time = TimeVal(tv_nsec = 0, tv_sec = 1399450183, tv_usec = 323990)
       type = DevLong
      value = 136
    w_dim_x = 1
    w_dim_y = 0
w_dimension = AttributeDimension(dim_x = 1, dim_y = 0)
    w_value = 0]

>>> # PyTango provides a handy pythonic shortcut to read the attribute value:
>>> test_device.long_scalar
136

>>> # Setting an attribute value is equally easy:
>>> test_device.write_attribute("long_scalar", 8776)

>>> # ... and a handy shortcut to do the same exists as well:
>>> test_device.long_scalar = 8776

>>> # TangoTest has a command called "DevDouble" which receives a number
>>> # as parameter and returns the same number as a result. Let's
>>> # execute this command:
>>> test_device.command_inout("DevDouble", 45.67)
45.67

>>> # PyTango provides a handy shortcut: it exports commands as device methods:
>>> test_device.DevDouble(45.67)
45.67

>>> # Introspection: check the list of attributes:
>>> test_device.get_attribute_list()
['ampli', 'boolean_scalar', 'double_scalar', '...', 'State', 'Status']

>>>

This is just the tip of the iceberg. Check the DeviceProxy for the complete API.

PyTango used to come with an integrated IPython based console called ITango, now moved to a separate project. It provides helpers to simplify console usage. You can use this console instead of the traditional python console. Be aware, though, that many of the tricks you can do in an ITango console cannot be done in a python program.

Server¶

Since PyTango 8.1 it has become much easier to program a Tango device server. PyTango provides some helpers that allow developers to simplify the programming of a Tango device server.

Before creating a server you need to decide:

The Tango Class name of your device (example: PowerSupply). In our example we will use the same name as the python class name.
The list of attributes of the device, their data type, access (read-only vs read-write), data_format (scalar, 1D, 2D)
The list of commands, their parameters and their result

In our example we will write a fake power supply device server. There will be a class called PowerSupply which will have attributes:

voltage (scalar, read-only, numeric)
current (scalar, read_write, numeric, expert mode)
noise (2D, read-only, numeric)

pipes:

info (read-only)

commands:

TurnOn (argument: None, result: None)
TurnOff (argument: None, result: None)
Ramp (param: scalar, numeric; result: bool)

properties:

host (string representing the host name of the actual power supply)
port (port number in the host with default value = 9788)

Here is the code for the power_supply.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""Demo power supply tango device server"""

import time
import numpy

from tango import AttrQuality, AttrWriteType, DispLevel, DevState, DebugIt
from tango.server import Device, attribute, command, pipe, device_property


class PowerSupply(Device):

    voltage = attribute(label="Voltage", dtype=float,
                        display_level=DispLevel.OPERATOR,
                        access=AttrWriteType.READ,
                        unit="V", format="8.4f",
                        doc="the power supply voltage")

    current = attribute(label="Current", dtype=float,
                        display_level=DispLevel.EXPERT,
                        access=AttrWriteType.READ_WRITE,
                        unit="A", format="8.4f",
                        min_value=0.0, max_value=8.5,
                        min_alarm=0.1, max_alarm=8.4,
                        min_warning=0.5, max_warning=8.0,
                        fget="get_current",
                        fset="set_current",
                        doc="the power supply current")

    noise = attribute(label="Noise",
                      dtype=((int,),),
                      max_dim_x=1024, max_dim_y=1024)

    info = pipe(label='Info')

    host = device_property(dtype=str)
    port = device_property(dtype=int, default_value=9788)

    def init_device(self):
        Device.init_device(self)
        self.__current = 0.0
        self.set_state(DevState.STANDBY)

    def read_voltage(self):
        self.info_stream("read_voltage(%s, %d)", self.host, self.port)
        return 9.99, time.time(), AttrQuality.ATTR_WARNING

    def get_current(self):
        return self.__current

    def set_current(self, current):
        # should set the power supply current
        self.__current = current

    def read_info(self):
        return 'Information', dict(manufacturer='Tango',
                                   model='PS2000',
                                   version_number=123)

    @DebugIt()
    def read_noise(self):
        return numpy.random.random_integers(1000, size=(100, 100))

    @command
    def TurnOn(self):
        # turn on the actual power supply here
        self.set_state(DevState.ON)

    @command
    def TurnOff(self):
        # turn off the actual power supply here
        self.set_state(DevState.OFF)

    @command(dtype_in=float, doc_in="Ramp target current",
             dtype_out=bool, doc_out="True if ramping went well, "
             "False otherwise")
    def Ramp(self, target_current):
        # should do the ramping
        return True


if __name__ == "__main__":
    PowerSupply.run_server()

Check the high level server API for the complete reference API. The write a server how to can help as well.

Before running this brand new server we need to register it in the Tango system. You can do it with Jive (Jive->Edit->Create server):

… or in a python script:

>>> import tango

>>> dev_info = tango.DbDevInfo()
>>> dev_info.server = "PowerSupply/test"
>>> dev_info._class = "PowerSupply"
>>> dev_info.name = "test/power_supply/1"

>>> db = tango.Database()
>>> db.add_device(dev_info)

After, you can run the server on a console with:

$ python power_supply.py test
Ready to accept request

Now you can access it from a python console:

>>> import tango

>>> power_supply = tango.DeviceProxy("test/power_supply/1")
>>> power_supply.state()
STANDBY

>>> power_supply.current = 2.3

>>> power_supply.current
2.3

>>> power_supply.TurnOn()
>>> power_supply.Ramp(2.1)
True

>>> power_supply.state()
ON

Note

In this example, the name of the server and the name of the tango class are the same: PowerSupply. This pattern is enforced by the run_server() method. However, it is possible to run several tango classes in the same server. In this case, the server name would typically be the name of server file. See the run() function for further information.

ITango¶

ITango is a PyTango CLI based on IPython. It is designed to be used as an IPython profile.

ITango is available since PyTango 7.1.2 and has been moved to a separate project since PyTango 9.2.0:

Green mode¶

PyTango supports cooperative green Tango objects. Since version 8.1 two green modes have been added: Futures and Gevent. In version 9.2.0 another one has been added: Asyncio.

Note

The preferred mode to use for new projects is Asyncio. Support for this mode will take priority over the others.

The Futures uses the standard python module concurrent.futures. The Gevent mode uses the well known gevent library. The newest, Asyncio mode, uses asyncio - a Python library for asynchronous programming (it’s featured as a part of a standard Python distribution since version 3.5 of Python; it’s available on PyPI for older ones).

You can set the PyTango green mode at a global level. Set the environment variable PYTANGO_GREEN_MODE to either futures, gevent or asyncio (case insensitive). If this environment variable is not defined the PyTango global green mode defaults to Synchronous.

Client green modes¶

You can also change the active global green mode at any time in your program:

>>> from tango import DeviceProxy, GreenMode
>>> from tango import set_green_mode, get_green_mode

>>> get_green_mode()
tango.GreenMode.Synchronous

>>> dev = DeviceProxy("sys/tg_test/1")
>>> dev.get_green_mode()
tango.GreenMode.Synchronous

>>> set_green_mode(GreenMode.Futures)
>>> get_green_mode()
tango.GreenMode.Futures

>>> dev.get_green_mode()
tango.GreenMode.Futures

As you can see by the example, the global green mode will affect any previously created DeviceProxy using the default DeviceProxy constructor parameters.

You can specificy green mode on a DeviceProxy at creation time. You can also change the green mode at any time:

>>> from tango.futures import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> dev.get_green_mode()
tango.GreenMode.Futures

>>> dev.set_green_mode(GreenMode.Synchronous)
>>> dev.get_green_mode()
tango.GreenMode.Synchronous

futures mode¶

Using concurrent.futures cooperative mode in PyTango is relatively easy:

>>> from tango.futures import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> dev.get_green_mode()
tango.GreenMode.Futures

>>> print(dev.state())
RUNNING

The tango.futures.DeviceProxy() API is exactly the same as the standard DeviceProxy. The difference is in the semantics of the methods that involve synchronous network calls (constructor included) which may block the execution for a relatively big amount of time. The list of methods that have been modified to accept futures semantics are, on the tango.futures.DeviceProxy():

So how does this work in fact? I see no difference from using the standard DeviceProxy. Well, this is, in fact, one of the goals: be able to use a futures cooperation without changing the API. Behind the scenes the methods mentioned before have been modified to be able to work cooperatively.

All of the above methods have been boosted with two extra keyword arguments wait and timeout which allow to fine tune the behaviour. The wait parameter is by default set to True meaning wait for the request to finish (the default semantics when not using green mode). If wait is set to True, the timeout determines the maximum time to wait for the method to execute. The default is None which means wait forever. If wait is set to False, the timeout is ignored.

If wait is set to True, the result is the same as executing the standard method on a DeviceProxy. If, wait is set to False, the result will be a concurrent.futures.Future. In this case, to get the actual value you will need to do something like:

>>> from tango.futures import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> result = dev.state(wait=False)
>>> result
<Future at 0x16cb310 state=pending>

>>> # this will be the blocking code
>>> state = result.result()
>>> print(state)
RUNNING

Here is another example using read_attribute():

>>> from tango.futures import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> result = dev.read_attribute('wave', wait=False)
>>> result
<Future at 0x16cbe50 state=pending>

>>> dev_attr = result.result()
>>> print(dev_attr)
DeviceAttribute[
data_format = tango.AttrDataFormat.SPECTRUM
      dim_x = 256
      dim_y = 0
 has_failed = False
   is_empty = False
       name = 'wave'
    nb_read = 256
 nb_written = 0
    quality = tango.AttrQuality.ATTR_VALID
r_dimension = AttributeDimension(dim_x = 256, dim_y = 0)
       time = TimeVal(tv_nsec = 0, tv_sec = 1383923329, tv_usec = 451821)
       type = tango.CmdArgType.DevDouble
      value = array([ -9.61260664e-01,  -9.65924853e-01,  -9.70294813e-01,
        -9.74369212e-01,  -9.78146810e-01,  -9.81626455e-01,
        -9.84807087e-01,  -9.87687739e-01,  -9.90267531e-01,
        ...
        5.15044507e-1])
    w_dim_x = 0
    w_dim_y = 0
w_dimension = AttributeDimension(dim_x = 0, dim_y = 0)
    w_value = None]

gevent mode¶

Warning

Before using gevent mode please note that at the time of writing this documentation, tango.gevent requires the latest version 1.0 of gevent (which has been released the day before :-P).

Using gevent cooperative mode in PyTango is relatively easy:

>>> from tango.gevent import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> dev.get_green_mode()
tango.GreenMode.Gevent

>>> print(dev.state())
RUNNING

The tango.gevent.DeviceProxy() API is exactly the same as the standard DeviceProxy. The difference is in the semantics of the methods that involve synchronous network calls (constructor included) which may block the execution for a relatively big amount of time. The list of methods that have been modified to accept gevent semantics are, on the tango.gevent.DeviceProxy():

So how does this work in fact? I see no difference from using the standard DeviceProxy. Well, this is, in fact, one of the goals: be able to use a gevent cooperation without changing the API. Behind the scenes the methods mentioned before have been modified to be able to work cooperatively with other greenlets.

All of the above methods have been boosted with two extra keyword arguments wait and timeout which allow to fine tune the behaviour. The wait parameter is by default set to True meaning wait for the request to finish (the default semantics when not using green mode). If wait is set to True, the timeout determines the maximum time to wait for the method to execute. The default timeout is None which means wait forever. If wait is set to False, the timeout is ignored.

If wait is set to True, the result is the same as executing the standard method on a DeviceProxy. If, wait is set to False, the result will be a gevent.event.AsyncResult. In this case, to get the actual value you will need to do something like:

>>> from tango.gevent import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> result = dev.state(wait=False)
>>> result
<gevent.event.AsyncResult at 0x1a74050>

>>> # this will be the blocking code
>>> state = result.get()
>>> print(state)
RUNNING

Here is another example using read_attribute():

>>> from tango.gevent import DeviceProxy

>>> dev = DeviceProxy("sys/tg_test/1")
>>> result = dev.read_attribute('wave', wait=False)
>>> result
<gevent.event.AsyncResult at 0x1aff54e>

>>> dev_attr = result.get()
>>> print(dev_attr)
DeviceAttribute[
data_format = tango.AttrDataFormat.SPECTRUM
      dim_x = 256
      dim_y = 0
 has_failed = False
   is_empty = False
       name = 'wave'
    nb_read = 256
 nb_written = 0
    quality = tango.AttrQuality.ATTR_VALID
r_dimension = AttributeDimension(dim_x = 256, dim_y = 0)
       time = TimeVal(tv_nsec = 0, tv_sec = 1383923292, tv_usec = 886720)
       type = tango.CmdArgType.DevDouble
      value = array([ -9.61260664e-01,  -9.65924853e-01,  -9.70294813e-01,
        -9.74369212e-01,  -9.78146810e-01,  -9.81626455e-01,
        -9.84807087e-01,  -9.87687739e-01,  -9.90267531e-01,
        ...
        5.15044507e-1])
    w_dim_x = 0
    w_dim_y = 0
w_dimension = AttributeDimension(dim_x = 0, dim_y = 0)
    w_value = None]

Note

due to the internal workings of gevent, setting the wait flag to True (default) doesn’t prevent other greenlets from running in parallel. This is, in fact, one of the major bonus of working with gevent when compared with concurrent.futures

asyncio mode¶

Asyncio mode is similar to gevent but it uses explicit coroutines. You can compare gevent and asyncio examples.

import asyncio
from tango.asyncio import DeviceProxy

async def asyncio_example():
    dev = await DeviceProxy("sys/tg_test/1")
    print(dev.get_green_mode())

    print(await dev.state())

loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio_example())
loop.close()

Below you can find a TCP server example, which runs in an asynchronous mode and waits for a device’s attribute name from a TCP client, then asks the device for a value and replies to the TCP client.

"""A simple TCP server for Tango attributes.

It runs on all interfaces on port 8888:

   $ python tango_tcp_server.py
   Serving on 0.0.0.0 port 8888

It can be accessed using netcat:

   $ ncat localhost 8888
   >>> sys/tg_test/1/ampli
   0.0
   >>> sys/tg_test/1/state
   RUNNING
   >>> sys/tg_test/1/nope
   DevFailed[
   DevError[
        desc = Attribute nope is not supported by device sys/tg_test/1
      origin = AttributeProxy::real_constructor()
      reason = API_UnsupportedAttribute
    severity = ERR]
    ]
   >>> ...
"""

import asyncio
from tango.asyncio import AttributeProxy


async def handle_echo(reader, writer):
    # Write the cursor
    writer.write(b'>>> ')
    # Loop over client request
    async for line in reader:
        request = line.decode().strip()
        # Get attribute value using asyncio green mode
        try:
            proxy = await AttributeProxy(request)
            attr_value = await proxy.read()
            reply = str(attr_value.value)
        # Catch exception if something goes wrong
        except Exception as exc:
            reply = str(exc)
        # Reply to client
        writer.write(reply.encode() + b'\n' + b'>>> ')
    # Close communication
    writer.close()


async def start_serving():
    server = await asyncio.start_server(handle_echo, '0.0.0.0', 8888)
    print('Serving on {} port {}'.format(*server.sockets[0].getsockname()))
    return server


async def stop_serving(server):
    server.close()
    await server.wait_closed()


def main():
    # Start the server
    loop = asyncio.get_event_loop()
    server = loop.run_until_complete(start_serving())
    # Serve requests until Ctrl+C is pressed
    try:
        loop.run_forever()
    except KeyboardInterrupt:
        pass
    # Close the server
    loop.run_until_complete(stop_serving(server))
    loop.close()


if __name__ == '__main__':
    main()

Server green modes¶

PyTango server API from version 9.2.0 supports two green modes: Gevent and Asyncio. Both can be used in writing new device servers in an asynchronous way.

gevent mode¶

This mode lets you convert your existing devices to asynchronous devices easily. You just add green_mode = tango.GreenMode.Gevent line to your device class. Consider this example:

class GeventDevice(Device):
    green_mode = tango.GreenMode.Gevent

Every method in your device class will be treated as a coroutine implicitly. This can be beneficial, but also potentially dangerous as it is a lot harder to debug. You should use this green mode with care. Gevent green mode is useful when you don’t want to change too much in your existing code (or you don’t feel comfortable with writing syntax of asynchronous calls).

Another thing to keep in mind is that when using Gevent green mode is that the Tango monitor lock is disabled, so the client requests can be processed concurrently.

Greenlets can also be used to spawn tasks in the background.

asyncio mode¶

The way asyncio green mode on the server side works is it redirects all user code to an event loop. This means that all user methods become coroutines, so in Python > 3.5 you should define them with async keyword. In Python < 3.5, you should use a @coroutine decorator. This also means that in order to convert existing code of your devices to Asyncio green mode you will have to introduce at least those changes. But, of course, to truly benefit from this green mode (and asynchronous approach in general), you should introduce more far-fetched changes!

The main benefit of asynchronous programing approach is that it lets you control precisely when code is run sequentially without interruptions and when control can be given back to the event loop. It’s especially useful if you want to perform some long operations and don’t want to prevent clients from accessing other parts of your device (attributes, in particular). This means that in Asyncio green mode there is no monitor lock!

The example below shows how asyncio can be used to write an asynchronous Tango device:

"""Demo Tango Device Server using asyncio green mode"""

import asyncio
from tango import DevState, GreenMode
from tango.server import Device, command, attribute


class AsyncioDevice(Device):
    green_mode = GreenMode.Asyncio

    async def init_device(self):
        await super().init_device()
        self.set_state(DevState.ON)

    @command
    async def long_running_command(self):
        self.set_state(DevState.OPEN)
        await asyncio.sleep(2)
        self.set_state(DevState.CLOSE)

    @command
    async def background_task_command(self):
        loop = asyncio.get_event_loop()
        future = loop.create_task(self.coroutine_target())

    async def coroutine_target(self):
        self.set_state(DevState.INSERT)
        await asyncio.sleep(15)
        self.set_state(DevState.EXTRACT)

    @attribute
    async def test_attribute(self):
        await asyncio.sleep(2)
        return 42


if __name__ == '__main__':
    AsyncioDevice.run_server()

PyTango API¶

This module implements the Python Tango Device API mapping.

Data types¶

This chapter describes the mapping of data types between Python and Tango.

Tango has more data types than Python which is more dynamic. The input and output values of the commands are translated according to the array below. Note that if PyTango is compiled with numpy support the numpy type will be the used for the input arguments. Also, it is recomended to use numpy arrays of the appropiate type for output arguments as well, as they tend to be much more efficient.

For scalar types (SCALAR)

Tango data type	Python 2.x type	Python 3.x type (New in PyTango 8.0)
DEV_VOID	No data	No data
DEV_BOOLEAN	`bool`	`bool`
DEV_SHORT	`int`	`int`
DEV_LONG	`int`	`int`
DEV_LONG64	`long` (on a 32 bits computer) `int` (on a 64 bits computer)	`int`
DEV_FLOAT	`float`	`float`
DEV_DOUBLE	`float`	`float`
DEV_USHORT	`int`	`int`
DEV_ULONG	`int`	`int`
DEV_ULONG64	`long` (on a 32 bits computer) `int` (on a 64 bits computer)	`int`
DEV_STRING	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
DEV_ENCODED (New in PyTango 8.0)	sequence of two elements: `str` `bytes` (for any value of extract_as)	sequence of two elements: `str` (decoded with latin-1, aka ISO-8859-1) `bytes` (for any value of extract_as, except String. In this case it is `str` (decoded with default python encoding utf-8))
DEV_ENUM (New in PyTango 9.0)	`int` (for value) `list` <`str`> (for enum_labels) Note: direct attribute access via DeviceProxy will return enumerated type `enum.IntEnum`. This type uses the package enum34.	`int` (for value) `list` <`str`> (for enum_labels) Note: direct attribute access via DeviceProxy will return enumerated type `enum.IntEnum`. Python < 3.4, uses the package enum34. Python >= 3.4, uses standard package enum.

For array types (SPECTRUM/IMAGE)

Tango data type	ExtractAs	Data type (Python 2.x)	Data type (Python 3.x) (New in PyTango 8.0)
DEVVAR_CHARARRAY	Numpy	`numpy.ndarray` (dtype= `numpy.uint8`)	`numpy.ndarray` (dtype= `numpy.uint8`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`int`>	`list` <`int`>
	Tuple	`tuple` <`int`>	`tuple` <`int`>
DEVVAR_SHORTARRAY or (DEV_SHORT + SPECTRUM) or (DEV_SHORT + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint16`)	`numpy.ndarray` (dtype= `numpy.uint16`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`int`>	`list` <`int`>
	Tuple	`tuple` <`int`>	`tuple` <`int`>
DEVVAR_LONGARRAY or (DEV_LONG + SPECTRUM) or (DEV_LONG + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint32`)	`numpy.ndarray` (dtype= `numpy.uint32`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`int`>	`list` <`int`>
	Tuple	`tuple` <`int`>	`tuple` <`int`>
DEVVAR_LONG64ARRAY or (DEV_LONG64 + SPECTRUM) or (DEV_LONG64 + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint64`)	`numpy.ndarray` (dtype= `numpy.uint64`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <int (64 bits) / long (32 bits)>	`list` <`int`>
	Tuple	`tuple` <int (64 bits) / long (32 bits)>	`tuple` <`int`>
DEVVAR_FLOATARRAY or (DEV_FLOAT + SPECTRUM) or (DEV_FLOAT + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.float32`)	`numpy.ndarray` (dtype= `numpy.float32`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`float`>	`list` <`float`>
	Tuple	`tuple` <`float`>	`tuple` <`float`>
DEVVAR_DOUBLEARRAY or (DEV_DOUBLE + SPECTRUM) or (DEV_DOUBLE + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.float64`)	`numpy.ndarray` (dtype= `numpy.float64`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`float`>	`list` <`float`>
	Tuple	`tuple` <`float`>	`tuple` <`float`>
DEVVAR_USHORTARRAY or (DEV_USHORT + SPECTRUM) or (DEV_USHORT + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint16`)	`numpy.ndarray` (dtype= `numpy.uint16`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`int`>	`list` <`int`>
	Tuple	`tuple` <`int`>	`tuple` <`int`>
DEVVAR_ULONGARRAY or (DEV_ULONG + SPECTRUM) or (DEV_ULONG + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint32`)	`numpy.ndarray` (dtype= `numpy.uint32`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <`int`>	`list` <`int`>
	Tuple	`tuple` <`int`>	`tuple` <`int`>
DEVVAR_ULONG64ARRAY or (DEV_ULONG64 + SPECTRUM) or (DEV_ULONG64 + IMAGE)	Numpy	`numpy.ndarray` (dtype= `numpy.uint64`)	`numpy.ndarray` (dtype= `numpy.uint64`)
	Bytes	`bytes` (which is in fact equal to `str`)	`bytes`
	ByteArray	`bytearray`	`bytearray`
	String	`str`	`str` (decoded with latin-1, aka ISO-8859-1)
	List	`list` <int (64 bits) / long (32 bits)>	`list` <`int`>
	Tuple	`tuple` <int (64 bits) / long (32 bits)>	`tuple` <`int`>
DEVVAR_STRINGARRAY or (DEV_STRING + SPECTRUM) or (DEV_STRING + IMAGE)		sequence<`str`>	sequence<`str`> (decoded with latin-1, aka ISO-8859-1)
DEV_LONGSTRINGARRAY		sequence of two elements: `numpy.ndarray` (dtype= `numpy.int32`) or sequence<`int`> sequence<`str`>	sequence of two elements: `numpy.ndarray` (dtype= `numpy.int32`) or sequence<`int`> sequence<`str`> (decoded with latin-1, aka ISO-8859-1)
DEV_DOUBLESTRINGARRAY		sequence of two elements: `numpy.ndarray` (dtype= `numpy.float64`) or sequence<`int`> sequence<`str`>	sequence of two elements: `numpy.ndarray` (dtype= `numpy.float64`) or sequence<`int`> sequence<`str`> (decoded with latin-1, aka ISO-8859-1)

For SPECTRUM and IMAGES the actual sequence object used depends on the context where the tango data is used, and the availability of numpy.

for properties the sequence is always a list. Example:

>>> import tango
>>> db = tango.Database()
>>> s = db.get_property(["TangoSynchrotrons"])
>>> print type(s)
<type 'list'>

for attribute/command values
- numpy.ndarray if PyTango was compiled with numpy support (default) and numpy is installed.
- list otherwise

Pipe data types¶

Pipes require different data types. You can think of them as a structured type.

A pipe transports data which is called a blob. A blob consists of name and a list of fields. Each field is called data element. Each data element consists of a name and a value. Data element names must be unique in the same blob.

The value can be of any of the SCALAR or SPECTRUM tango data types (except DevEnum).

Additionally, the value can be a blob itself.

In PyTango, a blob is represented by a sequence of two elements:

blob name (str)
data is either:
- sequence (list, tuple, or other) of data elements where each element is a dict with the following keys:
  - name (mandatory): (str) data element name
  - value (mandatory): data (compatible with any of the SCALAR or SPECTRUM data types except DevEnum). If value is to be a sub-blob then it should be sequence of [blob name, sequence of data elements] (see above)
  - dtype (optional, mandatory if a DevEncoded is required): see Data type equivalence. If dtype key is not given, PyTango will try to find the proper tango type by inspecting the value.
- a dict where key is the data element name and value is the data element value (compact version)

When using the compact dictionary version note that the order of the data elements is lost. If the order is important for you, consider using collections.OrderedDict instead (if you have python >=2.7. If not you can use ordereddict backport module available on pypi). Also, in compact mode it is not possible to enforce a specific type. As a consequence, DevEncoded is not supported in compact mode.

The description sounds more complicated that it actually is. Here are some practical examples of what you can return in a server as a read request from a pipe:

import numpy as np

# plain (one level) blob showing different tango data types
# (explicity and implicit):

PIPE0 = \
('BlobCase0',
 ({'name': 'DE1', 'value': 123,},                                # converts to DevLong64
  {'name': 'DE2', 'value': np.int32(456),},                      # converts to DevLong
  {'name': 'DE3', 'value': 789, 'dtype': 'int32'},               # converts to DevLong
  {'name': 'DE4', 'value': np.uint32(123)},                      # converts to DevULong
  {'name': 'DE5', 'value': range(5), 'dtype': ('uint16',)},      # converts to DevVarUShortArray
  {'name': 'DE6', 'value': [1.11, 2.22], 'dtype': ('float64',)}, # converts to DevVarDoubleArray
  {'name': 'DE7', 'value': numpy.zeros((100,))},                 # converts to DevVarDoubleArray
  {'name': 'DE8', 'value': True},                                # converts to DevBoolean
 )
)


# similar as above but in compact version (implicit data type conversion):

PIPE1 = \
('BlobCase1', dict(DE1=123, DE2=np.int32(456), DE3=np.int32(789),
                   DE4=np.uint32(123), DE5=np.arange(5, dtype='uint16'),
                   DE6=[1.11, 2.22], DE7=numpy.zeros((100,)),
                   DE8=True)
)

# similar as above but order matters so we use an ordered dict:

import collections

data = collections.OrderedDict()
data['DE1'] = 123
data['DE2'] = np.int32(456)
data['DE3'] = np.int32(789)
data['DE4'] = np.uint32(123)
data['DE5'] = np.arange(5, dtype='uint16')
data['DE6'] = [1.11, 2.22]
data['DE7'] = numpy.zeros((100,))
data['DE8'] = True

PIPE2 = 'BlobCase2', data

# another plain blob showing string, string array and encoded data types:

PIPE3 = \
('BlobCase3',
 ({'name': 'stringDE',  'value': 'Hello'},
  {'name': 'VectorStringDE', 'value': ('bonjour', 'le', 'monde')},
  {'name': 'DevEncodedDE', 'value': ('json', '"isn\'t it?"'), 'dtype': 'bytes'},
 )
)

# blob with sub-blob which in turn has a sub-blob

PIPE4 = \
('BlobCase4',
 ({'name': '1DE', 'value': ('Inner', ({'name': '1_1DE', 'value': 'Grenoble'},
                                      {'name': '1_2DE', 'value': ('InnerInner',
                                                                  ({'name': '1_1_1DE', 'value': np.int32(111)},
                                                                   {'name': '1_1_2DE', 'value': [3.33]}))
                                     })
  )},
  {'name': '2DE', 'value': (3,4,5,6), 'dtype': ('int32',) },
 )
)

DevEnum pythonic usage¶

When using regular tango DeviceProxy and AttributeProxy DevEnum is treated just like in cpp tango (see enumerated attributes for more info). However, since PyTango >= 9.2.5 there is a more pythonic way of using DevEnum data types if you use the high level API, both in server and client side.

In server side you can use python enum.IntEnum class to deal with DevEnum attributes:

import time
from enum import IntEnum
from tango import AttrWriteType
from tango.server import Device, attribute, command


class Noon(IntEnum):
    AM = 0  # DevEnum's must start at 0
    PM = 1  # and increment by 1


class DisplayType(IntEnum):
    ANALOG = 0  # DevEnum's must start at 0
    DIGITAL = 1  # and increment by 1


class Clock(Device):

    display_type = DisplayType(0)

    @attribute(dtype=float)
    def time(self):
        return time.time()

    gmtime = attribute(dtype=(int,), max_dim_x=9)

    def read_gmtime(self):
        return time.gmtime()

    @attribute(dtype=Noon)
    def noon(self):
        time_struct = time.gmtime(time.time())
        return Noon.AM if time_struct.tm_hour < 12 else Noon.PM

    display = attribute(dtype=DisplayType, access=AttrWriteType.READ_WRITE)

    def read_display(self):
        return self.display_type

    def write_display(self, display_type):
        self.display_type = display_type

    @command(dtype_in=float, dtype_out=str)
    def ctime(self, seconds):
        """
        Convert a time in seconds since the Epoch to a string in local time.
        This is equivalent to asctime(localtime(seconds)). When the time tuple
        is not present, current time as returned by localtime() is used.
        """
        return time.ctime(seconds)

    @command(dtype_in=(int,), dtype_out=float)
    def mktime(self, tupl):
        return time.mktime(tupl)


if __name__ == "__main__":
    Clock.run_server()

On the client side you can also use a pythonic approach for using DevEnum attributes:

import sys
import PyTango

if len(sys.argv) != 2:
    print("must provide one and only one clock device name")
    sys.exit(1)

clock = PyTango.DeviceProxy(sys.argv[1])
t = clock.time
gmt = clock.gmtime
noon = clock.noon
display = clock.display
print(t)
print(gmt)
print(noon, noon.name, noon.value)
if noon == noon.AM:
    print('Good morning!')
print(clock.ctime(t))
print(clock.mktime(gmt))
print(display, display.name, display.value)
clock.display = display.ANALOG
clock.display = 'DIGITAL'  # you can use a valid string to set the value
print(clock.display, clock.display.name, clock.display.value)
display_type = type(display)  # or even create your own IntEnum type
analog = display_type(0)
clock.display = analog
print(clock.display, clock.display.name, clock.display.value)
clock.display = clock.display.DIGITAL
print(clock.display, clock.display.name, clock.display.value)

Client API¶

DeviceProxy¶

class tango.DeviceProxy(*args, **kwargs)¶

Bases: _tango.Connection

DeviceProxy is the high level Tango object which provides the client with an easy-to-use interface to TANGO devices. DeviceProxy provides interfaces to all TANGO Device interfaces.The DeviceProxy manages timeouts, stateless connections and reconnection if the device server is restarted. To create a DeviceProxy, a Tango Device name must be set in the object constructor.

Example :: dev = tango.DeviceProxy(“sys/tg_test/1”)

DeviceProxy(dev_name, green_mode=None, wait=True, timeout=True) -> DeviceProxy DeviceProxy(self, dev_name, need_check_acc, green_mode=None, wait=True, timeout=True) -> DeviceProxy

Creates a new DeviceProxy.

Parameters

dev_name (str) – the device name or alias
need_check_acc (bool) – in first version of the function it defaults to True. Determines if at creation time of DeviceProxy it should check for channel access (rarely used)
green_mode (GreenMode) – determines the mode of execution of the device (including. the way it is created). Defaults to the current global green_mode (check get_green_mode() and set_green_mode())
wait (bool) – whether or not to wait for result. If green_mode Ignored when green_mode is Synchronous (always waits).
timeout (float) – The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when green_mode is Synchronous or wait is False.

Returns

if green_mode is Synchronous or wait is True:: DeviceProxy
elif green_mode is Futures:: concurrent.futures.Future
elif green_mode is Gevent:: gevent.event.AsynchResult

Throws

: class:~tango.DevFailed if green_mode is Synchronous or wait is True and there is an error creating the device.
: class:concurrent.futures.TimeoutError if green_mode is Futures, wait is False, timeout is not None and the time to create the device has expired.
: class:gevent.timeout.Timeout if green_mode is Gevent, wait is False, timeout is not None and the time to create the device has expired.

New in version 8.1.0: green_mode parameter. wait parameter. timeout parameter.

add_logging_target(self, target_type_target_name) → None¶

Adds a new logging target to the device.

The target_type_target_name input parameter must follow the format: target_type::target_name. Supported target types are: console, file and device. For a device target, the target_name part of the target_type_target_name parameter must contain the name of a log consumer device (as defined in A.8). For a file target, target_name is the full path to the file to log to. If omitted, the device’s name is used to build the file name (which is something like domain_family_member.log). Finally, the target_name part of the target_type_target_name input parameter is ignored in case of a console target and can be omitted.

Parameters

target_type_target_name: (str) logging target

Return

None

Throws

DevFailed from device

New in PyTango 7.0.0

adm_name(self) → str¶: Return the name of the corresponding administrator device. This is useful if you need to send an administration command to the device server, e.g restart it

New in PyTango 3.0.4

alias(self) → str¶

Return the device alias if one is defined. Otherwise, throws exception.

Return: (str) device alias

attribute_history(self, attr_name, depth, extract_as=ExtractAs.Numpy) → sequence<DeviceAttributeHistory>¶

Retrieve attribute history from the attribute polling buffer. See chapter on Advanced Feature for all details regarding polling

Parameters

attr_name: (str) Attribute name.
depth: (int) The wanted history depth.
extract_as: (ExtractAs)

Return

This method returns a vector of DeviceAttributeHistory types.

Throws

NonSupportedFeature, ConnectionFailed, CommunicationFailed, DevFailed from device

attribute_list_query(self) → sequence<AttributeInfo>¶

Query the device for info on all attributes. This method returns a sequence of tango.AttributeInfo.

Parameters: None
Return: (sequence<AttributeInfo>) containing the attributes configuration
Throws: ConnectionFailed, CommunicationFailed, DevFailed from device

attribute_list_query_ex(self) → sequence<AttributeInfoEx>¶

Query the device for info on all attributes. This method returns a sequence of tango.AttributeInfoEx.

Parameters: None
Return: (sequence<AttributeInfoEx>) containing the attributes configuration
Throws: ConnectionFailed, CommunicationFailed, DevFailed from device

attribute_query(self, attr_name) → AttributeInfoEx¶

Query the device for information about a single attribute.

Parameters

attr_name: (str) the attribute name

Return

(AttributeInfoEx) containing the attribute configuration

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

black_box(self, n) → sequence<str>¶

Get the last commands executed on the device server

Parameters

n: n number of commands to get

Return

(sequence<str>) sequence of strings containing the date, time, command and from which client computer the command was executed

Example

print(black_box(4))

cancel_all_polling_asynch_request(self) → None¶

Cancel all running asynchronous request

This is a client side call. Obviously, the calls cannot be aborted while it is running in the device.

Parameters: None
Return: None

New in PyTango 7.0.0

cancel_asynch_request(self, id) → None¶

Cancel a running asynchronous request

This is a client side call. Obviously, the call cannot be aborted while it is running in the device.

Parameters

id: The asynchronous call identifier

Return

None

New in PyTango 7.0.0

command_history(self, cmd_name, depth) → sequence<DeviceDataHistory>¶

Retrieve command history from the command polling buffer. See chapter on Advanced Feature for all details regarding polling

Parameters

cmd_name: (str) Command name.
depth: (int) The wanted history depth.

Return

This method returns a vector of DeviceDataHistory types.

Throws

NonSupportedFeature, ConnectionFailed, CommunicationFailed, DevFailed from device

command_inout(self, cmd_name, cmd_param=None, green_mode=None, wait=True, timeout=None) → any¶

Execute a command on a device.

Parameters

cmd_name

(str) Command name.

cmd_param

(any) It should be a value of the type expected by the command or a DeviceData object with this value inserted. It can be ommited if the command should not get any argument.

green_mode

(GreenMode) Defaults to the current DeviceProxy GreenMode. (see get_green_mode() and set_green_mode()).

wait

(bool) whether or not to wait for result. If green_mode is Synchronous, this parameter is ignored as it always waits for the result. Ignored when green_mode is Synchronous (always waits).

timeout

(float) The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when green_mode is Synchronous or wait is False.

Return

The result of the command. The type depends on the command. It may be None.

Throws

ConnectionFailed, CommunicationFailed, DeviceUnlocked, DevFailed from device TimeoutError (green_mode == Futures) If the future didn’t finish executing before the given timeout. Timeout (green_mode == Gevent) If the async result didn’t finish executing before the given timeout.

New in version 8.1.0: green_mode parameter. wait parameter. timeout parameter.

command_inout_asynch(self, cmd_name) → id¶

command_inout_asynch(self, cmd_name, cmd_param) → id

command_inout_asynch(self, cmd_name, cmd_param, forget) → id

Execute asynchronously (polling model) a command on a device

Parameters

cmd_name

(str) Command name.

cmd_param

(any) It should be a value of the type expected by the command or a DeviceData object with this value inserted. It can be ommited if the command should not get any argument. If the command should get no argument and you want to set the ‘forget’ param, use None for cmd_param.

forget

(bool) If this flag is set to true, this means that the client does not care at all about the server answer and will even not try to get it. Default value is False. Please, note that device re-connection will not take place (in case it is needed) if the fire and forget mode is used. Therefore, an application using only fire and forget requests is not able to automatically re-connnect to device.

Return

(int) This call returns an asynchronous call identifier which is needed to get the command result (see command_inout_reply)

Throws

ConnectionFailed, TypeError, anything thrown by command_query

command_inout_asynch( self, cmd_name, callback) -> None

command_inout_asynch( self, cmd_name, cmd_param, callback) -> None

Execute asynchronously (callback model) a command on a device.

Parameters

cmd_name

(str) Command name.

cmd_param

(any)It should be a value of the type expected by the command or a DeviceData object with this value inserted. It can be ommited if the command should not get any argument.

callback

Any callable object (function, lambda…) or any oject with a method named “cmd_ended”.

Return

None

Throws

ConnectionFailed, TypeError, anything thrown by command_query

Important

by default, TANGO is initialized with the polling model. If you want to use the push model (the one with the callback parameter), you need to change the global TANGO model to PUSH_CALLBACK. You can do this with the tango.:class:`ApiUtil().set_asynch_cb_sub_model`

command_inout_raw(self, cmd_name, cmd_param=None) → DeviceData¶

Execute a command on a device.

Parameters

cmd_name: (str) Command name.
cmd_param: (any) It should be a value of the type expected by the command or a DeviceData object with this value inserted. It can be ommited if the command should not get any argument.

Return

A DeviceData object.

Throws

ConnectionFailed, CommunicationFailed, DeviceUnlocked, DevFailed from device

command_inout_reply(self, id) → DeviceData¶

Check if the answer of an asynchronous command_inout is arrived (polling model). If the reply is arrived and if it is a valid reply, it is returned to the caller in a DeviceData object. If the reply is an exception, it is re-thrown by this call. An exception is also thrown in case of the reply is not yet arrived.

Parameters

id

(int) Asynchronous call identifier.

Return

(DeviceData)

Throws

AsynCall, AsynReplyNotArrived, CommunicationFailed, DevFailed from device

command_inout_reply(self, id, timeout) -> DeviceData

Check if the answer of an asynchronous command_inout is arrived (polling model). id is the asynchronous call identifier. If the reply is arrived and if it is a valid reply, it is returned to the caller in a DeviceData object. If the reply is an exception, it is re-thrown by this call. If the reply is not yet arrived, the call will wait (blocking the process) for the time specified in timeout. If after timeout milliseconds, the reply is still not there, an exception is thrown. If timeout is set to 0, the call waits until the reply arrived.

Parameters

id

(int) Asynchronous call identifier.

timeout

(int)

Return

(DeviceData)

Throws

AsynCall, AsynReplyNotArrived, CommunicationFailed, DevFailed from device

command_inout_reply_raw(self, id, timeout) → DeviceData¶

Check if the answer of an asynchronous command_inout is arrived (polling model). id is the asynchronous call identifier. If the reply is arrived and if it is a valid reply, it is returned to the caller in a DeviceData object. If the reply is an exception, it is re-thrown by this call. If the reply is not yet arrived, the call will wait (blocking the process) for the time specified in timeout. If after timeout milliseconds, the reply is still not there, an exception is thrown. If timeout is set to 0, the call waits until the reply arrived.

Parameters

id: (int) Asynchronous call identifier.
timeout: (int)

Return

(DeviceData)

Throws

AsynCall, AsynReplyNotArrived, CommunicationFailed, DevFailed from device

command_list_query(self) → sequence<CommandInfo>¶

Query the device for information on all commands.

Parameters: None
Return: (CommandInfoList) Sequence of CommandInfo objects

command_query(self, command) → CommandInfo¶

Query the device for information about a single command.

Parameters

command: (str) command name

Return

(CommandInfo) object

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

Example

com_info = dev.command_query(""DevString"")
print(com_info.cmd_name)
print(com_info.cmd_tag)
print(com_info.in_type)
print(com_info.out_type)
print(com_info.in_type_desc)
print(com_info.out_type_desc)
print(com_info.disp_level)

See CommandInfo documentation string form more detail

connect(self, corba_name) → None¶

Creates a connection to a TANGO device using it’s stringified CORBA reference i.e. IOR or corbaloc.

Parameters

corba_name: (str) Name of the CORBA object

Return

None

New in PyTango 7.0.0

delete_property(self, value)¶

Delete a the given of properties for this device. This method accepts the following types as value parameter:

string [in] - single property to be deleted

tango.DbDatum [in] - single property data to be deleted

tango.DbData [in] - several property data to be deleted

sequence<string> [in]- several property data to be deleted

sequence<DbDatum> [in] - several property data to be deleted

dict<str, obj> [in] - keys are property names to be deleted (values are ignored)

dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Parameters

value

can be one of the following:

string [in] - single property data to be deleted
tango.DbDatum [in] - single property data to be deleted
tango.DbData [in] - several property data to be deleted
sequence<string> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, obj> [in] - keys are property names to be deleted (values are ignored)
dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError), TypeError

description(self) → str¶

Get device description.

Parameters: None
Return: (str) describing the device

dev_name(self) → str¶

Return the device name as it is stored locally

Parameters: None
Return: (str)

event_queue_size(self, event_id) → int¶

Returns the number of stored events in the event reception buffer. After every call to DeviceProxy.get_events(), the event queue size is 0. During event subscription the client must have chosen the ‘pull model’ for this event. event_id is the event identifier returned by the DeviceProxy.subscribe_event() method.

Parameters

event_id: (int) event identifier

Return

an integer with the queue size

Throws

EventSystemFailed

New in PyTango 7.0.0

get_access_control(self) → AccessControlType¶

Returns the current access control type

Parameters: None
Return: (AccessControlType) The current access control type

New in PyTango 7.0.0

get_access_right(self) → AccessControlType¶

Returns the current access control type

Parameters: None
Return: (AccessControlType) The current access control type

New in PyTango 8.0.0

get_asynch_replies(self, call_timeout) → None¶

Try to obtain data returned by a command asynchronously requested. This method blocks for the specified timeout if the reply is not yet arrived. This method fires callback when the reply arrived. If the timeout is set to 0, the call waits undefinitely for the reply

Parameters

call_timeout: (int) timeout in miliseconds

Return

None

New in PyTango 7.0.0

get_attribute_config(self, name) → AttributeInfoEx¶

Return the attribute configuration for a single attribute.

Parameters

name

(str) attribute name

Return

(AttributeInfoEx) Object containing the attribute information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

Deprecated: use get_attribute_config_ex instead

get_attribute_config( self, names) -> AttributeInfoList

Return the attribute configuration for the list of specified attributes. To get all the attributes pass a sequence containing the constant tango.:class:constants.AllAttr

Parameters

names

(sequence<str>) attribute names

Return

(AttributeInfoList) Object containing the attributes information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

Deprecated: use get_attribute_config_ex instead

get_attribute_config_ex(self, name) → AttributeInfoListEx :¶

Return the extended attribute configuration for a single attribute.

Parameters

name

(str) attribute name

Return

(AttributeInfoEx) Object containing the attribute information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

get_attribute_config( self, names) -> AttributeInfoListEx :

Return the extended attribute configuration for the list of specified attributes. To get all the attributes pass a sequence containing the constant tango.:class:constants.AllAttr

Parameters

names

(sequence<str>) attribute names

Return

(AttributeInfoList) Object containing the attributes information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

get_attribute_list(self) → sequence<str>¶

Return the names of all attributes implemented for this device.

Parameters: None
Return: sequence<str>
Throws: ConnectionFailed, CommunicationFailed, DevFailed from device

get_attribute_poll_period(self, attr_name) → int¶

Return the attribute polling period.

Parameters

attr_name: (str) attribute name

Return

polling period in milliseconds

get_command_config(self) → CommandInfoList¶

Return the command configuration for all commands.

Return

(CommandInfoList) Object containing the commands information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

get_command_config( self, name) -> CommandInfo

Return the command configuration for a single command.

Parameters

name

(str) command name

Return

(CommandInfo) Object containing the command information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

get_command_config( self, names) -> CommandInfoList

Return the command configuration for the list of specified commands.

Parameters

names

(sequence<str>) command names

Return

(CommandInfoList) Object containing the commands information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

get_command_list(self) → sequence<str>¶

Return the names of all commands implemented for this device.

Parameters: None
Return: sequence<str>
Throws: ConnectionFailed, CommunicationFailed, DevFailed from device

get_command_poll_period(self, cmd_name) → int¶

Return the command polling period.

Parameters

cmd_name: (str) command name

Return

polling period in milliseconds

get_db_host(self) → str¶

Returns a string with the database host.

Parameters: None
Return: (str)

New in PyTango 7.0.0

get_db_port(self) → str¶

Returns a string with the database port.

Parameters: None
Return: (str)

New in PyTango 7.0.0

get_db_port_num(self) → int¶

Returns an integer with the database port.

Parameters: None
Return: (int)

New in PyTango 7.0.0

get_dev_host(self) → str¶

Returns the current host

Parameters: None
Return: (str) the current host

New in PyTango 7.2.0

get_dev_port(self) → str¶

Returns the current port

Parameters: None
Return: (str) the current port

New in PyTango 7.2.0

get_device_db(self) → Database¶

Returns the internal database reference

Parameters: None
Return: (Database) object

New in PyTango 7.0.0

get_events(event_id, callback=None, extract_as=Numpy) → None¶

The method extracts all waiting events from the event reception buffer.

If callback is not None, it is executed for every event. During event subscription the client must have chosen the pull model for this event. The callback will receive a parameter of type EventData, AttrConfEventData or DataReadyEventData depending on the type of the event (event_type parameter of subscribe_event).

If callback is None, the method extracts all waiting events from the event reception buffer. The returned event_list is a vector of EventData, AttrConfEventData or DataReadyEventData pointers, just the same data the callback would have received.

Parameters

event_id: (int) is the event identifier returned by the DeviceProxy.subscribe_event() method.
callback: (callable) Any callable object or any object with a “push_event” method.
extract_as: (ExtractAs)

Return

None

Throws

EventSystemFailed, TypeError, ValueError

See Also

subscribe_event

New in PyTango 7.0.0

get_fqdn(self) → str¶

Returns the fully qualified domain name

Parameters: None
Return: (str) the fully qualified domain name

New in PyTango 7.2.0

get_from_env_var(self) → bool¶

Returns True if determined by environment variable or False otherwise

Parameters: None
Return: (bool)

New in PyTango 7.0.0

get_green_mode()¶

Returns the green mode in use by this DeviceProxy.

Returns: the green mode in use by this DeviceProxy.
Return type: GreenMode

AttributeProxy¶

class tango.AttributeProxy(*args, **kwds)¶

AttributeProxy is the high level Tango object which provides the client with an easy-to-use interface to TANGO attributes.

To create an AttributeProxy, a complete attribute name must be set in the object constructor.

Example:: att = AttributeProxy(“tango/tangotest/1/long_scalar”)

Note: PyTango implementation of AttributeProxy is in part a python reimplementation of the AttributeProxy found on the C++ API.

delete_property(self, value) → None¶

Delete a the given of properties for this attribute. This method accepts the following types as value parameter:

string [in] - single property to be deleted

tango.DbDatum [in] - single property data to be deleted

tango.DbData [in] - several property data to be deleted

sequence<string> [in]- several property data to be deleted

sequence<DbDatum> [in] - several property data to be deleted

dict<str, obj> [in] - keys are property names to be deleted (values are ignored)

dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Parameters

value

can be one of the following:

string [in] - single property data to be deleted
tango.DbDatum [in] - single property data to be deleted
tango.DbData [in] - several property data to be deleted
sequence<string> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, obj> [in] - keys are property names to be deleted (values are ignored)
dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Return

None

Throws

ConnectionFailed, CommunicationFailed DevFailed from device (DB_SQLError), TypeError

event_queue_size(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().event_queue_size(…)

For convenience, here is the documentation of DeviceProxy.event_queue_size(…):

event_queue_size(self, event_id) -> int

Returns the number of stored events in the event reception buffer. After every call to DeviceProxy.get_events(), the event queue size is 0. During event subscription the client must have chosen the ‘pull model’ for this event. event_id is the event identifier returned by the DeviceProxy.subscribe_event() method.

Parameters

event_id

(int) event identifier

Return

an integer with the queue size

Throws

EventSystemFailed

New in PyTango 7.0.0

get_config(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().get_attribute_config(self.name(), …)

For convenience, here is the documentation of DeviceProxy.get_attribute_config(…):

get_attribute_config( self, name) -> AttributeInfoEx

Return the attribute configuration for a single attribute.

Parameters

name

(str) attribute name

Return

(AttributeInfoEx) Object containing the attribute information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

Deprecated: use get_attribute_config_ex instead

get_attribute_config( self, names) -> AttributeInfoList

Return the attribute configuration for the list of specified attributes. To get all the attributes pass a sequence containing the constant tango.:class:constants.AllAttr

Parameters

names

(sequence<str>) attribute names

Return

(AttributeInfoList) Object containing the attributes information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

Deprecated: use get_attribute_config_ex instead

get_device_proxy(self) → DeviceProxy¶

A method which returns the device associated to the attribute

Parameters: None
Return: (DeviceProxy)

get_events(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().get_events(…)

For convenience, here is the documentation of DeviceProxy.get_events(…):

get_events( event_id, callback=None, extract_as=Numpy) -> None

The method extracts all waiting events from the event reception buffer.

If callback is not None, it is executed for every event. During event subscription the client must have chosen the pull model for this event. The callback will receive a parameter of type EventData, AttrConfEventData or DataReadyEventData depending on the type of the event (event_type parameter of subscribe_event).

If callback is None, the method extracts all waiting events from the event reception buffer. The returned event_list is a vector of EventData, AttrConfEventData or DataReadyEventData pointers, just the same data the callback would have received.

Parameters

event_id

(int) is the event identifier returned by the DeviceProxy.subscribe_event() method.

callback

(callable) Any callable object or any object with a “push_event” method.

extract_as

(ExtractAs)

Return

None

Throws

EventSystemFailed, TypeError, ValueError

See Also

subscribe_event

New in PyTango 7.0.0

get_last_event_date(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().get_last_event_date(…)

For convenience, here is the documentation of DeviceProxy.get_last_event_date(…):

get_last_event_date(self, event_id) -> TimeVal

Returns the arrival time of the last event stored in the event reception buffer. After every call to DeviceProxy:get_events(), the event reception buffer is empty. In this case an exception will be returned. During event subscription the client must have chosen the ‘pull model’ for this event. event_id is the event identifier returned by the DeviceProxy.subscribe_event() method.

Parameters

event_id

(int) event identifier

Return

(tango.TimeVal) representing the arrival time

Throws

EventSystemFailed

New in PyTango 7.0.0

get_poll_period(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().get_attribute_poll_period(self.name(), …)

For convenience, here is the documentation of DeviceProxy.get_attribute_poll_period(…):

get_attribute_poll_period(self, attr_name) -> int

Return the attribute polling period.

Parameters

attr_name

(str) attribute name

Return

polling period in milliseconds

get_property(self, propname, value) → DbData¶

Get a (list) property(ies) for an attribute.

This method accepts the following types as propname parameter: 1. string [in] - single property data to be fetched 2. sequence<string> [in] - several property data to be fetched 3. tango.DbDatum [in] - single property data to be fetched 4. tango.DbData [in,out] - several property data to be fetched. 5. sequence<DbDatum> - several property data to be feteched

Note: for cases 3, 4 and 5 the ‘value’ parameter if given, is IGNORED.

If value is given it must be a tango.DbData that will be filled with the property values

Parameters

propname: (str) property(ies) name(s)
value: (tango.DbData) (optional, default is None meaning that the method will create internally a tango.DbData and return it filled with the property values

Return

(DbData) containing the property(ies) value(s). If a tango.DbData is given as parameter, it returns the same object otherwise a new tango.DbData is returned

Throws

NonDbDevice, ConnectionFailed (with database), CommunicationFailed (with database), DevFailed from database device

get_transparency_reconnection(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().get_transparency_reconnection(…)

For convenience, here is the documentation of DeviceProxy.get_transparency_reconnection(…):

get_transparency_reconnection(self) -> bool

Returns the device transparency reconnection flag.

Parameters

None

Return

(bool) True if transparency reconnection is set or False otherwise

history(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().attribute_history(self.name(), …)

For convenience, here is the documentation of DeviceProxy.attribute_history(…):

attribute_history(self, attr_name, depth, extract_as=ExtractAs.Numpy) -> sequence<DeviceAttributeHistory>

Retrieve attribute history from the attribute polling buffer. See chapter on Advanced Feature for all details regarding polling

Parameters

attr_name

(str) Attribute name.

depth

(int) The wanted history depth.

extract_as

(ExtractAs)

Return

This method returns a vector of DeviceAttributeHistory types.

Throws

NonSupportedFeature, ConnectionFailed, CommunicationFailed, DevFailed from device

is_event_queue_empty(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().is_event_queue_empty(…)

For convenience, here is the documentation of DeviceProxy.is_event_queue_empty(…):

is_event_queue_empty(self, event_id) -> bool

Returns true when the event reception buffer is empty. During event subscription the client must have chosen the ‘pull model’ for this event. event_id is the event identifier returned by the DeviceProxy.subscribe_event() method.

Parameters

event_id

(int) event identifier

Return

(bool) True if queue is empty or False otherwise

Throws

EventSystemFailed

New in PyTango 7.0.0

is_polled(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().is_attribute_polled(self.name(), …)

For convenience, here is the documentation of DeviceProxy.is_attribute_polled(…):

is_attribute_polled(self, attr_name) -> bool

True if the attribute is polled.

Parameters

attr_name

(str) attribute name

Return

boolean value

name(self) → str¶

Returns the attribute name

Parameters: None
Return: (str) with the attribute name

ping(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().ping(…)

For convenience, here is the documentation of DeviceProxy.ping(…):

ping(self) -> int

A method which sends a ping to the device

Parameters

None

Return

(int) time elapsed in microseconds

Throws

exception if device is not alive

poll(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().poll_attribute(self.name(), …)

For convenience, here is the documentation of DeviceProxy.poll_attribute(…):

poll_attribute(self, attr_name, period) -> None

Add an attribute to the list of polled attributes.

Parameters

attr_name

(str) attribute name

period

(int) polling period in milliseconds

Return

None

put_property(self, value) → None¶

Insert or update a list of properties for this attribute. This method accepts the following types as value parameter: 1. tango.DbDatum - single property data to be inserted 2. tango.DbData - several property data to be inserted 3. sequence<DbDatum> - several property data to be inserted 4. dict<str, DbDatum> - keys are property names and value has data to be inserted 5. dict<str, seq<str>> - keys are property names and value has data to be inserted 6. dict<str, obj> - keys are property names and str(obj) is property value

Parameters

value: can be one of the following: 1. tango.DbDatum - single property data to be inserted 2. tango.DbData - several property data to be inserted 3. sequence<DbDatum> - several property data to be inserted 4. dict<str, DbDatum> - keys are property names and value has data to be inserted 5. dict<str, seq<str>> - keys are property names and value has data to be inserted 6. dict<str, obj> - keys are property names and str(obj) is property value

Return

None

Throws

ConnectionFailed, CommunicationFailed DevFailed from device (DB_SQLError), TypeError

read(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().read_attribute(self.name(), …)

For convenience, here is the documentation of DeviceProxy.read_attribute(…):

read_attribute(self, attr_name, extract_as=ExtractAs.Numpy, green_mode=None, wait=True, timeout=None) -> DeviceAttribute

Read a single attribute.

Parameters

attr_name

(str) The name of the attribute to read.

extract_as

(ExtractAs) Defaults to numpy.

green_mode

(GreenMode) Defaults to the current DeviceProxy GreenMode. (see get_green_mode() and set_green_mode()).

wait

(bool) whether or not to wait for result. If green_mode is Synchronous, this parameter is ignored as it always waits for the result. Ignored when green_mode is Synchronous (always waits).

timeout

(float) The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when green_mode is Synchronous or wait is False.

Return

(DeviceAttribute)

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device TimeoutError (green_mode == Futures) If the future didn’t finish executing before the given timeout. Timeout (green_mode == Gevent) If the async result didn’t finish executing before the given timeout.

Changed in version 7.1.4: For DevEncoded attributes, before it was returning a DeviceAttribute.value as a tuple (format<str>, data<str>) no matter what was the extract_as value was. Since 7.1.4, it returns a (format<str>, data<buffer>) unless extract_as is String, in which case it returns (format<str>, data<str>).

Changed in version 8.0.0: For DevEncoded attributes, now returns a DeviceAttribute.value as a tuple (format<str>, data<bytes>) unless extract_as is String, in which case it returns (format<str>, data<str>). Carefull, if using python >= 3 data<str> is decoded using default python utf-8 encoding. This means that PyTango assumes tango DS was written encapsulating string into utf-8 which is the default python encoding.

New in version 8.1.0: green_mode parameter. wait parameter. timeout parameter.

read_asynch(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().read_attribute_asynch(self.name(), …)

For convenience, here is the documentation of DeviceProxy.read_attribute_asynch(…):

read_attribute_asynch( self, attr_name) -> int read_attribute_asynch( self, attr_name, callback) -> None

Shortcut to self.read_attributes_asynch([attr_name], cb)

New in PyTango 7.0.0

read_reply(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().read_attribute_reply(…)

For convenience, here is the documentation of DeviceProxy.read_attribute_reply(…):

read_attribute_reply( self, id, extract_as) -> int read_attribute_reply( self, id, timeout, extract_as) -> None

Shortcut to self.read_attributes_reply()[0]

New in PyTango 7.0.0

set_config(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().set_attribute_config(…)

For convenience, here is the documentation of DeviceProxy.set_attribute_config(…):

set_attribute_config( self, attr_info) -> None

Change the attribute configuration for the specified attribute

Parameters

attr_info

(AttributeInfo) attribute information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

set_attribute_config( self, attr_info_ex) -> None

Change the extended attribute configuration for the specified attribute

Parameters

attr_info_ex

(AttributeInfoEx) extended attribute information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

set_attribute_config( self, attr_info) -> None

Change the attributes configuration for the specified attributes

Parameters

attr_info

(sequence<AttributeInfo>) attributes information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

set_attribute_config( self, attr_info_ex) -> None

Change the extended attributes configuration for the specified attributes

Parameters

attr_info_ex

(sequence<AttributeInfoListEx>) extended attributes information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device, TypeError

set_transparency_reconnection(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().set_transparency_reconnection(…)

For convenience, here is the documentation of DeviceProxy.set_transparency_reconnection(…):

set_transparency_reconnection(self, yesno) -> None

Set the device transparency reconnection flag

Parameters

” - val : (bool) True to set transparency reconnection ” or False otherwise

Return

None

state(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().state(…)

For convenience, here is the documentation of DeviceProxy.state(…): state (self) -> DevState

A method which returns the state of the device.
Parameters

None

Return

(DevState) constant

Example
dev_st = dev.state()
if dev_st == DevState.ON : ...

status(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().status(…)

For convenience, here is the documentation of DeviceProxy.status(…): status (self) -> str

A method which returns the status of the device as a string.

Parameters

None

Return

(str) describing the device status

stop_poll(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().stop_poll_attribute(self.name(), …)

For convenience, here is the documentation of DeviceProxy.stop_poll_attribute(…):

stop_poll_attribute(self, attr_name) -> None

Remove an attribute from the list of polled attributes.

Parameters

attr_name

(str) attribute name

Return

None

subscribe_event(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().subscribe_event(self.name(), …)

For convenience, here is the documentation of DeviceProxy.subscribe_event(…):

subscribe_event(event_type, cb, stateless=False, green_mode=None) -> int

The client call to subscribe for event reception in the push model. The client implements a callback method which is triggered when the event is received. This method is currently used device interface change events only.

Parameters

event_type

(EventType) Is the event reason and must be on the enumerated values: * EventType.INTERFACE_CHANGE_EVENT

callback

(callable) Is any callable object or an object with a callable “push_event” method.

stateless

(bool) When the this flag is set to false, an exception will be thrown when the event subscription encounters a problem. With the stateless flag set to true, the event subscription will always succeed, even if the corresponding device server is not running. The keep alive thread will try every 10 seconds to subscribe for the specified event. At every subscription retry, a callback is executed which contains the corresponding exception

green_mode

the corresponding green mode (default is GreenMode.Synchronous)

Return

An event id which has to be specified when unsubscribing from this event.

Throws

EventSystemFailed, TypeError

subscribe_event(self, attr_name, event, callback, filters=[], stateless=False, extract_as=Numpy, green_mode=None) -> int

The client call to subscribe for event reception in the push model. The client implements a callback method which is triggered when the event is received. Filtering is done based on the reason specified and the event type. For example when reading the state and the reason specified is “change” the event will be fired only when the state changes. Events consist of an attribute name and the event reason. A standard set of reasons are implemented by the system, additional device specific reasons can be implemented by device servers programmers.

Parameters

attr_name

(str) The device attribute name which will be sent as an event e.g. “current”.

event_type

(EventType) Is the event reason and must be on the enumerated values: * EventType.CHANGE_EVENT * EventType.PERIODIC_EVENT * EventType.ARCHIVE_EVENT * EventType.ATTR_CONF_EVENT * EventType.DATA_READY_EVENT * EventType.USER_EVENT

callback

(callable) Is any callable object or an object with a callable “push_event” method.

filters

(sequence<str>) A variable list of name,value pairs which define additional filters for events.

stateless

(bool) When the this flag is set to false, an exception will be thrown when the event subscription encounters a problem. With the stateless flag set to true, the event subscription will always succeed, even if the corresponding device server is not running. The keep alive thread will try every 10 seconds to subscribe for the specified event. At every subscription retry, a callback is executed which contains the corresponding exception

extract_as

(ExtractAs)

green_mode

the corresponding green mode (default is GreenMode.Synchronous)

Return

An event id which has to be specified when unsubscribing from this event.

Throws

EventSystemFailed, TypeError

subscribe_event(self, attr_name, event, queuesize, filters=[], stateless=False, green_mode=None) -> int

The client call to subscribe for event reception in the pull model. Instead of a callback method the client has to specify the size of the event reception buffer.

The event reception buffer is implemented as a round robin buffer. This way the client can set-up different ways to receive events:

Event reception buffer size = 1 : The client is interested only in the value of the last event received. All other events that have been received since the last reading are discarded.

Event reception buffer size > 1 : The client has chosen to keep an event history of a given size. When more events arrive since the last reading, older events will be discarded.

Event reception buffer size = ALL_EVENTS : The client buffers all received events. The buffer size is unlimited and only restricted by the available memory for the client.

All other parameters are similar to the descriptions given in the other subscribe_event() version.

unsubscribe_event(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().unsubscribe_event(…)

For convenience, here is the documentation of DeviceProxy.unsubscribe_event(…):

unsubscribe_event(self, event_id) -> None

Unsubscribes a client from receiving the event specified by event_id.

Parameters

event_id

(int) is the event identifier returned by the DeviceProxy::subscribe_event(). Unlike in TangoC++ we chech that the event_id has been subscribed in this DeviceProxy.

Return

None

Throws

EventSystemFailed, KeyError

write(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().write_attribute(self.name(), …)

For convenience, here is the documentation of DeviceProxy.write_attribute(…):

write_attribute(self, attr_name, value, green_mode=None, wait=True, timeout=None) -> None write_attribute(self, attr_info, value, green_mode=None, wait=True, timeout=None) -> None

Write a single attribute.

Parameters

attr_name

(str) The name of the attribute to write.

attr_info

(AttributeInfo)

value

The value. For non SCALAR attributes it may be any sequence of sequences.

green_mode

(GreenMode) Defaults to the current DeviceProxy GreenMode. (see get_green_mode() and set_green_mode()).

wait

(bool) whether or not to wait for result. If green_mode is Synchronous, this parameter is ignored as it always waits for the result. Ignored when green_mode is Synchronous (always waits).

timeout

(float) The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when green_mode is Synchronous or wait is False.

Throws

ConnectionFailed, CommunicationFailed, DeviceUnlocked, DevFailed from device TimeoutError (green_mode == Futures) If the future didn’t finish executing before the given timeout. Timeout (green_mode == Gevent) If the async result didn’t finish executing before the given timeout.

New in version 8.1.0: green_mode parameter. wait parameter. timeout parameter.

write_asynch(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().write_attribute_asynch(…)

For convenience, here is the documentation of DeviceProxy.write_attribute_asynch(…):

write_attributes_asynch( self, values) -> int write_attributes_asynch( self, values, callback) -> None

Shortcut to self.write_attributes_asynch([attr_name, value], cb)

New in PyTango 7.0.0

write_read(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().write_read_attribute(self.name(), …)

For convenience, here is the documentation of DeviceProxy.write_read_attribute(…):

write_read_attribute(self, attr_name, value, extract_as=ExtractAs.Numpy, green_mode=None, wait=True, timeout=None) -> DeviceAttribute

Write then read a single attribute in a single network call. By default (serialisation by device), the execution of this call in the server can’t be interrupted by other clients.

Parameters

see write_attribute(attr_name, value)

Return

A tango.DeviceAttribute object.

Throws

ConnectionFailed, CommunicationFailed, DeviceUnlocked, DevFailed from device, WrongData TimeoutError (green_mode == Futures) If the future didn’t finish executing before the given timeout. Timeout (green_mode == Gevent) If the async result didn’t finish executing before the given timeout.

New in PyTango 7.0.0

New in version 8.1.0: green_mode parameter. wait parameter. timeout parameter.

write_reply(*args, **kwds)¶

This method is a simple way to do:: self.get_device_proxy().write_attribute_reply(…)

For convenience, here is the documentation of DeviceProxy.write_attribute_reply(…):

write_attribute_reply(self, id) -> None

Check if the answer of an asynchronous write_attribute is arrived (polling model). If the reply is arrived and if it is a valid reply, the call returned. If the reply is an exception, it is re-thrown by this call. An exception is also thrown in case of the reply is not yet arrived.

Parameters

id

(int) the asynchronous call identifier.

Return

None

Throws

AsynCall, AsynReplyNotArrived, CommunicationFailed, DevFailed from device.

New in PyTango 7.0.0

write_attribute_reply(self, id, timeout) -> None

Check if the answer of an asynchronous write_attribute is arrived (polling model). id is the asynchronous call identifier. If the reply is arrived and if it is a valid reply, the call returned. If the reply is an exception, it is re-thrown by this call. If the reply is not yet arrived, the call will wait (blocking the process) for the time specified in timeout. If after timeout milliseconds, the reply is still not there, an exception is thrown. If timeout is set to 0, the call waits until the reply arrived.

Parameters

id

(int) the asynchronous call identifier.

timeout

(int) the timeout

Return

None

Throws

AsynCall, AsynReplyNotArrived, CommunicationFailed, DevFailed from device.

New in PyTango 7.0.0

Group¶

Group class¶

class tango.Group(name)¶

Bases: object

A Tango Group represents a hierarchy of tango devices. The hierarchy may have more than one level. The main goal is to group devices with same attribute(s)/command(s) to be able to do parallel requests.

add(self, subgroup, timeout_ms=- 1) → None¶

Attaches a (sub)_RealGroup.

To remove the subgroup use the remove() method.

Parameters

subgroup: (str)
timeout_ms: (int) If timeout_ms parameter is different from -1, the client side timeout associated to each device composing the _RealGroup added is set to timeout_ms milliseconds. If timeout_ms is -1, timeouts are not changed.

Return

None

Throws

TypeError, ArgumentError

command_inout(self, cmd_name, forward=True) → sequence<GroupCmdReply>¶

command_inout(self, cmd_name, param, forward=True) → sequence<GroupCmdReply>

command_inout(self, cmd_name, param_list, forward=True) → sequence<GroupCmdReply>

Just a shortcut to do:
self.command_inout_reply(self.command_inout_asynch(…))

Parameters

cmd_name: (str) Command name
param: (any) parameter value
param_list: (tango.DeviceDataList) sequence of parameters. When given, it’s length must match the group size.
forward: (bool) If it is set to true (the default) request is forwarded to subgroups. Otherwise, it is only applied to the local set of devices.

Return

(sequence<GroupCmdReply>)

command_inout_asynch(self, cmd_name, forget=False, forward=True, reserved=- 1) → int¶

command_inout_asynch(self, cmd_name, param, forget=False, forward=True, reserved=- 1) → int

command_inout_asynch(self, cmd_name, param_list, forget=False, forward=True, reserved=- 1) → int

Executes a Tango command on each device in the group asynchronously. The method sends the request to all devices and returns immediately. Pass the returned request id to Group.command_inout_reply() to obtain the results.

Parameters

cmd_name: (str) Command name
param: (any) parameter value
param_list: (tango.DeviceDataList) sequence of parameters. When given, it’s length must match the group size.
forget: (bool) Fire and forget flag. If set to true, it means that no reply is expected (i.e. the caller does not care about it and will not even try to get it)
forward: (bool) If it is set to true (the default) request is forwarded to subgroups. Otherwise, it is only applied to the local set of devices.
reserved: (int) is reserved for internal purpose and should not be used. This parameter may disappear in a near future.

Return

(int) request id. Pass the returned request id to Group.command_inout_reply() to obtain the results.

Throws

command_inout_reply(self, req_id, timeout_ms=0) → sequence<GroupCmdReply>¶

Returns the results of an asynchronous command.

Parameters

req_id: (int) Is a request identifier previously returned by one of the command_inout_asynch methods
timeout_ms: (int) For each device in the hierarchy, if the command result is not yet available, command_inout_reply wait timeout_ms milliseconds before throwing an exception. This exception will be part of the global reply. If timeout_ms is set to 0, command_inout_reply waits “indefinitely”.

Return

(sequence<GroupCmdReply>)

Throws

contains(self, pattern, forward=True) → bool¶

Parameters

pattern: (str) The pattern can be a fully qualified or simple group name, a device name or a device name pattern.
forward: (bool) If fwd is set to true (the default), the remove request is also forwarded to subgroups. Otherwise, it is only applied to the local set of elements.

Return

(bool) Returns true if the hierarchy contains groups and/or devices which name matches the specified pattern. Returns false otherwise.

Throws

disable(*args, **kwds)¶: Disables a group or a device element in a group.

enable(*args, **kwds)¶: Enables a group or a device element in a group.

get_device_list(self, forward=True) → sequence<str>¶

Considering the following hierarchy:

g2.add("my/device/04")
g2.add("my/device/05")

g4.add("my/device/08")
g4.add("my/device/09")

g3.add("my/device/06")
g3.add(g4)
g3.add("my/device/07")

g1.add("my/device/01")
g1.add(g2)
g1.add("my/device/03")
g1.add(g3)
g1.add("my/device/02")

The returned vector content depends on the value of the forward option. If set to true, the results will be organized as follows:

    dl = g1.get_device_list(True)

dl[0] contains "my/device/01" which belongs to g1
dl[1] contains "my/device/04" which belongs to g1.g2
dl[2] contains "my/device/05" which belongs to g1.g2
dl[3] contains "my/device/03" which belongs to g1
dl[4] contains "my/device/06" which belongs to g1.g3
dl[5] contains "my/device/08" which belongs to g1.g3.g4
dl[6] contains "my/device/09" which belongs to g1.g3.g4
dl[7] contains "my/device/07" which belongs to g1.g3
dl[8] contains "my/device/02" which belongs to g1

If the forward option is set to false, the results are:

    dl = g1.get_device_list(False);

dl[0] contains "my/device/01" which belongs to g1
dl[1] contains "my/device/03" which belongs to g1
dl[2] contains "my/device/02" which belongs to g1

Parameters

forward: (bool) If it is set to true (the default), the request is forwarded to sub-groups. Otherwise, it is only applied to the local set of devices.

Return

(sequence<str>) The list of devices currently in the hierarchy.

Throws

get_fully_qualified_name(*args, **kwds)¶: Get the complete (dpt-separated) name of the group. This takes into consideration the name of the group and its parents.

get_name(*args, **kwds)¶: Get the name of the group. Eg: Group(‘name’).get_name() == ‘name’

get_size(self, forward=True) → int¶

Parameters

forward: (bool) If it is set to true (the default), the request is forwarded to sub-groups.

Return

(int) The number of the devices in the hierarchy

Throws

is_enabled(*args, **kwds)¶: Check if a group is enabled. New in PyTango 7.0.0

name_equals(*args, **kwds)¶: New in PyTango 7.0.0

name_matches(*args, **kwds)¶: New in PyTango 7.0.0

ping(self, forward=True) → bool¶

Ping all devices in a group.

Parameters

forward: (bool) If fwd is set to true (the default), the request is also forwarded to subgroups. Otherwise, it is only applied to the local set of devices.

Return

(bool) This method returns true if all devices in the group are alive, false otherwise.

Throws

read_attribute(self, attr_name, forward=True) → sequence<GroupAttrReply>¶

Just a shortcut to do:: self.read_attribute_reply(self.read_attribute_asynch(…))

read_attribute_asynch(self, attr_name, forward=True, reserved=- 1) → int¶

Reads an attribute on each device in the group asynchronously. The method sends the request to all devices and returns immediately.

Parameters

attr_name: (str) Name of the attribute to read.
forward: (bool) If it is set to true (the default) request is forwarded to subgroups. Otherwise, it is only applied to the local set of devices.
reserved: (int) is reserved for internal purpose and should not be used. This parameter may disappear in a near future.

Return

(int) request id. Pass the returned request id to Group.read_attribute_reply() to obtain the results.

Throws

read_attribute_reply(self, req_id, timeout_ms=0) → sequence<GroupAttrReply>¶

Returns the results of an asynchronous attribute reading.

Parameters

req_id: (int) a request identifier previously returned by read_attribute_asynch.
timeout_ms: (int) For each device in the hierarchy, if the attribute value is not yet available, read_attribute_reply wait timeout_ms milliseconds before throwing an exception. This exception will be part of the global reply. If timeout_ms is set to 0, read_attribute_reply waits “indefinitely”.

Return

(sequence<GroupAttrReply>)

Throws

read_attributes(self, attr_names, forward=True) → sequence<GroupAttrReply>¶

Just a shortcut to do:: self.read_attributes_reply(self.read_attributes_asynch(…))

read_attributes_asynch(self, attr_names, forward=True, reserved=- 1) → int¶

Reads the attributes on each device in the group asynchronously. The method sends the request to all devices and returns immediately.

Parameters

attr_names: (sequence<str>) Name of the attributes to read.
forward: (bool) If it is set to true (the default) request is forwarded to subgroups. Otherwise, it is only applied to the local set of devices.
reserved: (int) is reserved for internal purpose and should not be used. This parameter may disappear in a near future.

Return

(int) request id. Pass the returned request id to Group.read_attributes_reply() to obtain the results.

Throws

read_attributes_reply(self, req_id, timeout_ms=0) → sequence<GroupAttrReply>¶

Returns the results of an asynchronous attribute reading.

Parameters

req_id: (int) a request identifier previously returned by read_attribute_asynch.
timeout_ms: (int) For each device in the hierarchy, if the attribute value is not yet available, read_attribute_reply ait timeout_ms milliseconds before throwing an exception. This exception will be part of the global reply. If timeout_ms is set to 0, read_attributes_reply waits “indefinitely”.

Return

(sequence<GroupAttrReply>)

Throws

remove_all(self) → None¶: Removes all elements in the _RealGroup. After such a call, the _RealGroup is empty.

set_timeout_millis(self, timeout_ms) → bool¶

Set client side timeout for all devices composing the group in milliseconds. Any method which takes longer than this time to execute will throw an exception.

Parameters

timeout_ms: (int)

Return

None

Throws

(errors are ignored)

New in PyTango 7.0.0

write_attribute(self, attr_name, value, forward=True, multi=False) → sequence<GroupReply>¶

Just a shortcut to do:: self.write_attribute_reply(self.write_attribute_asynch(…))

write_attribute_asynch(self, attr_name, value, forward=True, multi=False) → int¶

Writes an attribute on each device in the group asynchronously. The method sends the request to all devices and returns immediately.

Parameters

attr_name: (str) Name of the attribute to write.
value: (any) Value to write. See DeviceProxy.write_attribute
forward: (bool) If it is set to true (the default) request is forwarded to subgroups. Otherwise, it is only applied to the local set of devices.
multi: (bool) If it is set to false (the default), the same value is applied to all devices in the group. Otherwise the value is interpreted as a sequence of values, and each value is applied to the corresponding device in the group. In this case len(value) must be equal to group.get_size()!

Return

(int) request id. Pass the returned request id to Group.write_attribute_reply() to obtain the acknowledgements.

Throws

write_attribute_reply(self, req_id, timeout_ms=0) → sequence<GroupReply>¶

Returns the acknowledgements of an asynchronous attribute writing.

Parameters

req_id: (int) a request identifier previously returned by write_attribute_asynch.
timeout_ms: (int) For each device in the hierarchy, if the acknowledgment is not yet available, write_attribute_reply wait timeout_ms milliseconds before throwing an exception. This exception will be part of the global reply. If timeout_ms is set to 0, write_attribute_reply waits “indefinitely”.

Return

(sequence<GroupReply>)

Throws

GroupReply classes¶

Group member functions do not return the same as their DeviceProxy counterparts, but objects that contain them. This is:

write attribute family returns tango.GroupReplyList

read attribute family returns tango.GroupAttrReplyList

command inout family returns tango.GroupCmdReplyList

The Group*ReplyList objects are just list-like objects containing GroupReply, GroupAttrReply and GroupCmdReply elements that will be described now.

Note also that GroupReply is the base of GroupCmdReply and GroupAttrReply.

class tango.GroupReply(*args, **kwargs)¶

This is the base class for the result of an operation on a PyTangoGroup, being it a write attribute, read attribute, or command inout operation.

It has some trivial common operations:

has_failed(self) -> bool

group_element_enabled(self) ->bool

dev_name(self) -> str

obj_name(self) -> str

get_err_stack(self) -> DevErrorList

class tango.GroupAttrReply(*args, **kwargs)¶

Bases:

get_data(self, extract_as=ExtractAs.Numpy) → DeviceAttribute¶

Get the DeviceAttribute.

Parameters

extract_as: (ExtractAs)

Return

(DeviceAttribute) Whatever is stored there, or None.

class tango.GroupCmdReply(*args, **kwargs)¶

Bases:

get_data(self) → any¶

Get the actual value stored in the GroupCmdRply, the command output value. It’s the same as self.get_data_raw().extract()

Parameters: None
Return: (any) Whatever is stored there, or None.

get_data_raw(self) → any¶

Get the DeviceData containing the output parameter of the command.

Parameters: None
Return: (DeviceData) Whatever is stored there, or None.

Green API¶

Summary:

tango.get_green_mode()
tango.set_green_mode()
tango.futures.DeviceProxy()
tango.gevent.DeviceProxy()

tango.get_green_mode()¶

Returns the current global default PyTango green mode.

Returns: the current global default PyTango green mode
Return type: GreenMode

tango.set_green_mode(green_mode=None)¶

Sets the global default PyTango green mode.

Advice: Use only in your final application. Don’t use this in a python library in order not to interfere with the beavior of other libraries and/or application where your library is being.

Parameters: green_mode (GreenMode) – the new global default PyTango green mode

tango.futures.DeviceProxy(self, dev_name, wait=True, timeout=True) → DeviceProxy¶

tango.futures.DeviceProxy(self, dev_name, need_check_acc, wait=True, timeout=True) → DeviceProxy

Creates a futures enabled DeviceProxy.

The DeviceProxy constructor internally makes some network calls which makes it slow. By using the futures green mode you are allowing other python code to be executed in a cooperative way.

Note

The timeout parameter has no relation with the tango device client side timeout (gettable by get_timeout_millis() and settable through set_timeout_millis())

Parameters

dev_name (str) – the device name or alias
need_check_acc (bool) – in first version of the function it defaults to True. Determines if at creation time of DeviceProxy it should check for channel access (rarely used)
wait (bool) – whether or not to wait for result of creating a DeviceProxy.
timeout (float) – The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when wait is False.

Returns

if wait is True:: DeviceProxy
else:: concurrent.futures.Future

Throws

a DevFailed if wait is True and there is an error creating the device.
a concurrent.futures.TimeoutError if wait is False, timeout is not None and the time to create the device has expired.

New in PyTango 8.1.0

tango.gevent.DeviceProxy(self, dev_name, wait=True, timeout=True) → DeviceProxy¶

tango.gevent.DeviceProxy(self, dev_name, need_check_acc, wait=True, timeout=True) → DeviceProxy

Creates a gevent enabled DeviceProxy.

The DeviceProxy constructor internally makes some network calls which makes it slow. By using the gevent green mode you are allowing other python code to be executed in a cooperative way.

Note

The timeout parameter has no relation with the tango device client side timeout (gettable by get_timeout_millis() and settable through set_timeout_millis())

Parameters

dev_name (str) – the device name or alias
need_check_acc (bool) – in first version of the function it defaults to True. Determines if at creation time of DeviceProxy it should check for channel access (rarely used)
wait (bool) – whether or not to wait for result of creating a DeviceProxy.
timeout (float) – The number of seconds to wait for the result. If None, then there is no limit on the wait time. Ignored when wait is False.

Returns

if wait is True:: DeviceProxy
else:: gevent.event.AsynchResult

Throws

a DevFailed if wait is True and there is an error creating the device.
a gevent.timeout.Timeout if wait is False, timeout is not None and the time to create the device has expired.

New in PyTango 8.1.0

API util¶

class tango.ApiUtil(*args, **kwargs)¶

This class allows you to access the tango syncronization model API. It is designed as a singleton. To get a reference to the singleton object you must do:

import tango
apiutil = tango.ApiUtil.instance()

New in PyTango 7.1.3

get_asynch_cb_sub_model(self) → cb_sub_model¶

Get the asynchronous callback sub-model.

Parameters: None
Return: (cb_sub_model) the active asynchronous callback sub-model.

New in PyTango 7.1.3

get_asynch_replies(self) → None¶

Fire callback methods for all (any device) asynchronous requests (command and attribute) with already arrived replied. Returns immediately if there is no replies already arrived or if there is no asynchronous requests.

Parameters

None

Return

None

Throws

None, all errors are reported using the err and errors fields of the parameter passed to the callback method.

New in PyTango 7.1.3

get_asynch_replies (self) -> None

Fire callback methods for all (any device) asynchronous requests (command and attributes) with already arrived replied. Wait and block the caller for timeout milliseconds if they are some device asynchronous requests which are not yet arrived. Returns immediately if there is no asynchronous request. If timeout is set to 0, the call waits until all the asynchronous requests sent has received a reply.

Parameters

timeout

(int) timeout (milliseconds)

Return

None

Throws

AsynReplyNotArrived. All other errors are reported using the err and errors fields of the object passed to the callback methods.

New in PyTango 7.1.3

pending_asynch_call(self, req) → int¶

Return number of asynchronous pending requests (any device). The input parameter is an enumeration with three values which are:

POLLING: Return only polling model asynchronous request number

CALL_BACK: Return only callback model asynchronous request number

ALL_ASYNCH: Return all asynchronous request number

Parameters

req: (asyn_req_type) asynchronous request type

Return

(int) the number of pending requests for the given type

New in PyTango 7.1.3

set_asynch_cb_sub_model(self, model) → None¶

Set the asynchronous callback sub-model between the pull and push sub-model. The cb_sub_model data type is an enumeration with two values which are:

PUSH_CALLBACK: The push sub-model

PULL_CALLBACK: The pull sub-model

Parameters

model: (cb_sub_model) the callback sub-model

Return

None

New in PyTango 7.1.3

Information classes¶

Attribute¶

class tango.AttributeAlarmInfo(*args, **kwargs)¶

A structure containing available alarm information for an attribute with the folowing members:

min_alarm : (str) low alarm level

max_alarm : (str) high alarm level

min_warning : (str) low warning level

max_warning : (str) high warning level

delta_t : (str) time delta

delta_val : (str) value delta

extensions : (StdStringVector) extensions (currently not used)

class tango.AttributeDimension(*args, **kwargs)¶

A structure containing x and y attribute data dimensions with the following members:

dim_x : (int) x dimension

dim_y : (int) y dimension

class tango.AttributeInfo(*args, **kwargs)¶

A structure (inheriting from DeviceAttributeConfig) containing available information for an attribute with the following members:

disp_level : (DispLevel) display level (OPERATOR, EXPERT)

Inherited members are:

name : (str) attribute name

writable : (AttrWriteType) write type (R, W, RW, R with W)

data_format : (AttrDataFormat) data format (SCALAR, SPECTRUM, IMAGE)

data_type : (int) attribute type (float, string,..)

max_dim_x : (int) first dimension of attribute (spectrum or image attributes)

max_dim_y : (int) second dimension of attribute(image attribute)

description : (int) attribute description

label : (str) attribute label (Voltage, time, …)

unit : (str) attribute unit (V, ms, …)

standard_unit : (str) standard unit

display_unit : (str) display unit

format : (str) how to display the attribute value (ex: for floats could be ‘%6.2f’)

min_value : (str) minimum allowed value

max_value : (str) maximum allowed value

min_alarm : (str) low alarm level

max_alarm : (str) high alarm level

writable_attr_name : (str) name of the writable attribute

extensions : (StdStringVector) extensions (currently not used)

class tango.AttributeInfoEx(*args, **kwargs)¶

A structure (inheriting from AttributeInfo) containing available information for an attribute with the following members:

alarms : object containing alarm information (see AttributeAlarmInfo).

events : object containing event information (see AttributeEventInfo).

sys_extensions : StdStringVector

Inherited members are:

name : (str) attribute name

writable : (AttrWriteType) write type (R, W, RW, R with W)

data_format : (AttrDataFormat) data format (SCALAR, SPECTRUM, IMAGE)

data_type : (int) attribute type (float, string,..)

max_dim_x : (int) first dimension of attribute (spectrum or image attributes)

max_dim_y : (int) second dimension of attribute(image attribute)

description : (int) attribute description

label : (str) attribute label (Voltage, time, …)

unit : (str) attribute unit (V, ms, …)

standard_unit : (str) standard unit

display_unit : (str) display unit

format : (str) how to display the attribute value (ex: for floats could be ‘%6.2f’)

min_value : (str) minimum allowed value

max_value : (str) maximum allowed value

min_alarm : (str) low alarm level

max_alarm : (str) high alarm level

writable_attr_name : (str) name of the writable attribute

extensions : (StdStringVector) extensions (currently not used)

disp_level : (DispLevel) display level (OPERATOR, EXPERT)

Command¶

class tango.DevCommandInfo(*args, **kwargs)¶

A device command info with the following members:

cmd_name : (str) command name

cmd_tag : command as binary value (for TACO)

in_type : (CmdArgType) input type

out_type : (CmdArgType) output type

in_type_desc : (str) description of input type

out_type_desc : (str) description of output type

New in PyTango 7.0.0

class tango.CommandInfo(*args, **kwargs)¶

A device command info (inheriting from DevCommandInfo) with the following members:

disp_level : (DispLevel) command display level

Inherited members are (from DevCommandInfo):

cmd_name : (str) command name

cmd_tag : (str) command as binary value (for TACO)

in_type : (CmdArgType) input type

out_type : (CmdArgType) output type

in_type_desc : (str) description of input type

out_type_desc : (str) description of output type

Other¶

class tango.DeviceInfo(*args, **kwargs)¶

A structure containing available information for a device with the” following members:

dev_class : (str) device class

server_id : (str) server ID

server_host : (str) host name

server_version : (str) server version

doc_url : (str) document url

class tango.LockerInfo(*args, **kwargs)¶

A structure with information about the locker with the folowing members:

ll : (tango.LockerLanguage) the locker language

li : (pid_t / UUID) the locker id

locker_host : (str) the host

locker_class : (str) the class

pid_t should be an int, UUID should be a tuple of four numbers.

New in PyTango 7.0.0

class tango.PollDevice(*args, **kwargs)¶

A structure containing PollDevice information with the folowing members:

dev_name : (str) device name

ind_list : (sequence<int>) index list

New in PyTango 7.0.0

Storage classes¶

Attribute: DeviceAttribute¶

class tango.DeviceAttribute(*args, **kwargs)¶

This is the fundamental type for RECEIVING data from device attributes.

It contains several fields. The most important ones depend on the ExtractAs method used to get the value. Normally they are:

value : Normal scalar value or numpy array of values.

w_value : The write part of the attribute.

See other ExtractAs for different possibilities. There are some more fields, these really fixed:

name : (str)

data_format : (AttrDataFormat) Attribute format

quality : (AttrQuality)

time : (TimeVal)

dim_x : (int) attribute dimension x

dim_y : (int) attribute dimension y

w_dim_x : (int) attribute written dimension x

w_dim_y : (int) attribute written dimension y

r_rimension : (tuple) Attribute read dimensions.

w_dimension : (tuple) Attribute written dimensions.

nb_read : (int) attribute read total length

nb_written : (int) attribute written total length

And two methods:

get_date
get_err_stack

class ExtractAs¶

Defines what will go into value field of DeviceAttribute, or what will Attribute.get_write_value() return… Not all the possible values are valid in all the cases.

Valid possible values are:

Numpy : Value will be stored in [value, w_value]. If the attribute is an scalar, they will contain a value. If it’s an SPECTRUM or IMAGE it will be exported as a numpy array.

Tuple : Value will be stored in [value, w_value]. If the attribute is an scalar, they will contain a value. If it’s an SPECTRUM or IMAGE it will be exported as a tuple or tuple of tuples.

List : Value will be stored in [value, w_value]. If the attribute is an scalar, they will contain a value. If it’s an SPECTRUM or IMAGE it will be exported as a list or list of lists

String : The data will be stored ‘as is’, the binary data as it comes from TangoC++ in ‘value’.

Nothing : The value will not be extracted from DeviceAttribute

get_date(self) → TimeVal¶

Get the time at which the attribute was read by the server.

Note: It’s the same as reading the “time” attribute.

Parameters: None
Return: (TimeVal) The attribute read timestamp.

get_err_stack(self) → sequence<DevError>¶

Returns the error stack reported by the server when the attribute was read.

Parameters: None
Return: (sequence<DevError>)

set_w_dim_x(self, val) → None¶

Sets the write value dim x.

Parameters

val: (int) new write dim x

Return

None

New in PyTango 8.0.0

set_w_dim_y(self, val) → None¶

Sets the write value dim y.

Parameters

val: (int) new write dim y

Return

None

New in PyTango 8.0.0

Command: DeviceData¶

Device data is the type used internally by Tango to deal with command parameters and return values. You don’t usually need to deal with it, as command_inout will automatically convert the parameters from any other type and the result value to another type.

You can still use them, using command_inout_raw to get the result in a DeviceData.

You also may deal with it when reading command history.

class tango.DeviceData(*args, **kwargs)¶

This is the fundamental type for sending and receiving data from device commands. The values can be inserted and extracted using the insert() and extract() methods.

extract(self) → any¶

Get the actual value stored in the DeviceData.

Parameters: None
Return: Whatever is stored there, or None.

get_type(self) → CmdArgType¶

This method returns the Tango data type of the data inside the DeviceData object.

Parameters: None
Return: The content arg type.

insert(self, data_type, value) → None¶

Inserts a value in the DeviceData.

Parameters

data_type
value: (any) The value to insert

Return

Whatever is stored there, or None.

is_empty(self) → bool¶

It can be used to test whether the DeviceData object has been initialized or not.

Parameters: None
Return: True or False depending on whether the DeviceData object contains data or not.

Event related classes¶

Event configuration information¶

class tango.AttributeEventInfo(*args, **kwargs)¶

A structure containing available event information for an attribute with the folowing members:

ch_event : (ChangeEventInfo) change event information

per_event : (PeriodicEventInfo) periodic event information

arch_event : (ArchiveEventInfo) archiving event information

class tango.ArchiveEventInfo(*args, **kwargs)¶

A structure containing available archiving event information for an attribute with the folowing members:

archive_rel_change : (str) relative change that will generate an event

archive_abs_change : (str) absolute change that will generate an event

archive_period : (str) archive period

extensions : (sequence<str>) extensions (currently not used)

class tango.ChangeEventInfo(*args, **kwargs)¶

A structure containing available change event information for an attribute with the folowing members:

rel_change : (str) relative change that will generate an event

abs_change : (str) absolute change that will generate an event

extensions : (StdStringVector) extensions (currently not used)

class tango.PeriodicEventInfo(*args, **kwargs)¶

A structure containing available periodic event information for an attribute with the folowing members:

period : (str) event period

extensions : (StdStringVector) extensions (currently not used)

Event arrived structures¶

class tango.EventData(*args, **kwargs)¶

This class is used to pass data to the callback method when an event is sent to the client. It contains the following public fields:

device : (DeviceProxy) The DeviceProxy object on which the call was executed.

attr_name : (str) The attribute name

event : (str) The event name

attr_value : (DeviceAttribute) The attribute data (DeviceAttribute)

err : (bool) A boolean flag set to true if the request failed. False otherwise

errors : (sequence<DevError>) The error stack

reception_date: (TimeVal)

class tango.AttrConfEventData(*args, **kwargs)¶

This class is used to pass data to the callback method when a configuration event is sent to the client. It contains the following public fields:

device : (DeviceProxy) The DeviceProxy object on which the call was executed

attr_name : (str) The attribute name

event : (str) The event name

attr_conf : (AttributeInfoEx) The attribute data

err : (bool) A boolean flag set to true if the request failed. False otherwise

errors : (sequence<DevError>) The error stack

reception_date: (TimeVal)

class tango.DataReadyEventData(*args, **kwargs)¶

This class is used to pass data to the callback method when an attribute data ready event is sent to the clien. It contains the following public fields:

device : (DeviceProxy) The DeviceProxy object on which the call was executed

attr_name : (str) The attribute name

event : (str) The event name

attr_data_type : (int) The attribute data type

ctr : (int) The user counter. Set to 0 if not defined when sent by the server

err : (bool) A boolean flag set to true if the request failed. False otherwise

errors : (sequence<DevError>) The error stack

reception_date: (TimeVal)

New in PyTango 7.0.0

History classes¶

class tango.DeviceAttributeHistory(*args, **kwargs)¶: Bases:

See DeviceAttribute.

class tango.DeviceDataHistory(*args, **kwargs)¶: Bases:

See DeviceData.

Enumerations & other classes¶

Enumerations¶

class tango.LockerLanguage(*args, **kwargs)¶

An enumeration representing the programming language in which the client application who locked is written.

CPP : C++/Python language

JAVA : Java language

New in PyTango 7.0.0

class tango.CmdArgType(*args, **kwargs)¶

An enumeration representing the command argument type.

DevVoid

DevBoolean

DevShort

DevLong

DevFloat

DevDouble

DevUShort

DevULong

DevString

DevVarCharArray

DevVarShortArray

DevVarLongArray

DevVarFloatArray

DevVarDoubleArray

DevVarUShortArray

DevVarULongArray

DevVarStringArray

DevVarLongStringArray

DevVarDoubleStringArray

DevState

ConstDevString

DevVarBooleanArray

DevUChar

DevLong64

DevULong64

DevVarLong64Array

DevVarULong64Array

DevInt

DevEncoded

DevEnum

DevPipeBlob

class tango.MessBoxType(*args, **kwargs)¶

An enumeration representing the MessBoxType

STOP

INFO

New in PyTango 7.0.0

class tango.PollObjType(*args, **kwargs)¶

An enumeration representing the PollObjType

POLL_CMD

POLL_ATTR

EVENT_HEARTBEAT

STORE_SUBDEV

New in PyTango 7.0.0

class tango.PollCmdCode(*args, **kwargs)¶

An enumeration representing the PollCmdCode

POLL_ADD_OBJ

POLL_REM_OBJ

POLL_START

POLL_STOP

POLL_UPD_PERIOD

POLL_REM_DEV

POLL_EXIT

POLL_REM_EXT_TRIG_OBJ

POLL_ADD_HEARTBEAT

POLL_REM_HEARTBEAT

New in PyTango 7.0.0

class tango.SerialModel(*args, **kwargs)¶

An enumeration representing the type of serialization performed by the device server

BY_DEVICE

BY_CLASS

BY_PROCESS

NO_SYNC

class tango.AttReqType(*args, **kwargs)¶

An enumeration representing the type of attribute request

READ_REQ

WRITE_REQ

class tango.LockCmdCode(*args, **kwargs)¶

An enumeration representing the LockCmdCode

LOCK_ADD_DEV

LOCK_REM_DEV

LOCK_UNLOCK_ALL_EXIT

LOCK_EXIT

New in PyTango 7.0.0

class tango.LogLevel(*args, **kwargs)¶

An enumeration representing the LogLevel

LOG_OFF

LOG_FATAL

LOG_ERROR

LOG_WARN

LOG_INFO

LOG_DEBUG

New in PyTango 7.0.0

class tango.LogTarget(*args, **kwargs)¶

An enumeration representing the LogTarget

LOG_CONSOLE

LOG_FILE

LOG_DEVICE

New in PyTango 7.0.0

class tango.EventType(*args, **kwargs)¶

An enumeration representing event type

CHANGE_EVENT

QUALITY_EVENT

PERIODIC_EVENT

ARCHIVE_EVENT

USER_EVENT

ATTR_CONF_EVENT

DATA_READY_EVENT

INTERFACE_CHANGE_EVENT

PIPE_EVENT

DATA_READY_EVENT - New in PyTango 7.0.0 INTERFACE_CHANGE_EVENT - New in PyTango 9.2.2 PIPE_EVENT - New in PyTango 9.2.2

class tango.KeepAliveCmdCode(*args, **kwargs)¶

An enumeration representing the KeepAliveCmdCode

EXIT_TH

New in PyTango 7.0.0

class tango.AccessControlType(*args, **kwargs)¶

An enumeration representing the AccessControlType

ACCESS_READ

ACCESS_WRITE

New in PyTango 7.0.0

class tango.asyn_req_type(*args, **kwargs)¶

An enumeration representing the asynchronous request type

POLLING

CALLBACK

ALL_ASYNCH

class tango.cb_sub_model(*args, **kwargs)¶

An enumeration representing callback sub model

PUSH_CALLBACK

PULL_CALLBACK

class tango.AttrQuality(*args, **kwargs)¶

An enumeration representing the attribute quality

ATTR_VALID

ATTR_INVALID

ATTR_ALARM

ATTR_CHANGING

ATTR_WARNING

class tango.AttrWriteType(*args, **kwargs)¶

An enumeration representing the attribute type

READ

READ_WITH_WRITE

WRITE

READ_WRITE

class tango.AttrDataFormat(*args, **kwargs)¶

An enumeration representing the attribute format

SCALAR

SPECTRUM

IMAGE

FMT_UNKNOWN

class tango.PipeWriteType(*args, **kwargs)¶

An enumeration representing the pipe type

PIPE_READ

PIPE_READ_WRITE

class tango.DevSource(*args, **kwargs)¶

An enumeration representing the device source for data

DEV

CACHE

CACHE_DEV

class tango.ErrSeverity(*args, **kwargs)¶

An enumeration representing the error severity

WARN

ERR

PANIC

class tango.DevState(*args, **kwargs)¶

An enumeration representing the device state

ON

OFF

CLOSE

OPEN

INSERT

EXTRACT

MOVING

STANDBY

FAULT

INIT

RUNNING

ALARM

DISABLE

UNKNOWN

class tango.DispLevel(*args, **kwargs)¶

An enumeration representing the display level

OPERATOR

EXPERT

class tango.GreenMode(*args, **kwargs)¶

An enumeration representing the GreenMode

Synchronous

Futures

Gevent

New in PyTango 8.1.0

Other classes¶

class tango.Release¶

Summarize release information as class attributes.

Release information:

name: (str) package name
version_info: (tuple) The five components of the version number: major, minor, micro, releaselevel, and serial.
version: (str) package version in format <major>.<minor>.<micro>
release: (str) pre-release, post-release or development release; it is empty for final releases.
version_long: (str) package version in format <major>.<minor>.<micro><releaselevel><serial>
version_description: (str) short description for the current version
version_number: (int) <major>*100 + <minor>*10 + <micro>
description : (str) package description
long_description: (str) longer package description
authors: (dict<str(last name), tuple<str(full name),str(email)>>) package authors
url: (str) package url
download_url: (str) package download url
platform: (seq) list of available platforms
keywords: (seq) list of keywords
license: (str) the license

class tango.TimeVal(*args, **kwargs)¶

Time value structure with the following members:

tv_sec : seconds

tv_usec : microseconds

tv_nsec : nanoseconds

isoformat(self, sep='T') → str¶

Returns a string in ISO 8601 format, YYYY-MM-DDTHH:MM:SS[.mmmmmm][+HH:MM]

Parameters

sep : (str) sep is used to separate the year from the time, and defaults to ‘T’

Return

(str) a string representing the time according to a format specification.

New in version 7.1.0.

New in version 7.1.2: Documented

Changed in version 7.1.2: The sep parameter is not mandatory anymore and defaults to ‘T’ (same as datetime.datetime.isoformat())

strftime(self, format) → str¶

Convert a time value to a string according to a format specification.

Parameters

format : (str) See the python library reference manual for formatting codes

Return

(str) a string representing the time according to a format specification.

New in version 7.1.0.

New in version 7.1.2: Documented

todatetime(self) → datetime.datetime¶

Returns a datetime.datetime object representing the same time value

Parameters

None

Return

(datetime.datetime) the time value in datetime format

New in version 7.1.0.

totime(self) → float¶

Returns a float representing this time value

Parameters

None

Return

a float representing the time value

New in version 7.1.0.

Server API¶

High level server API¶

Server helper classes for writing Tango device servers.

Device
attribute
command
pipe

device_property
class_property
run()
server_run()

This module provides a high level device server API. It implements TEP1. It exposes an easier API for developing a Tango device server.

Here is a simple example on how to write a Clock device server using the high level API:

import time
from tango.server import run
from tango.server import Device
from tango.server import attribute, command


class Clock(Device):

    time = attribute()

    def read_time(self):
        return time.time()

    @command(din_type=str, dout_type=str)
    def strftime(self, format):
        return time.strftime(format)


if __name__ == "__main__":
    run((Clock,))

Here is a more complete example on how to write a PowerSupply device server using the high level API. The example contains:

a read-only double scalar attribute called voltage
a read/write double scalar expert attribute current
a read-only double image attribute called noise
a ramp command
a host device property
a port class property

from time import time
from numpy.random import random_sample

from tango import AttrQuality, AttrWriteType, DispLevel
from tango.server import Device, attribute, command
from tango.server import class_property, device_property

class PowerSupply(Device):

    voltage = attribute()

    current = attribute(label="Current", dtype=float,
                        display_level=DispLevel.EXPERT,
                        access=AttrWriteType.READ_WRITE,
                        unit="A", format="8.4f",
                        min_value=0.0, max_value=8.5,
                        min_alarm=0.1, max_alarm=8.4,
                        min_warning=0.5, max_warning=8.0,
                        fget="get_current", fset="set_current",
                        doc="the power supply current")

    noise = attribute(label="Noise", dtype=((float,),),
                      max_dim_x=1024, max_dim_y=1024,
                      fget="get_noise")

    host = device_property(dtype=str)
    port = class_property(dtype=int, default_value=9788)

    def read_voltage(self):
        self.info_stream("get voltage(%s, %d)" % (self.host, self.port))
        return 10.0

    def get_current(self):
        return 2.3456, time(), AttrQuality.ATTR_WARNING

    def set_current(self, current):
        print("Current set to %f" % current)

    def get_noise(self):
        return random_sample((1024, 1024))

    @command(dtype_in=float)
    def ramp(self, value):
        print("Ramping up...")

if __name__ == "__main__":
    PowerSupply.run_server()

Pretty cool, uh?

Data types

When declaring attributes, properties or commands, one of the most important information is the data type. It is given by the keyword argument dtype. In order to provide a more pythonic interface, this argument is not restricted to the CmdArgType options.

For example, to define a SCALAR DevLong attribute you have several possibilities:

int
‘int’
‘int64’
tango.CmdArgType.DevLong64
‘DevLong64’
numpy.int64

To define a SPECTRUM attribute simply wrap the scalar data type in any python sequence:

using a tuple: (:obj:`int`,) or
using a list: [:obj:`int`] or
any other sequence type

To define an IMAGE attribute simply wrap the scalar data type in any python sequence of sequences:

using a tuple: ((:obj:`int`,),) or
using a list: [[:obj:`int`]] or
any other sequence type

Below is the complete table of equivalences.

dtype argument	converts to tango type
`None`	`DevVoid`
`'None'`	`DevVoid`
`DevVoid`	`DevVoid`
`'DevVoid'`	`DevVoid`
`DevState`	`DevState`
`'DevState'`	`DevState`
`bool`	`DevBoolean`
`'bool'`	`DevBoolean`
`'boolean'`	`DevBoolean`
`DevBoolean`	`DevBoolean`
`'DevBoolean'`	`DevBoolean`
`numpy.bool_`	`DevBoolean`
`'char'`	`DevUChar`
`'chr'`	`DevUChar`
`'byte'`	`DevUChar`
`chr`	`DevUChar`
`DevUChar`	`DevUChar`
`'DevUChar'`	`DevUChar`
`numpy.uint8`	`DevUChar`
`'int16'`	`DevShort`
`DevShort`	`DevShort`
`'DevShort'`	`DevShort`
`numpy.int16`	`DevShort`
`'uint16'`	`DevUShort`
`DevUShort`	`DevUShort`
`'DevUShort'`	`DevUShort`
`numpy.uint16`	`DevUShort`
`'int32'`	`DevLong`
`DevLong`	`DevLong`
`'DevLong'`	`DevLong`
`numpy.int32`	`DevLong`
`'uint32'`	`DevULong`
`DevULong`	`DevULong`
`'DevULong'`	`DevULong`
`numpy.uint32`	`DevULong`
`int`	`DevLong64`
`'int'`	`DevLong64`
`'int64'`	`DevLong64`
`DevLong64`	`DevLong64`
`'DevLong64'`	`DevLong64`
`numpy.int64`	`DevLong64`
`'uint'`	`DevULong64`
`'uint64'`	`DevULong64`
`DevULong64`	`DevULong64`
`'DevULong64'`	`DevULong64`
`numpy.uint64`	`DevULong64`
`DevInt`	`DevInt`
`'DevInt'`	`DevInt`
`'float32'`	`DevFloat`
`DevFloat`	`DevFloat`
`'DevFloat'`	`DevFloat`
`numpy.float32`	`DevFloat`
`float`	`DevDouble`
`'double'`	`DevDouble`
`'float'`	`DevDouble`
`'float64'`	`DevDouble`
`DevDouble`	`DevDouble`
`'DevDouble'`	`DevDouble`
`numpy.float64`	`DevDouble`
`str`	`DevString`
`'str'`	`DevString`
`'string'`	`DevString`
`'text'`	`DevString`
`DevString`	`DevString`
`'DevString'`	`DevString`
`bytearray`	`DevEncoded`
`'bytearray'`	`DevEncoded`
`'bytes'`	`DevEncoded`
`DevEncoded`	`DevEncoded`
`'DevEncoded'`	`DevEncoded`
`DevVarBooleanArray`	`DevVarBooleanArray`
`'DevVarBooleanArray'`	`DevVarBooleanArray`
`DevVarCharArray`	`DevVarCharArray`
`'DevVarCharArray'`	`DevVarCharArray`
`DevVarShortArray`	`DevVarShortArray`
`'DevVarShortArray'`	`DevVarShortArray`
`DevVarLongArray`	`DevVarLongArray`
`'DevVarLongArray'`	`DevVarLongArray`
`DevVarLong64Array`	`DevVarLong64Array`
`'DevVarLong64Array'`	`DevVarLong64Array`
`DevVarULong64Array`	`DevVarULong64Array`
`'DevVarULong64Array'`	`DevVarULong64Array`
`DevVarFloatArray`	`DevVarFloatArray`
`'DevVarFloatArray'`	`DevVarFloatArray`
`DevVarDoubleArray`	`DevVarDoubleArray`
`'DevVarDoubleArray'`	`DevVarDoubleArray`
`DevVarUShortArray`	`DevVarUShortArray`
`'DevVarUShortArray'`	`DevVarUShortArray`
`DevVarULongArray`	`DevVarULongArray`
`'DevVarULongArray'`	`DevVarULongArray`
`DevVarStringArray`	`DevVarStringArray`
`'DevVarStringArray'`	`DevVarStringArray`
`DevVarLongStringArray`	`DevVarLongStringArray`
`'DevVarLongStringArray'`	`DevVarLongStringArray`
`DevVarDoubleStringArray`	`DevVarDoubleStringArray`
`'DevVarDoubleStringArray'`	`DevVarDoubleStringArray`
`DevPipeBlob`	`DevPipeBlob`
`'DevPipeBlob'`	`DevPipeBlob`

class tango.server.Device(cl, name)¶

Bases: tango.server.BaseDevice

Device class for the high-level API.

All device specific classes should inherit from this class.

add_attribute(self, attr, r_meth=None, w_meth=None, is_allo_meth=None) → Attr¶

Add a new attribute to the device attribute list. Please, note that if you add an attribute to a device at device creation time, this attribute will be added to the device class attribute list. Therefore, all devices belonging to the same class created after this attribute addition will also have this attribute.

Parameters

attr: (Attr or AttrData) the new attribute to be added to the list.
r_meth: (callable) the read method to be called on a read request
w_meth: (callable) the write method to be called on a write request (if attr is writable)
is_allo_meth: (callable) the method that is called to check if it is possible to access the attribute or not

Return

(Attr) the newly created attribute.

Throws

DevFailed

add_command(self, cmd, level=TANGO::OPERATOR) → cmd¶

Add a new command to the device command list.

Parameters

cmd: the new command to be added to the list
device_level: Set this flag to true if the command must be added for only this device

Return

Command

Throws

DevFailed

always_executed_hook()¶: Tango always_executed_hook. Default implementation does nothing

append_status(self, status, new_line=False) → None¶

Appends a string to the device status.

Parameters: status : (str) the string to be appened to the device status new_line : (bool) If true, appends a new line character before the string. Default is False
Return: None

check_command_exists(self) → None¶

This method check that a command is supported by the device and does not need input value. The method throws an exception if the command is not defined or needs an input value

Parameters

cmd_name: (str) the command name

Return

None

Throws

DevFailed API_IncompatibleCmdArgumentType, API_CommandNotFound

New in PyTango 7.1.2

debug_stream(self, msg, *args) → None¶

Sends the given message to the tango debug stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_debug)

Parameters

msg: (str) the message to be sent to the debug stream

Return

None

delete_device(self) → None¶

Delete the device.

Parameters: None
Return: None

dev_state(self) → DevState¶

Get device state. Default method to get device state. The behaviour of this method depends on the device state. If the device state is ON or ALARM, it reads the attribute(s) with an alarm level defined, check if the read value is above/below the alarm and eventually change the state to ALARM, return the device state. For all th other device state, this method simply returns the state This method can be redefined in sub-classes in case of the default behaviour does not fullfill the needs.

Parameters: None
Return: (DevState) the device state
Throws: DevFailed - If it is necessary to read attribute(s) and a problem occurs during the reading

dev_status(self) → str¶

Get device status. Default method to get device status. It returns the contents of the device dev_status field. If the device state is ALARM, alarm messages are added to the device status. This method can be redefined in sub-classes in case of the default behaviour does not fullfill the needs.

Parameters: None
Return: (str) the device status
Throws: DevFailed - If it is necessary to read attribute(s) and a problem occurs during the reading

error_stream(self, msg, *args) → None¶

Sends the given message to the tango error stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_error)

Parameters

msg: (str) the message to be sent to the error stream

Return

None

fatal_stream(self, msg, *args) → None¶

Sends the given message to the tango fatal stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_fatal)

Parameters

msg: (str) the message to be sent to the fatal stream

Return

None

get_attr_min_poll_period(self) → seq<str>¶

Returns the min attribute poll period

Parameters: None
Return: (seq) the min attribute poll period

New in PyTango 7.2.0

get_attr_poll_ring_depth(self, attr_name) → int¶

Returns the attribute poll ring depth

Parameters

attr_name: (str) the attribute name

Return

(int) the attribute poll ring depth

New in PyTango 7.1.2

get_attribute_poll_period(self, attr_name) → int¶

Returns the attribute polling period (ms) or 0 if the attribute is not polled.

Parameters

attr_name: (str) attribute name

Return

(int) attribute polling period (ms) or 0 if it is not polled

New in PyTango 8.0.0

get_cmd_min_poll_period(self) → seq<str>¶

Returns the min command poll period

Parameters: None
Return: (seq) the min command poll period

New in PyTango 7.2.0

get_cmd_poll_ring_depth(self, cmd_name) → int¶

Returns the command poll ring depth

Parameters

cmd_name: (str) the command name

Return

(int) the command poll ring depth

New in PyTango 7.1.2

get_command_poll_period(self, cmd_name) → int¶

Returns the command polling period (ms) or 0 if the command is not polled.

Parameters

cmd_name: (str) command name

Return

(int) command polling period (ms) or 0 if it is not polled

New in PyTango 8.0.0

get_dev_idl_version(self) → int¶

Returns the IDL version

Parameters: None
Return: (int) the IDL version

New in PyTango 7.1.2

get_device_attr(self) → MultiAttribute¶

Get device multi attribute object.

Parameters: None
Return: (MultiAttribute) the device’s MultiAttribute object

get_device_properties(self, ds_class=None) → None¶

Utility method that fetches all the device properties from the database and converts them into members of this DeviceImpl.

Parameters

ds_class: (DeviceClass) the DeviceClass object. Optional. Default value is None meaning that the corresponding DeviceClass object for this DeviceImpl will be used

Return

None

Throws

DevFailed

get_exported_flag(self) → bool¶

Returns the state of the exported flag

Parameters: None
Return: (bool) the state of the exported flag

New in PyTango 7.1.2

get_logger(self) → Logger¶

Returns the Logger object for this device

Parameters: None
Return: (Logger) the Logger object for this device

get_min_poll_period(self) → int¶

Returns the min poll period

Parameters: None
Return: (int) the min poll period

New in PyTango 7.2.0

get_name(self)¶

Get a COPY of the device name.

Parameters: None
Return: (str) the device name

get_non_auto_polled_attr(self) → sequence<str>¶

Returns a COPY of the list of non automatic polled attributes

Parameters: None
Return: (sequence<str>) a COPY of the list of non automatic polled attributes

New in PyTango 7.1.2

get_non_auto_polled_cmd(self) → sequence<str>¶

Returns a COPY of the list of non automatic polled commands

Parameters: None
Return: (sequence<str>) a COPY of the list of non automatic polled commands

New in PyTango 7.1.2

get_poll_old_factor(self) → int¶

Returns the poll old factor

Parameters: None
Return: (int) the poll old factor

New in PyTango 7.1.2

get_poll_ring_depth(self) → int¶

Returns the poll ring depth

Parameters: None
Return: (int) the poll ring depth

New in PyTango 7.1.2

get_polled_attr(self) → sequence<str>¶

Returns a COPY of the list of polled attributes

Parameters: None
Return: (sequence<str>) a COPY of the list of polled attributes

New in PyTango 7.1.2

get_polled_cmd(self) → sequence<str>¶

Returns a COPY of the list of polled commands

Parameters: None
Return: (sequence<str>) a COPY of the list of polled commands

New in PyTango 7.1.2

get_prev_state(self) → DevState¶

Get a COPY of the device’s previous state.

Parameters: None
Return: (DevState) the device’s previous state

get_state(self) → DevState¶

Get a COPY of the device state.

Parameters: None
Return: (DevState) Current device state

get_status(self) → str¶

Get a COPY of the device status.

Parameters: None
Return: (str) the device status

info_stream(self, msg, *args) → None¶

Sends the given message to the tango info stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_info)

Parameters

msg: (str) the message to be sent to the info stream

Return

None

init_device()¶: Tango init_device method. Default implementation calls get_device_properties()

initialize_dynamic_attributes()¶: Method executed at initializion phase to create dynamic attributes. Default implementation does nothing. Overwrite when necessary.

is_device_locked(self) → bool¶

Returns if this device is locked by a client

Parameters: None
Return: (bool) True if it is locked or False otherwise

New in PyTango 7.1.2

is_polled(self) → bool¶

Returns if it is polled

Parameters: None
Return: (bool) True if it is polled or False otherwise

New in PyTango 7.1.2

is_there_subscriber(self, att_name, event_type) → bool¶

Check if there is subscriber(s) listening for the event.

This method returns a boolean set to true if there are some subscriber(s) listening on the event specified by the two method arguments. Be aware that there is some delay (up to 600 sec) between this method returning false and the last subscriber unsubscription or crash…

The device interface change event is not supported by this method.

Parameters

att_name: (str) the attribute name
event_type (EventType): the event type

Return

True if there is at least one listener or False otherwise

push_archive_event(self, attr_name) → None¶

push_archive_event(self, attr_name, except) → None

push_archive_event(self, attr_name, data, dim_x=1, dim_y=0) → None

push_archive_event(self, attr_name, str_data, data) → None

push_archive_event(self, attr_name, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_archive_event(self, attr_name, str_data, data, time_stamp, quality) → None

Push an archive event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
except: (DevFailed) Instead of data, you may want to send an exception.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_att_conf_event(self, attr) → None¶

Push an attribute configuration event.

Parameters: (Attribute) the attribute for which the configuration event will be sent.
Return: None

New in PyTango 7.2.1

push_change_event(self, attr_name) → None¶

push_change_event(self, attr_name, except) → None

push_change_event(self, attr_name, data, dim_x=1, dim_y=0) → None

push_change_event(self, attr_name, str_data, data) → None

push_change_event(self, attr_name, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_change_event(self, attr_name, str_data, data, time_stamp, quality) → None

Push a change event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
except: (DevFailed) Instead of data, you may want to send an exception.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_data_ready_event(self, attr_name, counter=0) → None¶

Push a data ready event for the given attribute name. The event is pushed to the notification daemon.

The method needs only the attribue name and an optional “counter” which will be passed unchanged within the event

Parameters

attr_name: (str) attribute name
counter: (int) the user counter

Return

None

Throws

DevFailed If the attribute name is unknown.

push_event(self, attr_name, filt_names, filt_vals) → None¶

push_event(self, attr_name, filt_names, filt_vals, data, dim_x=1, dim_y=0) → None

push_event(self, attr_name, filt_names, filt_vals, str_data, data) → None

push_event(self, attr_name, filt_names, filt_vals, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_event(self, attr_name, filt_names, filt_vals, str_data, data, time_stamp, quality) → None

Push a user event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
filt_names: (sequence<str>) the filterable fields name
filt_vals: (sequence<double>) the filterable fields value
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_pipe_event(self, blob) → None¶

Push an pipe event.

Parameters: the blob which pipe event will be send.
Return: None

New in PyTango 9.2.2

read_attr_hardware(self, attr_list) → None¶

Read the hardware to return attribute value(s). Default method to implement an action necessary on a device to read the hardware involved in a a read attribute CORBA call. This method must be redefined in sub-classes in order to support attribute reading

Parameters

attr_list(sequence<int>) list of indices in the device object attribute vector: of an attribute to be read.

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

register_signal(self, signo) → None¶

Register a signal. Register this device as device to be informed when signal signo is sent to to the device server process

Parameters

signo: (int) signal identifier

Return

None

remove_attribute(self, attr_name) → None¶

Remove one attribute from the device attribute list.

Parameters

attr_name: (str) attribute name

Return

None

Throws

DevFailed

remove_command(self, attr_name) → None¶

Remove one command from the device command list.

Parameters

cmd_name: (str) command name to be removed from the list
free_it: Boolean set to true if the command object must be freed.
clean_db: Clean command related information (included polling info if the command is polled) from database.

Return

None

Throws

DevFailed

classmethod run_server(args=None, **kwargs)¶

Run the class as a device server. It is based on the tango.server.run method.

The difference is that the device class and server name are automatically given.

Args:

args (iterable): args as given in the tango.server.run method: without the server name. If None, the sys.argv list is used
kwargs: the other keywords argument are as given: in the tango.server.run method.

set_archive_event(self, attr_name, implemented, detect=True) → None¶

Set an implemented flag for the attribute to indicate that the server fires archive events manually, without the polling to be started. If the detect parameter is set to true, the criteria specified for the archive event are verified and the event is only pushed if they are fullfilled. If detect is set to false the event is fired without any value checking!

Parameters

attr_name: (str) attribute name
implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the change event properties when set to true. Default value is true.

Return

None

set_change_event(self, attr_name, implemented, detect=True) → None¶

Set an implemented flag for the attribute to indicate that the server fires change events manually, without the polling to be started. If the detect parameter is set to true, the criteria specified for the change event are verified and the event is only pushed if they are fullfilled. If detect is set to false the event is fired without any value checking!

Parameters

attr_name: (str) attribute name
implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the change event properties when set to true. Default value is true.

Return

None

set_state(self, new_state) → None¶

Set device state.

Parameters

new_state: (DevState) the new device state

Return

None

set_status(self, new_status) → None¶

Set device status.

Parameters

new_status: (str) the new device status

Return

None

signal_handler(self, signo) → None¶

Signal handler. The method executed when the signal arrived in the device server process. This method is defined as virtual and then, can be redefined following device needs.

Parameters

signo: (int) the signal number

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

stop_polling(self) → None¶

stop_polling(self, with_db_upd) → None

Stop all polling for a device. if the device is polled, call this method before deleting it.

Parameters

with_db_upd: (bool) Is it necessary to update db ?

Return

None

New in PyTango 7.1.2

unregister_signal(self, signo) → None¶

Unregister a signal. Unregister this device as device to be informed when signal signo is sent to to the device server process

Parameters

signo: (int) signal identifier

Return

None

warn_stream(self, msg, *args) → None¶

Sends the given message to the tango warn stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_warn)

Parameters

msg: (str) the message to be sent to the warn stream

Return

None

write_attr_hardware(self) → None¶

Write the hardware for attributes. Default method to implement an action necessary on a device to write the hardware involved in a a write attribute. This method must be redefined in sub-classes in order to support writable attribute

Parameters

attr_list(sequence<int>) list of indices in the device object attribute vector: of an attribute to be written.

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

class tango.server.attribute(fget=None, **kwargs)¶

Declares a new tango attribute in a Device. To be used like the python native property function. For example, to declare a scalar, tango.DevDouble, read-only attribute called voltage in a PowerSupply Device do:

class PowerSupply(Device):

    voltage = attribute()

    def read_voltage(self):
        return 999.999

The same can be achieved with:

class PowerSupply(Device):

    @attribute
    def voltage(self):
        return 999.999

It receives multiple keyword arguments.

parameter	type	default value	description
name	`str`	class member name	alternative attribute name
dtype	`object`	`DevDouble`	data type (see Data type equivalence)
dformat	`AttrDataFormat`	`SCALAR`	data format
max_dim_x	`int`	1	maximum size for x dimension (ignored for SCALAR format)
max_dim_y	`int`	0	maximum size for y dimension (ignored for SCALAR and SPECTRUM formats)
display_level	`DispLevel`	`OPERATOR`	display level
polling_period	`int`	-1	polling period
memorized	`bool`	False	attribute should or not be memorized
hw_memorized	`bool`	False	write method should be called at startup when restoring memorize value (dangerous!)
access	`AttrWriteType`	`READ`	read only/ read write / write only access
fget (or fread)	`str` or `callable`	‘read_<attr_name>’	read method name or method object
fset (or fwrite)	`str` or `callable`	‘write_<attr_name>’	write method name or method object
fisallowed	`str` or `callable`	‘is_<attr_name>_allowed’	is allowed method name or method object
label	`str`	‘<attr_name>’	attribute label
enum_labels	sequence	None	the list of enumeration labels (enum data type)
doc (or description)	`str`	‘’	attribute description
unit	`str`	‘’	physical units the attribute value is in
standard_unit	`str`	‘’	physical standard unit
display_unit	`str`	‘’	physical display unit (hint for clients)
format	`str`	‘6.2f’	attribute representation format
min_value	`str`	None	minimum allowed value
max_value	`str`	None	maximum allowed value
min_alarm	`str`	None	minimum value to trigger attribute alarm
max_alarm	`str`	None	maximum value to trigger attribute alarm
min_warning	`str`	None	minimum value to trigger attribute warning
max_warning	`str`	None	maximum value to trigger attribute warning
delta_val	`str`	None
delta_t	`str`	None
abs_change	`str`	None	minimum value change between events that causes event filter to send the event
rel_change	`str`	None	minimum relative change between events that causes event filter to send the event (%)
period	`str`	None
archive_abs_change	`str`	None
archive_rel_change	`str`	None
archive_period	`str`	None
green_mode	`GreenMode`	None	green mode for read and write. None means use server green mode.
read_green_mode	`GreenMode`	None	green mode for read. None means use server green mode.
write_green_mode	`GreenMode`	None	green mode for write. None means use server green mode.
forwarded	`bool`	False	the attribute should be forwarded if True

Note

avoid using dformat parameter. If you need a SPECTRUM attribute of say, boolean type, use instead dtype=(bool,).

Example of a integer writable attribute with a customized label, unit and description:

class PowerSupply(Device):

    current = attribute(label="Current", unit="mA", dtype=int,
                        access=AttrWriteType.READ_WRITE,
                        doc="the power supply current")

    def init_device(self):
        Device.init_device(self)
        self._current = -1

    def read_current(self):
        return self._current

    def write_current(self, current):
        self._current = current

The same, but using attribute as a decorator:

class PowerSupply(Device):

    def init_device(self):
        Device.init_device(self)
        self._current = -1

    @attribute(label="Current", unit="mA", dtype=int)
    def current(self):
        """the power supply current"""
        return 999.999

    @current.write
    def current(self, current):
        self._current = current

In this second format, defining the write implicitly sets the attribute access to READ_WRITE.

New in version 8.1.7: added green_mode, read_green_mode and write_green_mode options

tango.server.command(f=None, dtype_in=None, dformat_in=None, doc_in='', dtype_out=None, dformat_out=None, doc_out='', display_level=None, polling_period=None, green_mode=None)¶

Declares a new tango command in a Device. To be used like a decorator in the methods you want to declare as tango commands. The following example declares commands:

void TurnOn(void)

void Ramp(DevDouble current)

DevBool Pressurize(DevDouble pressure)

class PowerSupply(Device):

    @command
    def TurnOn(self):
        self.info_stream('Turning on the power supply')

    @command(dtype_in=float)
    def Ramp(self, current):
        self.info_stream('Ramping on %f...' % current)

    @command(dtype_in=float, doc_in='the pressure to be set',
             dtype_out=bool, doc_out='True if it worked, False otherwise')
    def Pressurize(self, pressure):
        self.info_stream('Pressurizing to %f...' % pressure)
        return True

Note

avoid using dformat parameter. If you need a SPECTRUM attribute of say, boolean type, use instead dtype=(bool,).

Parameters

dtype_in – a data type describing the type of parameter. Default is None meaning no parameter.
dformat_in (AttrDataFormat) – parameter data format. Default is None.
doc_in (str) – parameter documentation
dtype_out – a data type describing the type of return value. Default is None meaning no return value.
dformat_out (AttrDataFormat) – return value data format. Default is None.
doc_out (str) – return value documentation
display_level (DispLevel) – display level for the command (optional)
polling_period (int) – polling period in milliseconds (optional)
green_mode – set green mode on this specific command. Default value is None meaning use the server green mode. Set it to GreenMode.Synchronous to force a non green command in a green server.

New in version 8.1.7: added green_mode option

New in version 9.2.0: added display_level and polling_period optional argument

class tango.server.pipe(fget=None, **kwargs)¶

Declares a new tango pipe in a Device. To be used like the python native property function.

Checkout the pipe data types to see what you should return on a pipe read request and what to expect as argument on a pipe write request.

For example, to declare a read-only pipe called ROI (for Region Of Interest), in a Detector Device do:

class Detector(Device):

    ROI = pipe()

    def read_ROI(self):
        return ('ROI', ({'name': 'x', 'value': 0},
                        {'name': 'y', 'value': 10},
                        {'name': 'width', 'value': 100},
                        {'name': 'height', 'value': 200}))

The same can be achieved with (also showing that a dict can be used to pass blob data):

class Detector(Device):

    @pipe
    def ROI(self):
        return 'ROI', dict(x=0, y=10, width=100, height=200)

It receives multiple keyword arguments.

parameter	type	default value	description
name	`str`	class member name	alternative pipe name
display_level	`DispLevel`	`OPERATOR`	display level
access	`PipeWriteType`	`READ`	read only/ read write access
fget (or fread)	`str` or `callable`	‘read_<pipe_name>’	read method name or method object
fset (or fwrite)	`str` or `callable`	‘write_<pipe_name>’	write method name or method object
fisallowed	`str` or `callable`	‘is_<pipe_name>_allowed’	is allowed method name or method object
label	`str`	‘<pipe_name>’	pipe label
doc (or description)	`str`	‘’	pipe description
green_mode	`GreenMode`	None	green mode for read and write. None means use server green mode.
read_green_mode	`GreenMode`	None	green mode for read. None means use server green mode.
write_green_mode	`GreenMode`	None	green mode for write. None means use server green mode.

The same example with a read-write ROI, a customized label and description:

class Detector(Device):

    ROI = pipe(label='Region Of Interest', doc='The active region of interest',
               access=PipeWriteType.PIPE_READ_WRITE)

    def init_device(self):
        Device.init_device(self)
        self.__roi = 'ROI', dict(x=0, y=10, width=100, height=200)

    def read_ROI(self):
        return self.__roi

    def write_ROI(self, roi):
        self.__roi = roi

The same, but using pipe as a decorator:

class Detector(Device):

    def init_device(self):
        Device.init_device(self)
        self.__roi = 'ROI', dict(x=0, y=10, width=100, height=200)

    @pipe(label="Region Of Interest")
    def ROI(self):
        """The active region of interest"""
        return self.__roi

    @ROI.write
    def ROI(self, roi):
        self.__roi = roi

In this second format, defining the write / setter implicitly sets the pipe access to READ_WRITE.

New in version 9.2.0.

class tango.server.device_property(dtype, doc='', mandatory=False, default_value=None, update_db=False)¶

Declares a new tango device property in a Device. To be used like the python native property function. For example, to declare a scalar, tango.DevString, device property called host in a PowerSupply Device do:

from tango.server import Device, DeviceMeta
from tango.server import device_property

class PowerSupply(Device):

    host = device_property(dtype=str)
    port = device_property(dtype=int, mandatory=True)

Parameters

dtype – Data type (see Data types)
doc – property documentation (optional)
(optional (mandatory) – default is False)
default_value – default value for the property (optional)
update_db (bool) – tells if set value should write the value to database. [default: False]

New in version 8.1.7: added update_db option

class tango.server.class_property(dtype, doc='', default_value=None, update_db=False)¶

Declares a new tango class property in a Device. To be used like the python native property function. For example, to declare a scalar, tango.DevString, class property called port in a PowerSupply Device do:

from tango.server import Device, DeviceMeta
from tango.server import class_property

class PowerSupply(Device):

    port = class_property(dtype=int, default_value=9788)

Parameters

dtype – Data type (see Data types)
doc – property documentation (optional)
default_value – default value for the property (optional)
update_db (bool) – tells if set value should write the value to database. [default: False]

New in version 8.1.7: added update_db option

tango.server.run(classes, args=None, msg_stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, verbose=False, util=None, event_loop=None, post_init_callback=None, green_mode=None, raises=False)¶

Provides a simple way to run a tango server. It handles exceptions by writting a message to the msg_stream.

The classes parameter can be either a sequence of:

: class:~tango.server.Device or
a sequence of two elements DeviceClass, DeviceImpl or
a sequence of three elements DeviceClass, DeviceImpl, tango class name (str)

or a dictionary where:

key is the tango class name
value is either:
- a : class:~tango.server.Device class or
- a sequence of two elements DeviceClass, DeviceImpl or
- a sequence of three elements DeviceClass, DeviceImpl, tango class name (str)

The optional post_init_callback can be a callable (without arguments) or a tuple where the first element is the callable, the second is a list of arguments (optional) and the third is a dictionary of keyword arguments (also optional).

Note

the order of registration of tango classes defines the order tango uses to initialize the corresponding devices. if using a dictionary as argument for classes be aware that the order of registration becomes arbitrary. If you need a predefined order use a sequence or an OrderedDict.

Example 1: registering and running a PowerSupply inheriting from Device:

from tango.server import Device, DeviceMeta, run

class PowerSupply(Device):
    pass

run((PowerSupply,))

Example 2: registering and running a MyServer defined by tango classes MyServerClass and MyServer:

from tango import Device_4Impl, DeviceClass
from tango.server import run

class MyServer(Device_4Impl):
    pass

class MyServerClass(DeviceClass):
    pass

run({'MyServer': (MyServerClass, MyServer)})

Example 3: registering and running a MyServer defined by tango classes MyServerClass and MyServer:

from tango import Device_4Impl, DeviceClass
from tango.server import Device, DeviceMeta, run

class PowerSupply(Device):
    pass

class MyServer(Device_4Impl):
    pass

class MyServerClass(DeviceClass):
    pass

run([PowerSupply, [MyServerClass, MyServer]])
# or: run({'MyServer': (MyServerClass, MyServer)})

Parameters

classes (sequence or dict) – a sequence of Device classes or a dictionary where keyword is the tango class name and value is a sequence of Tango Device Class python class, and Tango Device python class
args (list) – list of command line arguments [default: None, meaning use sys.argv]
msg_stream – stream where to put messages [default: sys.stdout]
util (Util) – PyTango Util object [default: None meaning create a Util instance]
event_loop (callable) – event_loop callable
post_init_callback (callable or tuple (see description above)) – an optional callback that is executed between the calls Util.server_init and Util.server_run
raises (bool) – Disable error handling and propagate exceptions from the server

Returns

The Util singleton object

Return type

Util

New in version 8.1.2.

Changed in version 8.1.4: when classes argument is a sequence, the items can also be a sequence <TangoClass, TangoClassClass>[, tango class name]

Changed in version 9.2.2: raises argument has been added

tango.server.server_run(classes, args=None, msg_stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, verbose=False, util=None, event_loop=None, post_init_callback=None, green_mode=None)¶: Since PyTango 8.1.2 it is just an alias to run(). Use run() instead.

New in version 8.0.0.

Changed in version 8.0.3: Added util keyword parameter. Returns util object

Changed in version 8.1.1: Changed default msg_stream from stderr to stdout Added event_loop keyword parameter. Returns util object

Changed in version 8.1.2: Added post_init_callback keyword parameter

Deprecated since version 8.1.2: Use run() instead.

Device¶

DeviceImpl¶

class tango.LatestDeviceImpl¶

Latest implementation of the TANGO device base class (alias for Device_5Impl).

It inherits from CORBA classes where all the network layer is implemented.

add_attribute(self, attr, r_meth=None, w_meth=None, is_allo_meth=None) → Attr¶

Add a new attribute to the device attribute list. Please, note that if you add an attribute to a device at device creation time, this attribute will be added to the device class attribute list. Therefore, all devices belonging to the same class created after this attribute addition will also have this attribute.

Parameters

attr: (Attr or AttrData) the new attribute to be added to the list.
r_meth: (callable) the read method to be called on a read request
w_meth: (callable) the write method to be called on a write request (if attr is writable)
is_allo_meth: (callable) the method that is called to check if it is possible to access the attribute or not

Return

(Attr) the newly created attribute.

Throws

DevFailed

add_command(self, cmd, level=TANGO::OPERATOR) → cmd¶

Add a new command to the device command list.

Parameters

cmd: the new command to be added to the list
device_level: Set this flag to true if the command must be added for only this device

Return

Command

Throws

DevFailed

always_executed_hook(self) → None¶

Hook method. Default method to implement an action necessary on a device before any command is executed. This method can be redefined in sub-classes in case of the default behaviour does not fullfill the needs

Parameters: None
Return: None
Throws: DevFailed This method does not throw exception but a redefined method can.

append_status(self, status, new_line=False) → None¶

Appends a string to the device status.

Parameters: status : (str) the string to be appened to the device status new_line : (bool) If true, appends a new line character before the string. Default is False
Return: None

check_command_exists(self) → None¶

This method check that a command is supported by the device and does not need input value. The method throws an exception if the command is not defined or needs an input value

Parameters

cmd_name: (str) the command name

Return

None

Throws

DevFailed API_IncompatibleCmdArgumentType, API_CommandNotFound

New in PyTango 7.1.2

debug_stream(self, msg, *args) → None¶

Sends the given message to the tango debug stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_debug)

Parameters

msg: (str) the message to be sent to the debug stream

Return

None

delete_device(self) → None¶

Delete the device.

Parameters: None
Return: None

dev_state(self) → DevState¶

Get device state. Default method to get device state. The behaviour of this method depends on the device state. If the device state is ON or ALARM, it reads the attribute(s) with an alarm level defined, check if the read value is above/below the alarm and eventually change the state to ALARM, return the device state. For all th other device state, this method simply returns the state This method can be redefined in sub-classes in case of the default behaviour does not fullfill the needs.

Parameters: None
Return: (DevState) the device state
Throws: DevFailed - If it is necessary to read attribute(s) and a problem occurs during the reading

dev_status(self) → str¶

Get device status. Default method to get device status. It returns the contents of the device dev_status field. If the device state is ALARM, alarm messages are added to the device status. This method can be redefined in sub-classes in case of the default behaviour does not fullfill the needs.

Parameters: None
Return: (str) the device status
Throws: DevFailed - If it is necessary to read attribute(s) and a problem occurs during the reading

error_stream(self, msg, *args) → None¶

Sends the given message to the tango error stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_error)

Parameters

msg: (str) the message to be sent to the error stream

Return

None

fatal_stream(self, msg, *args) → None¶

Sends the given message to the tango fatal stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_fatal)

Parameters

msg: (str) the message to be sent to the fatal stream

Return

None

get_attr_min_poll_period(self) → seq<str>¶

Returns the min attribute poll period

Parameters: None
Return: (seq) the min attribute poll period

New in PyTango 7.2.0

get_attr_poll_ring_depth(self, attr_name) → int¶

Returns the attribute poll ring depth

Parameters

attr_name: (str) the attribute name

Return

(int) the attribute poll ring depth

New in PyTango 7.1.2

get_attribute_poll_period(self, attr_name) → int¶

Returns the attribute polling period (ms) or 0 if the attribute is not polled.

Parameters

attr_name: (str) attribute name

Return

(int) attribute polling period (ms) or 0 if it is not polled

New in PyTango 8.0.0

get_cmd_min_poll_period(self) → seq<str>¶

Returns the min command poll period

Parameters: None
Return: (seq) the min command poll period

New in PyTango 7.2.0

get_cmd_poll_ring_depth(self, cmd_name) → int¶

Returns the command poll ring depth

Parameters

cmd_name: (str) the command name

Return

(int) the command poll ring depth

New in PyTango 7.1.2

get_command_poll_period(self, cmd_name) → int¶

Returns the command polling period (ms) or 0 if the command is not polled.

Parameters

cmd_name: (str) command name

Return

(int) command polling period (ms) or 0 if it is not polled

New in PyTango 8.0.0

get_dev_idl_version(self) → int¶

Returns the IDL version

Parameters: None
Return: (int) the IDL version

New in PyTango 7.1.2

get_device_attr(self) → MultiAttribute¶

Get device multi attribute object.

Parameters: None
Return: (MultiAttribute) the device’s MultiAttribute object

get_device_properties(self, ds_class=None) → None¶

Utility method that fetches all the device properties from the database and converts them into members of this DeviceImpl.

Parameters

ds_class: (DeviceClass) the DeviceClass object. Optional. Default value is None meaning that the corresponding DeviceClass object for this DeviceImpl will be used

Return

None

Throws

DevFailed

get_exported_flag(self) → bool¶

Returns the state of the exported flag

Parameters: None
Return: (bool) the state of the exported flag

New in PyTango 7.1.2

get_logger(self) → Logger¶

Returns the Logger object for this device

Parameters: None
Return: (Logger) the Logger object for this device

get_min_poll_period(self) → int¶

Returns the min poll period

Parameters: None
Return: (int) the min poll period

New in PyTango 7.2.0

get_name(self)¶

Get a COPY of the device name.

Parameters: None
Return: (str) the device name

get_non_auto_polled_attr(self) → sequence<str>¶

Returns a COPY of the list of non automatic polled attributes

Parameters: None
Return: (sequence<str>) a COPY of the list of non automatic polled attributes

New in PyTango 7.1.2

get_non_auto_polled_cmd(self) → sequence<str>¶

Returns a COPY of the list of non automatic polled commands

Parameters: None
Return: (sequence<str>) a COPY of the list of non automatic polled commands

New in PyTango 7.1.2

get_poll_old_factor(self) → int¶

Returns the poll old factor

Parameters: None
Return: (int) the poll old factor

New in PyTango 7.1.2

get_poll_ring_depth(self) → int¶

Returns the poll ring depth

Parameters: None
Return: (int) the poll ring depth

New in PyTango 7.1.2

get_polled_attr(self) → sequence<str>¶

Returns a COPY of the list of polled attributes

Parameters: None
Return: (sequence<str>) a COPY of the list of polled attributes

New in PyTango 7.1.2

get_polled_cmd(self) → sequence<str>¶

Returns a COPY of the list of polled commands

Parameters: None
Return: (sequence<str>) a COPY of the list of polled commands

New in PyTango 7.1.2

get_prev_state(self) → DevState¶

Get a COPY of the device’s previous state.

Parameters: None
Return: (DevState) the device’s previous state

get_state(self) → DevState¶

Get a COPY of the device state.

Parameters: None
Return: (DevState) Current device state

get_status(self) → str¶

Get a COPY of the device status.

Parameters: None
Return: (str) the device status

info_stream(self, msg, *args) → None¶

Sends the given message to the tango info stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_info)

Parameters

msg: (str) the message to be sent to the info stream

Return

None

init_device(self) → None¶

Intialize the device.

Parameters: None
Return: None

is_device_locked(self) → bool¶

Returns if this device is locked by a client

Parameters: None
Return: (bool) True if it is locked or False otherwise

New in PyTango 7.1.2

is_polled(self) → bool¶

Returns if it is polled

Parameters: None
Return: (bool) True if it is polled or False otherwise

New in PyTango 7.1.2

is_there_subscriber(self, att_name, event_type) → bool¶

Check if there is subscriber(s) listening for the event.

This method returns a boolean set to true if there are some subscriber(s) listening on the event specified by the two method arguments. Be aware that there is some delay (up to 600 sec) between this method returning false and the last subscriber unsubscription or crash…

The device interface change event is not supported by this method.

Parameters

att_name: (str) the attribute name
event_type (EventType): the event type

Return

True if there is at least one listener or False otherwise

push_archive_event(self, attr_name) → None¶

push_archive_event(self, attr_name, except) → None

push_archive_event(self, attr_name, data, dim_x=1, dim_y=0) → None

push_archive_event(self, attr_name, str_data, data) → None

push_archive_event(self, attr_name, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_archive_event(self, attr_name, str_data, data, time_stamp, quality) → None

Push an archive event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
except: (DevFailed) Instead of data, you may want to send an exception.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_att_conf_event(self, attr) → None¶

Push an attribute configuration event.

Parameters: (Attribute) the attribute for which the configuration event will be sent.
Return: None

New in PyTango 7.2.1

push_change_event(self, attr_name) → None¶

push_change_event(self, attr_name, except) → None

push_change_event(self, attr_name, data, dim_x=1, dim_y=0) → None

push_change_event(self, attr_name, str_data, data) → None

push_change_event(self, attr_name, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_change_event(self, attr_name, str_data, data, time_stamp, quality) → None

Push a change event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
except: (DevFailed) Instead of data, you may want to send an exception.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_data_ready_event(self, attr_name, counter=0) → None¶

Push a data ready event for the given attribute name. The event is pushed to the notification daemon.

The method needs only the attribue name and an optional “counter” which will be passed unchanged within the event

Parameters

attr_name: (str) attribute name
counter: (int) the user counter

Return

None

Throws

DevFailed If the attribute name is unknown.

push_event(self, attr_name, filt_names, filt_vals) → None¶

push_event(self, attr_name, filt_names, filt_vals, data, dim_x=1, dim_y=0) → None

push_event(self, attr_name, filt_names, filt_vals, str_data, data) → None

push_event(self, attr_name, filt_names, filt_vals, data, time_stamp, quality, dim_x=1, dim_y=0) → None

push_event(self, attr_name, filt_names, filt_vals, str_data, data, time_stamp, quality) → None

Push a user event for the given attribute name. The event is pushed to the notification daemon.

Parameters

attr_name: (str) attribute name
filt_names: (sequence<str>) the filterable fields name
filt_vals: (sequence<double>) the filterable fields value
data: the data to be sent as attribute event data. Data must be compatible with the attribute type and format. for SPECTRUM and IMAGE attributes, data can be any type of sequence of elements compatible with the attribute type
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
dim_x: (int) the attribute x length. Default value is 1
dim_y: (int) the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Throws

DevFailed If the attribute data type is not coherent.

push_pipe_event(self, blob) → None¶

Push an pipe event.

Parameters: the blob which pipe event will be send.
Return: None

New in PyTango 9.2.2

read_attr_hardware(self, attr_list) → None¶

Read the hardware to return attribute value(s). Default method to implement an action necessary on a device to read the hardware involved in a a read attribute CORBA call. This method must be redefined in sub-classes in order to support attribute reading

Parameters

attr_list(sequence<int>) list of indices in the device object attribute vector: of an attribute to be read.

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

register_signal(self, signo) → None¶

Register a signal. Register this device as device to be informed when signal signo is sent to to the device server process

Parameters

signo: (int) signal identifier

Return

None

remove_attribute(self, attr_name) → None¶

Remove one attribute from the device attribute list.

Parameters

attr_name: (str) attribute name

Return

None

Throws

DevFailed

remove_command(self, attr_name) → None¶

Remove one command from the device command list.

Parameters

cmd_name: (str) command name to be removed from the list
free_it: Boolean set to true if the command object must be freed.
clean_db: Clean command related information (included polling info if the command is polled) from database.

Return

None

Throws

DevFailed

set_archive_event(self, attr_name, implemented, detect=True) → None¶

Set an implemented flag for the attribute to indicate that the server fires archive events manually, without the polling to be started. If the detect parameter is set to true, the criteria specified for the archive event are verified and the event is only pushed if they are fullfilled. If detect is set to false the event is fired without any value checking!

Parameters

attr_name: (str) attribute name
implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the change event properties when set to true. Default value is true.

Return

None

set_change_event(self, attr_name, implemented, detect=True) → None¶

Set an implemented flag for the attribute to indicate that the server fires change events manually, without the polling to be started. If the detect parameter is set to true, the criteria specified for the change event are verified and the event is only pushed if they are fullfilled. If detect is set to false the event is fired without any value checking!

Parameters

attr_name: (str) attribute name
implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the change event properties when set to true. Default value is true.

Return

None

set_state(self, new_state) → None¶

Set device state.

Parameters

new_state: (DevState) the new device state

Return

None

set_status(self, new_status) → None¶

Set device status.

Parameters

new_status: (str) the new device status

Return

None

signal_handler(self, signo) → None¶

Signal handler. The method executed when the signal arrived in the device server process. This method is defined as virtual and then, can be redefined following device needs.

Parameters

signo: (int) the signal number

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

stop_polling(self) → None¶

stop_polling(self, with_db_upd) → None

Stop all polling for a device. if the device is polled, call this method before deleting it.

Parameters

with_db_upd: (bool) Is it necessary to update db ?

Return

None

New in PyTango 7.1.2

unregister_signal(self, signo) → None¶

Unregister a signal. Unregister this device as device to be informed when signal signo is sent to to the device server process

Parameters

signo: (int) signal identifier

Return

None

warn_stream(self, msg, *args) → None¶

Sends the given message to the tango warn stream.

Since PyTango 7.1.3, the same can be achieved with:
print(msg, file=self.log_warn)

Parameters

msg: (str) the message to be sent to the warn stream

Return

None

write_attr_hardware(self) → None¶

Write the hardware for attributes. Default method to implement an action necessary on a device to write the hardware involved in a a write attribute. This method must be redefined in sub-classes in order to support writable attribute

Parameters

attr_list(sequence<int>) list of indices in the device object attribute vector: of an attribute to be written.

Return

None

Throws

DevFailed This method does not throw exception but a redefined method can.

DeviceClass¶

class tango.DeviceClass(*args, **kwargs)¶

Base class for all TANGO device-class class. A TANGO device-class class is a class where is stored all data/method common to all devices of a TANGO device class

DeviceClass.add_wiz_class_prop(self, str, str) -> None

DeviceClass.add_wiz_class_prop(self, str, str, str) -> None

For internal usage only

Parameters: None
Return: None

DeviceClass.add_wiz_dev_prop(self, str, str) -> None

DeviceClass.add_wiz_dev_prop(self, str, str, str) -> None

For internal usage only

Parameters: None
Return: None

create_device(self, device_name, alias=None, cb=None) → None¶

Creates a new device of the given class in the database, creates a new DeviceImpl for it and calls init_device (just like it is done for existing devices when the DS starts up)

An optional parameter callback is called AFTER the device is registered in the database and BEFORE the init_device for the newly created device is called

Throws tango.DevFailed:

the device name exists already or
the given class is not registered for this DS.
the cb is not a callable

New in PyTango 7.1.2

Parameters

device_name: (str) the device name
alias: (str) optional alias. Default value is None meaning do not create device alias
cb: (callable) a callback that is called AFTER the device is registered in the database and BEFORE the init_device for the newly created device is called. Typically you may want to put device and/or attribute properties in the database here. The callback must receive a parameter: device name (str). Default value is None meaning no callback

Return

None

delete_device(self, klass_name, device_name) → None¶

Deletes an existing device from the database and from this running server

Throws tango.DevFailed:

the device name doesn’t exist in the database

the device name doesn’t exist in this DS.

New in PyTango 7.1.2

Parameters

klass_name: (str) the device class name
device_name: (str) the device name

Return

None

device_destroyer(name)¶: for internal usage only

device_factory(device_list)¶: for internal usage only

device_name_factory(self, dev_name_list) → None¶

Create device(s) name list (for no database device server). This method can be re-defined in DeviceClass sub-class for device server started without database. Its rule is to initialise class device name. The default method does nothing.

Parameters

dev_name_list: (seq) sequence of devices to be filled

Return

None

dyn_attr(self, device_list) → None¶

Default implementation does not do anything Overwrite in order to provide dynamic attributes

Parameters

device_list: (seq) sequence of devices of this class

Return

None

export_device(self, dev, corba_dev_name='Unused') → None¶

For internal usage only

Parameters

dev: (DeviceImpl) device object
corba_dev_name: (str) CORBA device name. Default value is ‘Unused’

Return

None

get_cmd_by_name(self, (str)cmd_name) → tango.Command¶

Get a reference to a command object.

Parameters

cmd_name: (str) command name

Return

(tango.Command) tango.Command object

New in PyTango 8.0.0

get_command_list(self) → sequence<tango.Command>¶

Gets the list of tango.Command objects for this class

Parameters: None
Return: (sequence<tango.Command>) list of tango.Command objects for this class

New in PyTango 8.0.0

get_cvs_location(self) → None¶

Gets the cvs localtion

Parameters: None
Return: (str) cvs location

get_cvs_tag(self) → str¶

Gets the cvs tag

Parameters: None
Return: (str) cvs tag

get_device_list(self) → sequence<tango.DeviceImpl>¶

Gets the list of tango.DeviceImpl objects for this class

Parameters: None
Return: (sequence<tango.DeviceImpl>) list of tango.DeviceImpl objects for this class

get_doc_url(self) → str¶

Get the TANGO device class documentation URL.

Parameters: None
Return: (str) the TANGO device type name

get_name(self) → str¶

Get the TANGO device class name.

Parameters: None
Return: (str) the TANGO device class name.

get_type(self) → str¶

Gets the TANGO device type name.

Parameters: None
Return: (str) the TANGO device type name

register_signal(self, signo) → None¶

register_signal(self, signo, own_handler=false) → None

Register a signal. Register this class as class to be informed when signal signo is sent to to the device server process. The second version of the method is available only under Linux.

Throws tango.DevFailed:

if the signal number is out of range
if the operating system failed to register a signal for the process.

Parameters

signo: (int) signal identifier
own_handler: (bool) true if you want the device signal handler to be executed in its own handler instead of being executed by the signal thread. If this parameter is set to true, care should be taken on how the handler is written. A default false value is provided

Return

None

set_type(self, dev_type) → None¶

Set the TANGO device type name.

Parameters

dev_type: (str) the new TANGO device type name

Return

None

signal_handler(self, signo) → None¶

Signal handler.

The method executed when the signal arrived in the device server process. This method is defined as virtual and then, can be redefined following device class needs.

Parameters

signo: (int) signal identifier

Return

None

unregister_signal(self, signo) → None¶

Unregister a signal. Unregister this class as class to be informed when signal signo is sent to to the device server process

Parameters

signo: (int) signal identifier

Return

None

Logging decorators¶

LogIt¶

class tango.LogIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.LogIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have DEBUG level. If you whish to have different log level messages, you should implement subclasses that log to those levels. See, for example, tango.InfoIt.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

DebugIt¶

class tango.DebugIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method as DEBUG level records.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.DebugIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have DEBUG level.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

InfoIt¶

class tango.InfoIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method as INFO level records.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.InfoIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have INFO level.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

WarnIt¶

class tango.WarnIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method as WARN level records.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.WarnIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have WARN level.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

ErrorIt¶

class tango.ErrorIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method as ERROR level records.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.ErrorIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have ERROR level.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

FatalIt¶

class tango.FatalIt(show_args=False, show_kwargs=False, show_ret=False)¶

A class designed to be a decorator of any method of a tango.DeviceImpl subclass. The idea is to log the entrance and exit of any decorated method as FATAL level records.

Example:

class MyDevice(tango.Device_4Impl):

    @tango.FatalIt()
    def read_Current(self, attr):
        attr.set_value(self._current, 1)

All log messages generated by this class have FATAL level.

The constructor receives three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs - shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

Attribute classes¶

Attr¶

class tango.Attr(*args, **kwargs)¶

This class represents a Tango writable attribute.

get_assoc(self) → str¶

Get the associated name.

Parameters: None
Return: (bool) the associated name

get_cl_name(self) → str¶

Returns the class name

Parameters: None
Return: (str) the class name

New in PyTango 7.2.0

get_class_properties(self) → sequence<AttrProperty>¶

Get the class level attribute properties

Parameters: None
Return: (sequence<AttrProperty>) the class attribute properties

get_disp_level(self) → DispLevel¶

Get the attribute display level

Parameters: None
Return: (DispLevel) the attribute display level

get_format(self) → AttrDataFormat¶

Get the attribute format

Parameters: None
Return: (AttrDataFormat) the attribute format

get_memorized(self) → bool¶

Determine if the attribute is memorized or not.

Parameters: None
Return: (bool) True if the attribute is memorized

get_memorized_init(self) → bool¶

Determine if the attribute is written at startup from the memorized value if it is memorized

Parameters: None
Return: (bool) True if initialized with memorized value or not

get_name(self) → str¶

Get the attribute name.

Parameters: None
Return: (str) the attribute name

get_polling_period(self) → int¶

Get the polling period (mS)

Parameters: None
Return: (int) the polling period (mS)

get_type(self) → int¶

Get the attribute data type

Parameters: None
Return: (int) the attribute data type

get_user_default_properties(self) → sequence<AttrProperty>¶

Get the user default attribute properties

Parameters: None
Return: (sequence<AttrProperty>) the user default attribute properties

get_writable(self) → AttrWriteType¶

Get the attribute write type

Parameters: None
Return: (AttrWriteType) the attribute write type

is_archive_event(self) → bool¶

Check if the archive event is fired manually for this attribute.

Parameters: None
Return: (bool) true if a manual fire archive event is implemented.

is_assoc(self) → bool¶

Determine if it is assoc.

Parameters: None
Return: (bool) if it is assoc

is_change_event(self) → bool¶

Check if the change event is fired manually for this attribute.

Parameters: None
Return: (bool) true if a manual fire change event is implemented.

is_check_archive_criteria(self) → bool¶

Check if the archive event criteria should be checked when firing the event manually.

Parameters: None
Return: (bool) true if a archive event criteria will be checked.

is_check_change_criteria(self) → bool¶

Check if the change event criteria should be checked when firing the event manually.

Parameters: None
Return: (bool) true if a change event criteria will be checked.

is_data_ready_event(self) → bool¶

Check if the data ready event is fired for this attribute.

Parameters: None
Return: (bool) true if firing data ready event is implemented.

New in PyTango 7.2.0

set_archive_event(self) → None¶

Set a flag to indicate that the server fires archive events manually without the polling to be started for the attribute If the detect parameter is set to true, the criteria specified for the archive event are verified and the event is only pushed if they are fullfilled.

If detect is set to false the event is fired without checking!

Parameters

implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the archive event properties when set to true.

Return

None

set_change_event(self, implemented, detect) → None¶

Set a flag to indicate that the server fires change events manually without the polling to be started for the attribute. If the detect parameter is set to true, the criteria specified for the change event are verified and the event is only pushed if they are fullfilled.

If detect is set to false the event is fired without checking!

Parameters

implemented: (bool) True when the server fires change events manually.
detect: (bool) Triggers the verification of the change event properties when set to true.

Return

None

set_cl_name(self, cl) → None¶

Sets the class name

Parameters

cl: (str) new class name

Return

None

New in PyTango 7.2.0

set_class_properties(self, props) → None¶

Set the class level attribute properties

Parameters

props: (StdAttrPropertyVector) new class level attribute properties

Return

None

set_data_ready_event(self, implemented) → None¶

Set a flag to indicate that the server fires data ready events.

Parameters

implemented: (bool) True when the server fires data ready events

Return

None

New in PyTango 7.2.0

set_default_properties(self) → None¶

Set default attribute properties.

Parameters

attr_prop: (UserDefaultAttrProp) the user default property class

Return

None

set_disp_level(self, disp_lelel) → None¶

Set the attribute display level.

Parameters

disp_level: (DispLevel) the new display level

Return

None

set_memorized(self) → None¶

Set the attribute as memorized in database (only for scalar and writable attribute) With no argument the setpoint will be written to the attribute during initialisation!

Parameters: None
Return: None

set_memorized_init(self, write_on_init) → None¶

Set the initialisation flag for memorized attributes true = the setpoint value will be written to the attribute on initialisation false = only the attribute setpoint is initialised. No action is taken on the attribute

Parameters

write_on_init: (bool) if true the setpoint value will be written to the attribute on initialisation

Return

None

set_polling_period(self, period) → None¶

Set the attribute polling update period.

Parameters

period: (int) the attribute polling period (in mS)

Return

None

Attribute¶

class tango.Attribute(*args, **kwargs)¶

This class represents a Tango attribute.

check_alarm(self) → bool¶

Check if the attribute read value is below/above the alarm level.

Parameters: None
Return: (bool) true if the attribute is in alarm condition.
Throws: DevFailed If no alarm level is defined.

get_assoc_ind(self) → int¶

Get index of the associated writable attribute.

Parameters: None
Return: (int) the index in the main attribute vector of the associated writable attribute

get_assoc_name(self) → str¶

Get name of the associated writable attribute.

Parameters: None
Return: (str) the associated writable attribute name

get_attr_serial_model(self) → AttrSerialModel¶

Get attribute serialization model.

Parameters: None
Return: (AttrSerialModel) The attribute serialization model

New in PyTango 7.1.0

get_data_format(self) → AttrDataFormat¶

Get attribute data format.

Parameters: None
Return: (AttrDataFormat) the attribute data format

get_data_size(self) → None¶

Get attribute data size.

Parameters: None
Return: (int) the attribute data size

get_data_type(self) → int¶

Get attribute data type.

Parameters: None
Return: (int) the attribute data type

get_date(self) → TimeVal¶

Get a COPY of the attribute date.

Parameters: None
Return: (TimeVal) the attribute date

get_label(self) → str¶

Get attribute label property.

Parameters: None
Return: (str) he attribute label

get_max_dim_x(self) → int¶

Get attribute maximum data size in x dimension.

Parameters: None
Return: (int) the attribute maximum data size in x dimension. Set to 1 for scalar attribute

get_max_dim_y(self) → int¶

Get attribute maximum data size in y dimension.

Parameters: None
Return: (int) the attribute maximum data size in y dimension. Set to 0 for scalar attribute

get_name(self) → str¶

Get attribute name.

Parameters: None
Return: (str) The attribute name

get_polling_period(self) → int¶

Get attribute polling period.

Parameters: None
Return: (int) The attribute polling period in mS. Set to 0 when the attribute is not polled

get_properties(self, attr_cfg=None) → AttributeConfig¶

Get attribute properties.

Parameters

conf: the config object to be filled with the attribute configuration. Default is None meaning the method will create internally a new AttributeConfig_5 and return it. Can be AttributeConfig, AttributeConfig_2, AttributeConfig_3, AttributeConfig_5 or MultiAttrProp

Return

(AttributeConfig) the config object filled with attribute configuration information

New in PyTango 7.1.4

get_quality(self) → AttrQuality¶

Get a COPY of the attribute data quality.

Parameters: None
Return: (AttrQuality) the attribute data quality

get_writable(self) → AttrWriteType¶

Get the attribute writable type (RO/WO/RW).

Parameters: None
Return: (AttrWriteType) The attribute write type.

get_x(self) → int¶

Get attribute data size in x dimension.

Parameters: None
Return: (int) the attribute data size in x dimension. Set to 1 for scalar attribute

get_y(self) → int¶

Get attribute data size in y dimension.

Parameters: None
Return: (int) the attribute data size in y dimension. Set to 1 for scalar attribute

is_archive_event(self) → bool¶

Check if the archive event is fired manually (without polling) for this attribute.

Parameters: None
Return: (bool) True if a manual fire archive event is implemented.

New in PyTango 7.1.0

is_change_event(self) → bool¶

Check if the change event is fired manually (without polling) for this attribute.

Parameters: None
Return: (bool) True if a manual fire change event is implemented.

New in PyTango 7.1.0

is_check_archive_criteria(self) → bool¶

Check if the archive event criteria should be checked when firing the event manually.

Parameters: None
Return: (bool) True if a archive event criteria will be checked.

New in PyTango 7.1.0

is_check_change_criteria(self) → bool¶

Check if the change event criteria should be checked when firing the event manually.

Parameters: None
Return: (bool) True if a change event criteria will be checked.

New in PyTango 7.1.0

is_data_ready_event(self) → bool¶

Check if the data ready event is fired manually (without polling) for this attribute.

Parameters: None
Return: (bool) True if a manual fire data ready event is implemented.

New in PyTango 7.2.0

is_max_alarm(self) → bool¶

Check if the attribute is in maximum alarm condition.

Parameters: None
Return: (bool) true if the attribute is in alarm condition (read value above the max. alarm).

is_max_warning(self) → bool¶

Check if the attribute is in maximum warning condition.

Parameters: None
Return: (bool) true if the attribute is in warning condition (read value above the max. warning).

is_min_alarm(self) → bool¶

Check if the attribute is in minimum alarm condition.

Parameters: None
Return: (bool) true if the attribute is in alarm condition (read value below the min. alarm).

is_min_warning(self) → bool¶

Check if the attribute is in minimum warning condition.

Parameters: None
Return: (bool) true if the attribute is in warning condition (read value below the min. warning).

is_polled(self) → bool¶

Check if the attribute is polled.

Parameters: None
Return: (bool) true if the attribute is polled.

is_rds_alarm(self) → bool¶

Check if the attribute is in RDS alarm condition.

Parameters: None
Return: (bool) true if the attribute is in RDS condition (Read Different than Set).

is_write_associated(self) → bool¶

Check if the attribute has an associated writable attribute.

Parameters: None
Return: (bool) True if there is an associated writable attribute

remove_configuration(self) → None¶

Remove the attribute configuration from the database. This method can be used to clean-up all the configuration of an attribute to come back to its default values or the remove all configuration of a dynamic attribute before deleting it.

The method removes all configured attribute properties and removes the attribute from the list of polled attributes.

Parameters: None
Return: None

New in PyTango 7.1.0

set_archive_event(self, implemented, detect=True) → None¶

Set a flag to indicate that the server fires archive events manually, without the polling to be started for the attribute If the detect parameter is set to true, the criteria specified for the archive event are verified and the event is only pushed if they are fullfilled.

Parameters

implemented: (bool) True when the server fires archive events manually.
detect: (bool) (optional, default is True) Triggers the verification of the archive event properties when set to true.

Return

None

New in PyTango 7.1.0

set_assoc_ind(self, index) → None¶

Set index of the associated writable attribute.

Parameters

index: (int) The new index in the main attribute vector of the associated writable attribute

Return

None

set_attr_serial_model(self, ser_model) → void¶

Set attribute serialization model. This method allows the user to choose the attribute serialization model.

Parameters

ser_model: (AttrSerialModel) The new serialisation model. The serialization model must be one of ATTR_BY_KERNEL, ATTR_BY_USER or ATTR_NO_SYNC

Return

None

New in PyTango 7.1.0

set_change_event(self, implemented, detect=True) → None¶

Set a flag to indicate that the server fires change events manually, without the polling to be started for the attribute. If the detect parameter is set to true, the criteria specified for the change event are verified and the event is only pushed if they are fullfilled. If detect is set to false the event is fired without any value checking!

Parameters

implemented: (bool) True when the server fires change events manually.
detect: (bool) (optional, default is True) Triggers the verification of the change event properties when set to true.

Return

None

New in PyTango 7.1.0

set_data_ready_event(self, implemented) → None¶

Set a flag to indicate that the server fires data ready events.

Parameters

implemented: (bool) True when the server fires data ready events manually.

Return

None

New in PyTango 7.2.0

set_date(self, new_date) → None¶

Set attribute date.

Parameters

new_date: (TimeVal) the attribute date

Return

None

set_properties(self, attr_cfg, dev) → None¶

Set attribute properties.

This method sets the attribute properties value with the content of the fileds in the AttributeConfig/ AttributeConfig_3 object

Parameters

conf: (AttributeConfig or AttributeConfig_3) the config object.
dev: (DeviceImpl) the device (not used, maintained for backward compatibility)

New in PyTango 7.1.4

set_quality(self, quality, send_event=False) → None¶

Set attribute data quality.

Parameters

quality: (AttrQuality) the new attribute data quality
send_event: (bool) true if a change event should be sent. Default is false.

Return

None

set_value(self, data, dim_x=1, dim_y=0) → None <= DEPRECATED¶

set_value(self, data) → None

set_value(self, str_data, data) → None

Set internal attribute value. This method stores the attribute read value inside the object. This method also stores the date when it is called and initializes the attribute quality factor.

Parameters

data: the data to be set. Data must be compatible with the attribute type and format. In the DEPRECATED form for SPECTRUM and IMAGE attributes, data can be any type of FLAT sequence of elements compatible with the attribute type. In the new form (without dim_x or dim_y) data should be any sequence for SPECTRUM and a SEQUENCE of equal-length SEQUENCES for IMAGE attributes. The recommended sequence is a C continuous and aligned numpy array, as it can be optimized.
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
dim_x: (int) [DEPRECATED] the attribute x length. Default value is 1
dim_y: (int) [DEPRECATED] the attribute y length. Default value is 0

Return

None

set_value_date_quality(self, data, time_stamp, quality, dim_x=1, dim_y=0) → None <= DEPRECATED¶

set_value_date_quality(self, data, time_stamp, quality) → None

set_value_date_quality(self, str_data, data, time_stamp, quality) → None

Set internal attribute value, date and quality factor. This method stores the attribute read value, the date and the attribute quality factor inside the object.

Parameters

data: the data to be set. Data must be compatible with the attribute type and format. In the DEPRECATED form for SPECTRUM and IMAGE attributes, data can be any type of FLAT sequence of elements compatible with the attribute type. In the new form (without dim_x or dim_y) data should be any sequence for SPECTRUM and a SEQUENCE of equal-length SEQUENCES for IMAGE attributes. The recommended sequence is a C continuous and aligned numpy array, as it can be optimized.
str_data: (str) special variation for DevEncoded data type. In this case ‘data’ must be a str or an object with the buffer interface.
dim_x: (int) [DEPRECATED] the attribute x length. Default value is 1
dim_y: (int) [DEPRECATED] the attribute y length. Default value is 0
time_stamp: (double) the time stamp
quality: (AttrQuality) the attribute quality factor

Return

None

WAttribute¶

class tango.WAttribute(*args, **kwargs)¶

This class represents a Tango writable attribute.

get_max_value(self) → obj¶

Get attribute maximum value or throws an exception if the attribute does not have a maximum value.

Parameters: None
Return: (obj) an object with the python maximum value

get_min_value(self) → obj¶

Get attribute minimum value or throws an exception if the attribute does not have a minimum value.

Parameters: None
Return: (obj) an object with the python minimum value

get_write_value(self, lst) → None <= DEPRECATED¶

get_write_value(self, extract_as=ExtractAs.Numpy) → obj

Retrieve the new value for writable attribute.

Parameters

extract_as: (ExtractAs)
lst: [out] (list) a list object that will be filled with the attribute write value (DEPRECATED)

Return

(obj) the attribute write value.

get_write_value_length(self) → int¶

Retrieve the new value length (data number) for writable attribute.

Parameters: None
Return: (int) the new value data length

is_max_value(self) → bool¶

Check if the attribute has a maximum value.

Parameters: None
Return: (bool) true if the attribute has a maximum value defined

is_min_value(self) → bool¶

Check if the attribute has a minimum value.

Parameters: None
Return: (bool) true if the attribute has a minimum value defined

set_max_value(self, data) → None¶

Set attribute maximum value.

Parameters

data: the attribute maximum value. python data type must be compatible with the attribute data format and type.

Return

None

set_min_value(self, data) → None¶

Set attribute minimum value.

Parameters

data: the attribute minimum value. python data type must be compatible with the attribute data format and type.

Return

None

MultiAttribute¶

class tango.MultiAttribute(*args, **kwargs)¶

There is one instance of this class for each device. This class is mainly an aggregate of Attribute or WAttribute objects. It eases management of multiple attributes

check_alarm(self) → bool¶

check_alarm(self, attr_name) → bool

check_alarm(self, ind) → bool

The 1st version of the method checks alarm on all attribute(s) with an alarm defined.

The 2nd version of the method checks alarm for one attribute with a given name.

The 3rd version of the method checks alarm for one attribute from its index in the main attributes vector.

Parameters

attr_name: (str) attribute name
ind: (int) the attribute index

Return

(bool) True if at least one attribute is in alarm condition

Throws

DevFailed If at least one attribute does not have any alarm level defined

New in PyTango 7.0.0

get_attr_by_ind(self, ind) → Attribute¶

Get Attribute object from its index. This method returns an Attribute object from the index in the main attribute vector.

Parameters

ind: (int) the attribute index

Return

(Attribute) the attribute object

get_attr_by_name(self, attr_name) → Attribute¶

Get Attribute object from its name. This method returns an Attribute object with a name passed as parameter. The equality on attribute name is case independant.

Parameters

attr_name: (str) attribute name

Return

(Attribute) the attribute object

Throws

DevFailed If the attribute is not defined.

get_attr_ind_by_name(self, attr_name) → int¶

Get Attribute index into the main attribute vector from its name. This method returns the index in the Attribute vector (stored in the MultiAttribute object) of an attribute with a given name. The name equality is case independant.

Parameters

attr_name: (str) attribute name

Return

(int) the attribute index

Throws

DevFailed If the attribute is not found in the vector.

New in PyTango 7.0.0

get_attr_nb(self) → int¶

Get attribute number.

Parameters: None
Return: (int) the number of attributes

New in PyTango 7.0.0

get_attribute_list(self) → seq<Attribute>¶

Get the list of attribute objects.

Return: (seq) list of attribute objects

New in PyTango 7.2.1

get_w_attr_by_ind(self, ind) → WAttribute¶

Get a writable attribute object from its index. This method returns an WAttribute object from the index in the main attribute vector.

Parameters

ind: (int) the attribute index

Return

(WAttribute) the attribute object

get_w_attr_by_name(self, attr_name) → WAttribute¶

Get a writable attribute object from its name. This method returns an WAttribute object with a name passed as parameter. The equality on attribute name is case independant.

Parameters

attr_name: (str) attribute name

Return

(WAttribute) the attribute object

Throws

DevFailed If the attribute is not defined.

read_alarm(self, status) → None¶

Add alarm message to device status. This method add alarm mesage to the string passed as parameter. A message is added for each attribute which is in alarm condition

Parameters

status: (str) a string (should be the device status)

Return

None

New in PyTango 7.0.0

UserDefaultAttrProp¶

class tango.UserDefaultAttrProp(*args, **kwargs)¶

User class to set attribute default properties. This class is used to set attribute default properties. Three levels of attributes properties setting are implemented within Tango. The highest property setting level is the database. Then the user default (set using this UserDefaultAttrProp class) and finally a Tango library default value

set_abs_change(self, def_abs_change) → None <= DEPRECATED¶

Set default change event abs_change property.

Parameters

def_abs_change: (str) the user default change event abs_change property

Return

None

Deprecated since PyTango 8.0. Please use set_event_abs_change instead.

set_archive_abs_change(self, def_archive_abs_change) → None <= DEPRECATED¶

Set default archive event abs_change property.

Parameters

def_archive_abs_change: (str) the user default archive event abs_change property

Return

None

Deprecated since PyTango 8.0. Please use set_archive_event_abs_change instead.

set_archive_event_abs_change(self, def_archive_abs_change) → None¶

Set default archive event abs_change property.

Parameters

def_archive_abs_change: (str) the user default archive event abs_change property

Return

None

New in PyTango 8.0

set_archive_event_period(self, def_archive_period) → None¶

Set default archive event period property.

Parameters

def_archive_period: (str) t

Return

None

New in PyTango 8.0

set_archive_event_rel_change(self, def_archive_rel_change) → None¶

Set default archive event rel_change property.

Parameters

def_archive_rel_change: (str) the user default archive event rel_change property

Return

None

New in PyTango 8.0

set_archive_period(self, def_archive_period) → None <= DEPRECATED¶

Set default archive event period property.

Parameters

def_archive_period: (str) t

Return

None

Deprecated since PyTango 8.0. Please use set_archive_event_period instead.

set_archive_rel_change(self, def_archive_rel_change) → None <= DEPRECATED¶

Set default archive event rel_change property.

Parameters

def_archive_rel_change: (str) the user default archive event rel_change property

Return

None

Deprecated since PyTango 8.0. Please use set_archive_event_rel_change instead.

set_delta_t(self, def_delta_t) → None¶

Set default RDS alarm delta_t property.

Parameters

def_delta_t: (str) the user default RDS alarm delta_t property

Return

None

set_delta_val(self, def_delta_val) → None¶

Set default RDS alarm delta_val property.

Parameters

def_delta_val: (str) the user default RDS alarm delta_val property

Return

None

set_description(self, def_description) → None¶

Set default description property.

Parameters

def_description: (str) the user default description property

Return

None

set_display_unit(self, def_display_unit) → None¶

Set default display unit property.

Parameters

def_display_unit: (str) the user default display unit property

Return

None

set_enum_labels(self, enum_labels) → None¶

Set default enumeration labels.

Parameters

enum_labels: (seq) list of enumeration labels

New in PyTango 9.2.0

set_event_abs_change(self, def_abs_change) → None¶

Set default change event abs_change property.

Parameters

def_abs_change: (str) the user default change event abs_change property

Return

None

New in PyTango 8.0

set_event_period(self, def_period) → None¶

Set default periodic event period property.

Parameters

def_period: (str) the user default periodic event period property

Return

None

New in PyTango 8.0

set_event_rel_change(self, def_rel_change) → None¶

Set default change event rel_change property.

Parameters

def_rel_change: (str) the user default change event rel_change property

Return

None

New in PyTango 8.0

set_format(self, def_format) → None¶

Set default format property.

Parameters

def_format: (str) the user default format property

Return

None

set_label(self, def_label) → None¶

Set default label property.

Parameters

def_label: (str) the user default label property

Return

None

set_max_alarm(self, def_max_alarm) → None¶

Set default max_alarm property.

Parameters

def_max_alarm: (str) the user default max_alarm property

Return

None

set_max_value(self, def_max_value) → None¶

Set default max_value property.

Parameters

def_max_value: (str) the user default max_value property

Return

None

set_max_warning(self, def_max_warning) → None¶

Set default max_warning property.

Parameters

def_max_warning: (str) the user default max_warning property

Return

None

set_min_alarm(self, def_min_alarm) → None¶

Set default min_alarm property.

Parameters

def_min_alarm: (str) the user default min_alarm property

Return

None

set_min_value(self, def_min_value) → None¶

Set default min_value property.

Parameters

def_min_value: (str) the user default min_value property

Return

None

set_min_warning(self, def_min_warning) → None¶

Set default min_warning property.

Parameters

def_min_warning: (str) the user default min_warning property

Return

None

set_period(self, def_period) → None <= DEPRECATED¶

Set default periodic event period property.

Parameters

def_period: (str) the user default periodic event period property

Return

None

Deprecated since PyTango 8.0. Please use set_event_period instead.

set_rel_change(self, def_rel_change) → None <= DEPRECATED¶

Set default change event rel_change property.

Parameters

def_rel_change: (str) the user default change event rel_change property

Return

None

Deprecated since PyTango 8.0. Please use set_event_rel_change instead.

set_standard_unit(self, def_standard_unit) → None¶

Set default standard unit property.

Parameters

def_standard_unit: (str) the user default standard unit property

Return

None

set_unit(self, def_unit) → None¶

Set default unit property.

Parameters

def_unit: (str) te user default unit property

Return

None

Util¶

class tango.Util(*args, **kwargs)¶

This class is a used to store TANGO device server process data and to provide the user with a set of utilities method.

This class is implemented using the singleton design pattern. Therefore a device server process can have only one instance of this class and its constructor is not public. Example:

util = tango.Util.instance()
    print(util.get_host_name())

add_Cpp_TgClass(device_class_name, tango_device_class_name)¶

Register a new C++ tango class.

If there is a shared library file called MotorClass.so which contains a MotorClass class and a _create_MotorClass_class method. Example:

util.add_Cpp_TgClass('MotorClass', 'Motor')

Note

the parameter ‘device_class_name’ must match the shared library name.

Deprecated since version 7.1.2: Use tango.Util.add_class() instead.

add_TgClass(klass_device_class, klass_device, device_class_name=None)¶

Register a new python tango class. Example:

util.add_TgClass(MotorClass, Motor)
util.add_TgClass(MotorClass, Motor, 'Motor') # equivalent to previous line

Deprecated since version 7.1.2: Use tango.Util.add_class() instead.

add_class(self, class<DeviceClass>, class<DeviceImpl>, language="python") → None¶

Register a new tango class (‘python’ or ‘c++’).

If language is ‘python’ then args must be the same as tango.Util.add_TgClass(). Otherwise, args should be the ones in tango.Util.add_Cpp_TgClass(). Example:
util.add_class(MotorClass, Motor)
util.add_class('CounterClass', 'Counter', language='c++')

New in PyTango 7.1.2

connect_db(self) → None¶

Connect the process to the TANGO database. If the connection to the database failed, a message is displayed on the screen and the process is aborted

Parameters: None
Return: None

create_device(self, klass_name, device_name, alias=None, cb=None) → None¶

Creates a new device of the given class in the database, creates a new DeviceImpl for it and calls init_device (just like it is done for existing devices when the DS starts up)

An optional parameter callback is called AFTER the device is registered in the database and BEFORE the init_device for the newly created device is called

Throws tango.DevFailed:

the device name exists already or

the given class is not registered for this DS.

the cb is not a callable

New in PyTango 7.1.2

Parameters

klass_name: (str) the device class name
device_name: (str) the device name
alias: (str) optional alias. Default value is None meaning do not create device alias
cb: (callable) a callback that is called AFTER the device is registered in the database and BEFORE the init_device for the newly created device is called. Typically you may want to put device and/or attribute properties in the database here. The callback must receive a parameter: device name (str). Default value is None meaning no callback

Return

None

delete_device(self, klass_name, device_name) → None¶

Deletes an existing device from the database and from this running server

Throws tango.DevFailed:

the device name doesn’t exist in the database

the device name doesn’t exist in this DS.

New in PyTango 7.1.2

Parameters

klass_name: (str) the device class name
device_name: (str) the device name

Return

None

get_class_list(self) → seq<DeviceClass>¶

Returns a list of objects of inheriting from DeviceClass

Parameters: None
Return: (seq) a list of objects of inheriting from DeviceClass

get_database(self) → Database¶

Get a reference to the TANGO database object

Parameters: None
Return: (Database) the database

New in PyTango 7.0.0

get_device_by_name(self, dev_name) → DeviceImpl¶

Get a device reference from its name

Parameters

dev_name: (str) The TANGO device name

Return

(DeviceImpl) The device reference

New in PyTango 7.0.0

get_device_list(self) → sequence<DeviceImpl>¶

Get device list from name. It is possible to use a wild card (‘*’) in the name parameter (e.g. “*”, “/tango/tangotest/n*”, …)

Parameters: None
Return: (sequence<DeviceImpl>) the list of device objects

New in PyTango 7.0.0

get_device_list_by_class(self, class_name) → sequence<DeviceImpl>¶

Get the list of device references for a given TANGO class. Return the list of references for all devices served by one implementation of the TANGO device pattern implemented in the process.

Parameters

class_name: (str) The TANGO device class name

Return

(sequence<DeviceImpl>) The device reference list

New in PyTango 7.0.0

get_ds_exec_name(self) → str¶

Get a COPY of the device server executable name.

Parameters: None
Return: (str) a COPY of the device server executable name.

New in PyTango 3.0.4

get_ds_inst_name(self) → str¶

Get a COPY of the device server instance name.

Parameters: None
Return: (str) a COPY of the device server instance name.

New in PyTango 3.0.4

get_ds_name(self) → str¶

Get the device server name. The device server name is the <device server executable name>/<the device server instance name>

Parameters: None
Return: (str) device server name

New in PyTango 3.0.4

get_dserver_device(self) → DServer¶

Get a reference to the dserver device attached to the device server process

Parameters: None
Return: (DServer) A reference to the dserver device

New in PyTango 7.0.0

get_host_name(self) → str¶

Get the host name where the device server process is running.

Parameters: None
Return: (str) the host name where the device server process is running

New in PyTango 3.0.4

get_pid(self) → TangoSys_Pid¶

Get the device server process identifier.

Parameters: None
Return: (int) the device server process identifier

get_pid_str(self) → str¶

Get the device server process identifier as a string.

Parameters: None
Return: (str) the device server process identifier as a string

New in PyTango 3.0.4

get_polling_threads_pool_size(self) → int¶

Get the polling threads pool size.

Parameters: None
Return: (int) the maximun number of threads in the polling threads pool

get_serial_model(self) → SerialModel¶

Get the serialization model.

Parameters: None
Return: (SerialModel) the serialization model

get_server_version(self) → str¶

Get the device server version.

Parameters: None
Return: (str) the device server version.

get_sub_dev_diag(self) → SubDevDiag¶

Get the internal sub device manager

Parameters: None
Return: (SubDevDiag) the sub device manager

New in PyTango 7.0.0

get_tango_lib_release(self) → int¶

Get the TANGO library version number.

Parameters: None
Return: (int) The Tango library release number coded in 3 digits (for instance 550,551,552,600,….)

get_trace_level(self) → int¶

Get the process trace level.

Parameters: None
Return: (int) the process trace level.

get_version_str(self) → str¶

Get the IDL TANGO version.

Parameters: None
Return: (str) the IDL TANGO version.

New in PyTango 3.0.4

is_device_restarting(self, (str)dev_name) → bool¶

Check if the device is actually restarted by the device server process admin device with its DevRestart command

Parameters: dev_name : (str) device name
Return: (bool) True if the device is restarting.

New in PyTango 8.0.0

is_svr_shutting_down(self) → bool¶

Check if the device server process is in its shutting down sequence

Parameters: None
Return: (bool) True if the server is in its shutting down phase.

New in PyTango 8.0.0

is_svr_starting(self) → bool¶

Check if the device server process is in its starting phase

Parameters: None
Return: (bool) True if the server is in its starting phase

New in PyTango 8.0.0

reset_filedatabase(self) → None¶

Reread the file database

Parameters: None
Return: None

New in PyTango 7.0.0

server_init(self, with_window=False) → None¶

Initialize all the device server pattern(s) embedded in a device server process.

Parameters

with_window: (bool) default value is False

Return

None

Throws

DevFailed If the device pattern initialistaion failed

server_run(self) → None¶

Run the CORBA event loop. This method runs the CORBA event loop. For UNIX or Linux operating system, this method does not return. For Windows in a non-console mode, this method start a thread which enter the CORBA event loop.

Parameters: None
Return: None

server_set_event_loop(self, event_loop) → None¶

This method registers an event loop function in a Tango server. This function will be called by the process main thread in an infinite loop The process will not use the classical ORB blocking event loop. It is the user responsability to code this function in a way that it implements some kind of blocking in order not to load the computer CPU. The following piece of code is an example of how you can use this feature:

_LOOP_NB = 1
def looping():
    global _LOOP_NB
    print "looping", _LOOP_NB
    time.sleep(0.1)
    _LOOP_NB += 1
    return _LOOP_NB > 100

def main():
    py = tango.Util(sys.argv)

    # ...

    U = tango.Util.instance()
    U.server_set_event_loop(looping)
    U.server_init()
    U.server_run()

Parameters: None
Return: None

New in PyTango 8.1.0

set_polling_threads_pool_size(self, thread_nb) → None¶

Set the polling threads pool size.

Parameters

thread_nb: (int) the maximun number of threads in the polling threads pool

Return

None

New in PyTango 7.0.0

set_serial_model(self, ser) → None¶

Set the serialization model.

Parameters

ser: (SerialModel) the new serialization model. The serialization model must be one of BY_DEVICE, BY_CLASS, BY_PROCESS or NO_SYNC

Return

None

set_server_version(self, vers) → None¶

Set the device server version.

Parameters

vers: (str) the device server version

Return

None

set_trace_level(self, level) → None¶

Set the process trace level.

Parameters

level: (int) the new process level

Return

None

trigger_attr_polling(self, dev, name) → None¶

Trigger polling for polled attribute. This method send the order to the polling thread to poll one object registered with an update period defined as “externally triggerred”

Parameters

dev: (DeviceImpl) the TANGO device
name: (str) the attribute name which must be polled

Return

None

trigger_cmd_polling(self, dev, name) → None¶

Trigger polling for polled command. This method send the order to the polling thread to poll one object registered with an update period defined as “externally triggerred”

Parameters

dev: (DeviceImpl) the TANGO device
name: (str) the command name which must be polled

Return

None

Throws

DevFailed If the call failed

unregister_server(self) → None¶

Unregister a device server process from the TANGO database. If the database call fails, a message is displayed on the screen and the process is aborted

Parameters: None
Return: None

New in PyTango 7.0.0

Database API¶

class tango.Database(*args, **kwargs)¶

Database is the high level Tango object which contains the link to the static database. Database provides methods for all database commands : get_device_property(), put_device_property(), info(), etc.. To create a Database, use the default constructor. Example:

db = Database()

The constructor uses the TANGO_HOST env. variable to determine which instance of the Database to connect to.

add_device(self, dev_info) → None¶

Add a device to the database. The device name, server and class are specified in the DbDevInfo structure
Example
dev_info = DbDevInfo()
dev_info.name = 'my/own/device'
dev_info._class = 'MyDevice'
dev_info.server = 'MyServer/test'
db.add_device(dev_info)

Parameters

dev_info: (DbDevInfo) device information

Return

None

add_server(self, servname, dev_info, with_dserver=False) → None¶

Add a (group of) devices to the database. This is considered as a low level call because it may render the database inconsistent if it is not used properly.

If with_dserver parameter is set to False (default), this call will only register the given dev_info(s). You should include in the list of dev_info an entry to the usually hidden DServer device.

If with_dserver parameter is set to True, the call will add an additional DServer device if it is not included in the dev_info parameter.

Example using with_dserver=True:

dev_info1 = DbDevInfo()
dev_info1.name = 'my/own/device'
dev_info1._class = 'MyDevice'
dev_info1.server = 'MyServer/test'
db.add_server(dev_info1.server, dev_info, with_dserver=True)

Same example using with_dserver=False:

dev_info1 = DbDevInfo()
dev_info1.name = 'my/own/device'
dev_info1._class = 'MyDevice'
dev_info1.server = 'MyServer/test'

dev_info2 = DbDevInfo()
dev_info1.name = 'dserver/' + dev_info1.server
dev_info1._class = 'DServer
dev_info1.server = dev_info1.server

dev_info = dev_info1, dev_info2
db.add_server(dev_info1.server, dev_info)

New in version 8.1.7: added with_dserver parameter

Parameters

servname: (str) server name
dev_info: (sequence<DbDevInfo> | DbDevInfos | DbDevInfo) containing the server device(s) information
with_dserver: (bool) whether or not to auto create DServer device in server

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

build_connection(self) → None¶

Tries to build a connection to the Database server.

Parameters: None
Return: None

New in PyTango 7.0.0

check_access_control(self, dev_name) → AccessControlType¶

Check the access for the given device for this client.

Parameters

dev_name: (str) device name

Return

the access control type as a AccessControlType object

New in PyTango 7.0.0

check_tango_host(self, tango_host_env) → None¶

Check the TANGO_HOST environment variable syntax and extract database server host(s) and port(s) from it.

Parameters

tango_host_env: (str) The TANGO_HOST env. variable value

Return

None

New in PyTango 7.0.0

delete_attribute_alias(self, alias) → None¶

Remove the alias associated to an attribute name.

Parameters

alias: (str) alias

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_class_attribute_property(self, class_name, value) → None¶

Delete a list of attribute properties for the specified class.

Parameters

class_name

(str) class name

propnames

can be one of the following:

DbData [in] - several property data to be deleted
sequence<str> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, seq<str>> keys are attribute names and value being a list of attribute property names

Return

None

Throws

ConnectionFailed, CommunicationFailed DevFailed from device (DB_SQLError)

delete_class_pipe_property(self, class_name, value) → None¶

Delete a list of pipe properties for the specified class.

Parameters

class_name

(str) class name

propnames

can be one of the following:

DbData [in] - several property data to be deleted
sequence<str> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, seq<str>> keys are pipe names and value being a list of pipe property names

Return

None

Throws

ConnectionFailed, CommunicationFailed DevFailed from device (DB_SQLError)

delete_class_property(self, class_name, value) → None¶

Delete a the given of properties for the specified class.

Parameters

class_name

(str) class name

value

can be one of the following:

str [in] - single property data to be deleted
DbDatum [in] - single property data to be deleted
DbData [in] - several property data to be deleted
sequence<str> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, obj> [in] - keys are property names to be deleted (values are ignored)
dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_device(self, dev_name) → None¶

Delete the device of the specified name from the database.

Parameters

dev_name: (str) device name

Return

None

delete_device_alias(self, alias) → void¶

Delete a device alias

Parameters

alias: (str) alias name

Return

None

delete_device_attribute_property(self, dev_name, value) → None¶

Delete a list of attribute properties for the specified device.

Parameters

devname: (string) device name
propnames: can be one of the following: 1. DbData [in] - several property data to be deleted 2. sequence<str> [in]- several property data to be deleted 3. sequence<DbDatum> [in] - several property data to be deleted 3. dict<str, seq<str>> keys are attribute names and value being a list of attribute property names

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_device_pipe_property(self, dev_name, value) → None¶

Delete a list of pipe properties for the specified device.

Parameters

devname: (string) device name
propnames: can be one of the following: 1. DbData [in] - several property data to be deleted 2. sequence<str> [in]- several property data to be deleted 3. sequence<DbDatum> [in] - several property data to be deleted 3. dict<str, seq<str>> keys are pipe names and value being a list of pipe property names

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_device_property(self, dev_name, value) → None¶

Delete a the given of properties for the specified device.

Parameters

dev_name: (str) object name
value: can be one of the following: 1. str [in] - single property data to be deleted 2. DbDatum [in] - single property data to be deleted 3. DbData [in] - several property data to be deleted 4. sequence<str> [in]- several property data to be deleted 5. sequence<DbDatum> [in] - several property data to be deleted 6. dict<str, obj> [in] - keys are property names to be deleted (values are ignored) 7. dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_property(self, obj_name, value) → None¶

Delete a the given of properties for the specified object.

Parameters

obj_name

(str) object name

value

can be one of the following:

str [in] - single property data to be deleted
DbDatum [in] - single property data to be deleted
DbData [in] - several property data to be deleted
sequence<string> [in]- several property data to be deleted
sequence<DbDatum> [in] - several property data to be deleted
dict<str, obj> [in] - keys are property names to be deleted (values are ignored)
dict<str, DbDatum> [in] - several DbDatum.name are property names to be deleted (keys are ignored)

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

delete_server(self, server) → None¶

Delete the device server and its associated devices from database.

Parameters

server: (str) name of the server to be deleted with format: <server name>/<instance>

Return

None

delete_server_info(self, server) → None¶

Delete server information of the specifed server from the database.

Parameters

server: (str) name of the server to be deleted with format: <server name>/<instance>

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

export_device(self, dev_export) → None¶

Update the export info for this device in the database.

Example

dev_export = DbDevExportInfo()
dev_export.name = 'my/own/device'
dev_export.ior = <the real ior>
dev_export.host = <the host>
dev_export.version = '3.0'
dev_export.pid = '....'
db.export_device(dev_export)

Parameters

dev_export: (DbDevExportInfo) export information

Return

None

export_event(self, event_data) → None¶

Export an event to the database.

Parameters

eventdata: (sequence<str>) event data (same as DbExportEvent Database command)

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

export_server(self, dev_info) → None¶

Export a group of devices to the database.

Parameters

devinfo: (sequence<DbDevExportInfo> | DbDevExportInfos | DbDevExportInfo) containing the device(s) to export information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_access_except_errors(self) → DevErrorList¶

Returns a reference to the control access exceptions.

Parameters: None
Return: DevErrorList

New in PyTango 7.0.0

get_alias(self, alias) → str¶

Get the device alias name from its name.

Parameters

alias: (str) device name

Return

alias

New in PyTango 3.0.4

Deprecated since version 8.1.0: Use get_alias_from_device() instead

get_alias_from_attribute(self, attr_name) → str¶

Get the attribute alias from the full attribute name.

Parameters

attr_name: (str) full attribute name

Return

attribute alias

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 8.1.0

get_alias_from_device(self, alias) → str¶

Get the device alias name from its name.

Parameters

alias: (str) device name

Return

alias

New in PyTango 8.1.0

get_attribute_alias(self, alias) → str¶

Get the full attribute name from an alias.

Parameters

alias: (str) attribute alias

Return

full attribute name

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

Deprecated since version 8.1.0: Use :class:`Database().get_attribute_from_alias` instead

get_attribute_alias_list(self, filter) → DbDatum¶

Get attribute alias list. The parameter alias is a string to filter the alias list returned. Wildcard (*) is supported. For instance, if the string alias passed as the method parameter is initialised with only the * character, all the defined attribute alias will be returned. If there is no alias with the given filter, the returned array will have a 0 size.

Parameters

filter: (str) attribute alias filter

Return

DbDatum containing the list of matching attribute alias

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_attribute_from_alias(self, alias) → str¶

Get the full attribute name from an alias.

Parameters

alias: (str) attribute alias

Return

full attribute name

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 8.1.0

get_class_attribute_list(self, class_name, wildcard) → DbDatum¶

Query the database for a list of attributes defined for the specified class which match the specified wildcard.

Parameters

class_name: (str) class name
wildcard: (str) attribute name

Return

DbDatum containing the list of matching attributes for the given class

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_class_attribute_property(self, class_name, value) → dict<str, dict<str, seq<str>>¶

Query the database for a list of class attribute properties for the specified class. The method returns all the properties for the specified attributes.

Parameters

class_name

(str) class name

propnames

can be one of the following:

str [in] - single attribute properties to be fetched
DbDatum [in] - single attribute properties to be fetched
DbData [in,out] - several attribute properties to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several attribute properties to be fetched
sequence<DbDatum> [in] - several attribute properties to be fetched
dict<str, obj> [in,out] - keys are attribute names In this case the given dict values will be changed to contain the several attribute property values

Return

a dictionary which keys are the attribute names the value associated with each key being a another dictionary where keys are property names and value is a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_class_attribute_property_history(self, dev_name, attr_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specifed class attribute property. Note that prop_name and attr_name can contain a wildcard character (eg: ‘prop*’).

Parameters

dev_name: (str) device name
attr_name: (str) attribute name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_class_for_device(self, dev_name) → str¶

Return the class of the specified device.

Parameters

dev_name: (str) device name

Return

a string containing the device class

get_class_inheritance_for_device(self, dev_name) → DbDatum¶

Return the class inheritance scheme of the specified device.

Parameters

devn_ame: (str) device name

Return

DbDatum with the inheritance class list

New in PyTango 7.0.0

get_class_list(self, wildcard) → DbDatum¶

Query the database for a list of classes which match the specified wildcard

Parameters

wildcard: (str) class wildcard

Return

DbDatum containing the list of matching classes

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_class_pipe_list(self, class_name, wildcard) → DbDatum¶

Query the database for a list of pipes defined for the specified class which match the specified wildcard. This corresponds to the pure C++ API call.

Parameters

class_name: (str) class name
wildcard: (str) pipe name

Return

DbDatum containing the list of matching pipes for the given class

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_class_pipe_property(self, class_name, value) → dict<str, dict<str, seq<str>>¶

Query the database for a list of class pipe properties for the specified class. The method returns all the properties for the specified pipes.

Parameters

class_name

(str) class name

propnames

can be one of the following:

str [in] - single pipe properties to be fetched
DbDatum [in] - single pipe properties to be fetched
DbData [in,out] - several pipe properties to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several pipe properties to be fetched
sequence<DbDatum> [in] - several pipe properties to be fetched
dict<str, obj> [in,out] - keys are pipe names In this case the given dict values will be changed to contain the several pipe property values

Return

a dictionary which keys are the pipe names the value associated with each key being a another dictionary where keys are property names and value is a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_class_pipe_property_history(self, dev_name, pipe_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specifed class pipe property. Note that prop_name and attr_name can contain a wildcard character (eg: ‘prop*’).

Parameters

dev_name: (str) device name
pipe_name: (str) pipe name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_class_property(self, class_name, value) → dict<str, seq<str>>¶

Query the database for a list of class properties.

Parameters

class_name

(str) class name

value

can be one of the following:

str [in] - single property data to be fetched
tango.DbDatum [in] - single property data to be fetched
tango.DbData [in,out] - several property data to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several property data to be fetched
sequence<DbDatum> [in] - several property data to be fetched
dict<str, obj> [in,out] - keys are property names In this case the given dict values will be changed to contain the several property values

Return

a dictionary which keys are the property names the value associated with each key being a a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_class_property_history(self, class_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specified class property. Note that propname can contain a wildcard character (eg: ‘prop*’).

Parameters

class_name: (str) class name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_class_property_list(self, class_name) → DbDatum¶

Query the database for a list of properties defined for the specified class.

Parameters

class_name: (str) class name

Return

DbDatum containing the list of properties for the specified class

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_alias(self, alias) → str¶

Get the device name from an alias.

Parameters

alias: (str) alias

Return

device name

Deprecated since version 8.1.0: Use get_device_from_alias() instead

get_device_alias_list(self, filter) → DbDatum¶

Get device alias list. The parameter alias is a string to filter the alias list returned. Wildcard (*) is supported.

Parameters

filter: (str) a string with the alias filter (wildcard (*) is supported)

Return

DbDatum with the list of device names

New in PyTango 7.0.0

get_device_attribute_list(self, dev_name, att_list) → None¶

Get the list of attribute(s) with some data defined in database for a specified device. Note that this is not the list of all device attributes because not all attribute(s) have some data in database This corresponds to the pure C++ API call.

Parameters

dev_name: (str) device name
att_list [out]: (StdStringVector) array that will contain the attribute name list

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_attribute_property(self, dev_name, value) → dict<str, dict<str, seq<str>>>¶

Query the database for a list of device attribute properties for the specified device. The method returns all the properties for the specified attributes.

Parameters

dev_name

(string) device name

value

can be one of the following:

str [in] - single attribute properties to be fetched
DbDatum [in] - single attribute properties to be fetched
DbData [in,out] - several attribute properties to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several attribute properties to be fetched
sequence<DbDatum> [in] - several attribute properties to be fetched
dict<str, obj> [in,out] - keys are attribute names In this case the given dict values will be changed to contain the several attribute property values

Return

a dictionary which keys are the attribute names the value associated with each key being a another dictionary where keys are property names and value is a DbDatum containing the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_attribute_property_history(self, dev_name, attr_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specified device attribute property. Note that propname and devname can contain a wildcard character (eg: ‘prop*’).

Parameters

dev_name: (str) device name
attr_name: (str) attribute name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_device_class_list(self, server) → DbDatum¶

Query the database for a list of devices and classes served by the specified server. Return a list with the following structure: [device name, class name, device name, class name, …]

Parameters

server: (str) name of the server with format: <server name>/<instance>

Return

DbDatum containing list with the following structure: [device_name, class name]

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_device_domain(self, wildcard) → DbDatum¶

Query the database for a list of of device domain names which match the wildcard provided (* is wildcard for any character(s)). Domain names are case insensitive.

Parameters

wildcard: (str) domain filter

Return

DbDatum with the list of device domain names

get_device_exported(self, filter) → DbDatum¶

Query the database for a list of exported devices whose names satisfy the supplied filter (* is wildcard for any character(s))

Parameters

filter: (str) device name filter (wildcard)

Return

DbDatum with the list of exported devices

get_device_exported_for_class(self, class_name) → DbDatum¶

Query database for list of exported devices for the specified class.

Parameters

class_name: (str) class name

Return

DbDatum with the list of exported devices for the

New in PyTango 7.0.0

get_device_family(self, wildcard) → DbDatum¶

Query the database for a list of of device family names which match the wildcard provided (* is wildcard for any character(s)). Family names are case insensitive.

Parameters

wildcard: (str) family filter

Return

DbDatum with the list of device family names

get_device_from_alias(self, alias) → str¶

Get the device name from an alias.

Parameters

alias: (str) alias

Return

device name

New in PyTango 8.1.0

get_device_info(self, dev_name) → DbDevFullInfo¶

Query the databse for the full info of the specified device.

Example

dev_info = db.get_device_info('my/own/device')
print(dev_info.name)
print(dev_info.class_name)
print(dev_info.ds_full_name)
print(dev_info.exported)
print(dev_info.ior)
print(dev_info.version)
print(dev_info.pid)
print(dev_info.started_date)
print(dev_info.stopped_date)

Parameters

dev_name: (str) device name

Return

DbDevFullInfo

New in PyTango 8.1.0

get_device_member(self, wildcard) → DbDatum¶

Query the database for a list of of device member names which match the wildcard provided (* is wildcard for any character(s)). Member names are case insensitive.

Parameters

wildcard: (str) member filter

Return

DbDatum with the list of device member names

get_device_name(self, serv_name, class_name) → DbDatum¶

Query the database for a list of devices served by a server for a given device class

Parameters

serv_name: (str) server name
class_name: (str) device class name

Return

DbDatum with the list of device names

get_device_pipe_list(self, dev_name, pipe_list) → None¶

Get the list of pipe(s) with some data defined in database for a specified device. Note that this is not the list of all device pipes because not all pipe(s) have some data in database This corresponds to the pure C++ API call.

Parameters

dev_name: (str) device name
pipe_list [out]: (StdStringVector) array that will contain the pipe name list

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_pipe_property(self, dev_name, value) → dict<str, dict<str, seq<str>>>¶

Query the database for a list of device pipe properties for the specified device. The method returns all the properties for the specified pipes.

Parameters

dev_name

(string) device name

value

can be one of the following:

str [in] - single pipe properties to be fetched
DbDatum [in] - single pipe properties to be fetched
DbData [in,out] - several pipe properties to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several pipe properties to be fetched
sequence<DbDatum> [in] - several pipe properties to be fetched
dict<str, obj> [in,out] - keys are pipe names In this case the given dict values will be changed to contain the several pipe property values

Return

a dictionary which keys are the pipe names the value associated with each key being a another dictionary where keys are property names and value is a DbDatum containing the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_pipe_property_history(self, dev_name, pipe_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specified device pipe property. Note that propname and devname can contain a wildcard character (eg: ‘prop*’).

Parameters

dev_name: (str) device name
pipe_name: (str) pipe name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_property(self, dev_name, value) → dict<str, seq<str>>¶

Query the database for a list of device properties.

Parameters

dev_name

(str) object name

value

can be one of the following:

str [in] - single property data to be fetched
DbDatum [in] - single property data to be fetched
DbData [in,out] - several property data to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several property data to be fetched
sequence<DbDatum> [in] - several property data to be fetched
dict<str, obj> [in,out] - keys are property names In this case the given dict values will be changed to contain the several property values

Return

a dictionary which keys are the property names the value associated with each key being a a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_device_property_history(self, dev_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specified device property. Note that propname can contain a wildcard character (eg: ‘prop*’). This corresponds to the pure C++ API call.

Parameters

serv_name: (str) server name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_device_property_list(self, dev_name, wildcard, array=None) → DbData¶

Query the database for a list of properties defined for the specified device and which match the specified wildcard. If array parameter is given, it must be an object implementing de ‘append’ method. If given, it is filled with the matching property names. If not given the method returns a new DbDatum containing the matching property names.

New in PyTango 7.0.0

Parameters

dev_name: (str) device name
wildcard: (str) property name wildcard
array: [out] (sequence) (optional) array that will contain the matching property names.

Return

if container is None, return is a new DbDatum containing the matching property names. Otherwise returns the given array filled with the property names

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device

get_device_service_list(self, dev_name) → DbDatum¶

Query database for the list of services provided by the given device.

Parameters

dev_name: (str) device name

Return

DbDatum with the list of services

New in PyTango 8.1.0

get_file_name(self) → str¶

Returns the database file name or throws an exception if not using a file database

Parameters: None
Return: a string containing the database file name
Throws: DevFailed

New in PyTango 7.2.0

get_host_list(self) → DbDatum¶

get_host_list(self, wildcard) → DbDatum

Returns the list of all host names registered in the database.

Parameters

wildcard: (str) (optional) wildcard (eg: ‘l-c0*’)

Return

DbDatum with the list of registered host names

get_host_server_list(self, host_name) → DbDatum¶

Query the database for a list of servers registered on the specified host.

Parameters

host_name: (str) host name

Return

DbDatum containing list of servers for the specified host

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_info(self) → str¶

Query the database for some general info about the tables.

Parameters: None
Return: a multiline string

get_instance_name_list(self, serv_name) → DbDatum¶

Return the list of all instance names existing in the database for the specifed server.

Parameters

serv_name: (str) server name with format <server name>

Return

DbDatum containing list of instance names for the specified server

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_object_list(self, wildcard) → DbDatum¶

Query the database for a list of object (free properties) for which properties are defined and which match the specified wildcard.

Parameters

wildcard: (str) object wildcard

Return

DbDatum containing the list of object names matching the given wildcard

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_object_property_list(self, obj_name, wildcard) → DbDatum¶

Query the database for a list of properties defined for the specified object and which match the specified wildcard.

Parameters

obj_name: (str) object name
wildcard: (str) property name wildcard

Return

DbDatum with list of properties defined for the specified object and which match the specified wildcard

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_property(self, obj_name, value) → dict<str, seq<str>>¶

Query the database for a list of object (i.e non-device) properties.

Parameters

obj_name

(str) object name

value

can be one of the following:

str [in] - single property data to be fetched
DbDatum [in] - single property data to be fetched
DbData [in,out] - several property data to be fetched In this case (direct C++ API) the DbData will be filled with the property values
sequence<str> [in] - several property data to be fetched
sequence<DbDatum> [in] - several property data to be fetched
dict<str, obj> [in,out] - keys are property names In this case the given dict values will be changed to contain the several property values

Return

a dictionary which keys are the property names the value associated with each key being a a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_property_forced(obj_name, value)¶

get_property(self, obj_name, value) -> dict<str, seq<str>>

Query the database for a list of object (i.e non-device) properties.

Parameters

obj_name

(str) object name

value

can be one of the following:

str [in] - single property data to be fetched

DbDatum [in] - single property data to be fetched

DbData [in,out] - several property data to be fetched In this case (direct C++ API) the DbData will be filled with the property values

sequence<str> [in] - several property data to be fetched

sequence<DbDatum> [in] - several property data to be fetched

dict<str, obj> [in,out] - keys are property names In this case the given dict values will be changed to contain the several property values

Return

a dictionary which keys are the property names the value associated with each key being a a sequence of strings being the property value.

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

get_property_history(self, obj_name, prop_name) → DbHistoryList¶

Get the list of the last 10 modifications of the specifed object property. Note that propname can contain a wildcard character (eg: ‘prop*’)

Parameters

serv_name: (str) server name
prop_name: (str) property name

Return

DbHistoryList containing the list of modifications

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

get_server_class_list(self, server) → DbDatum¶

Query the database for a list of classes instantiated by the specified server. The DServer class exists in all TANGO servers and for this reason this class is removed from the returned list.

Parameters

server: (str) name of the server to be deleted with format: <server name>/<instance>

Return

DbDatum containing list of class names instanciated by the specified server

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_server_info(self, server) → DbServerInfo¶

Query the database for server information.

Parameters

server: (str) name of the server with format: <server name>/<instance>

Return

DbServerInfo with server information

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_server_list(self) → DbDatum¶

get_server_list(self, wildcard) → DbDatum

Return the list of all servers registered in the database. If wildcard parameter is given, then the list of matching servers will be returned (ex: Serial/*)

Parameters

wildcard: (str) host wildcard (ex: Serial/*)

Return

DbDatum containing list of registered servers

get_server_name_list(self) → DbDatum¶

Return the list of all server names registered in the database.

Parameters: None
Return: DbDatum containing list of server names
Throws: ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

get_services(self, serv_name, inst_name) → DbDatum¶

Query database for specified services.

Parameters

serv_name: (str) service name
inst_name: (str) instance name (can be a wildcard character (‘*’))

Return

DbDatum with the list of available services

New in PyTango 3.0.4

import_device(self, dev_name) → DbDevImportInfo¶

Query the databse for the export info of the specified device.

Example

dev_imp_info = db.import_device('my/own/device')
print(dev_imp_info.name)
print(dev_imp_info.exported)
print(dev_imp_info.ior)
print(dev_imp_info.version)

Parameters

dev_name: (str) device name

Return

DbDevImportInfo

is_control_access_checked(self) → bool¶

Returns True if control access is checked or False otherwise.

Parameters: None
Return: (bool) True if control access is checked or False

New in PyTango 7.0.0

is_multi_tango_host(self) → bool¶

Returns if in multi tango host.

Parameters: None
Return: True if multi tango host or False otherwise

New in PyTango 7.1.4

put_attribute_alias(self, attr_name, alias) → None¶

Set an alias for an attribute name. The attribute alias is specified by alias and the attribute name is specifed by attr_name. If the given alias already exists, a DevFailed exception is thrown.

Parameters

attr_name: (str) full attribute name
alias: (str) alias

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_class_attribute_property(self, class_name, value) → None¶

Insert or update a list of properties for the specified class.

Parameters

class_name

(str) class name

propdata

can be one of the following:

tango.DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, dict<str, obj>> keys are attribute names and value being another dictionary which keys are the attribute property names and the value associated with each key being:

3.1 seq<str> 3.2 tango.DbDatum

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_class_pipe_property(self, class_name, value) → None¶

Insert or update a list of properties for the specified class.

Parameters

class_name

(str) class name

propdata

can be one of the following:

tango.DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, dict<str, obj>> keys are pipe names and value being another dictionary which keys are the pipe property names and the value associated with each key being:

3.1 seq<str> 3.2 tango.DbDatum

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_class_property(self, class_name, value) → None¶

Insert or update a list of properties for the specified class.

Parameters

class_name: (str) class name
value: can be one of the following: 1. DbDatum - single property data to be inserted 2. DbData - several property data to be inserted 3. sequence<DbDatum> - several property data to be inserted 4. dict<str, DbDatum> - keys are property names and value has data to be inserted 5. dict<str, obj> - keys are property names and str(obj) is property value 6. dict<str, seq<str>> - keys are property names and value has data to be inserted

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_device_alias(self, dev_name, alias) → None¶

Query database for list of exported devices for the specified class.

Parameters

dev_name: (str) device name
alias: (str) alias name

Return

None

put_device_attribute_property(self, dev_name, value) → None¶

Insert or update a list of properties for the specified device.

Parameters

dev_name

(str) device name

value

can be one of the following:

DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, dict<str, obj>> keys are attribute names and value being another dictionary which keys are the attribute property names and the value associated with each key being:

3.1 seq<str> 3.2 tango.DbDatum

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_device_pipe_property(self, dev_name, value) → None¶

Insert or update a list of properties for the specified device.

Parameters

dev_name

(str) device name

value

can be one of the following:

DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, dict<str, obj>> keys are pipe names and value being another dictionary which keys are the pipe property names and the value associated with each key being:

3.1 seq<str> 3.2 tango.DbDatum

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_device_property(self, dev_name, value) → None¶

Insert or update a list of properties for the specified device.

Parameters

dev_name

(str) object name

value

can be one of the following:

DbDatum - single property data to be inserted
DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, DbDatum> - keys are property names and value has data to be inserted
dict<str, obj> - keys are property names and str(obj) is property value
dict<str, seq<str>> - keys are property names and value has data to be inserted

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_property(self, obj_name, value) → None¶

Insert or update a list of properties for the specified object.

Parameters

obj_name

(str) object name

value

can be one of the following:

DbDatum - single property data to be inserted
DbData - several property data to be inserted
sequence<DbDatum> - several property data to be inserted
dict<str, DbDatum> - keys are property names and value has data to be inserted
dict<str, obj> - keys are property names and str(obj) is property value
dict<str, seq<str>> - keys are property names and value has data to be inserted

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

put_server_info(self, info) → None¶

Add/update server information in the database.

Parameters

info: (DbServerInfo) new server information

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 3.0.4

register_service(self, serv_name, inst_name, dev_name) → None¶

Register the specified service wihtin the database.

Parameters

serv_name: (str) service name
inst_name: (str) instance name
dev_name: (str) device name

Return

None

New in PyTango 3.0.4

rename_server(self, old_ds_name, new_ds_name) → None¶

Rename a device server process.

Parameters

old_ds_name: (str) old name
new_ds_name: (str) new name

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 8.1.0

reread_filedatabase(self) → None¶

Force a complete refresh over the database if using a file based database.

Parameters: None
Return: None

New in PyTango 7.0.0

set_access_checked(self, val) → None¶

Sets or unsets the control access check.

Parameters

val: (bool) True to set or False to unset the access control

Return

None

New in PyTango 7.0.0

unexport_device(self, dev_name) → None¶

Mark the specified device as unexported in the database
Example
db.unexport_device('my/own/device')

Parameters

dev_name: (str) device name

Return

None

unexport_event(self, event) → None¶

Un-export an event from the database.

Parameters

event: (str) event

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

New in PyTango 7.0.0

unexport_server(self, server) → None¶

Mark all devices exported for this server as unexported.

Parameters

server: (str) name of the server to be unexported with format: <server name>/<instance>

Return

None

Throws

ConnectionFailed, CommunicationFailed, DevFailed from device (DB_SQLError)

unregister_service(self, serv_name, inst_name) → None¶

Unregister the specified service from the database.

Parameters

serv_name: (str) service name
inst_name: (str) instance name

Return

None

New in PyTango 3.0.4

write_filedatabase(self) → None¶

Force a write to the file if using a file based database.

Parameters: None
Return: None

New in PyTango 7.0.0

class tango.DbDatum(*args, **kwargs)¶

A single database value which has a name, type, address and value and methods for inserting and extracting C++ native types. This is the fundamental type for specifying database properties. Every property has a name and has one or more values associated with it. A status flag indicates if there is data in the DbDatum object or not. An additional flag allows the user to activate exceptions.

Note: DbDatum is extended to support the python sequence API.: This way the DbDatum behaves like a sequence of strings. This allows the user to work with a DbDatum as if it was working with the old list of strings.

New in PyTango 7.0.0

is_empty(self) → bool¶

Returns True or False depending on whether the DbDatum object contains data or not. It can be used to test whether a property is defined in the database or not.

Parameters: None
Return: (bool) True if no data or False otherwise.

New in PyTango 7.0.0

size(self) → int¶

Returns the number of separate elements in the value.

Parameters: None
Return: the number of separate elements in the value.

New in PyTango 7.0.0

class tango.DbDevExportInfo(*args, **kwargs)¶

A structure containing export info for a device (should be retrieved from the database) with the following members:

name : (str) device name

ior : (str) CORBA reference of the device

host : name of the computer hosting the server

version : (str) version

pid : process identifier

class tango.DbDevExportInfo(*args, **kwargs)¶

A structure containing export info for a device (should be retrieved from the database) with the following members:

name : (str) device name

ior : (str) CORBA reference of the device

host : name of the computer hosting the server

version : (str) version

pid : process identifier

class tango.DbDevImportInfo(*args, **kwargs)¶

A structure containing import info for a device (should be retrieved from the database) with the following members:

name : (str) device name

exported : 1 if device is running, 0 else

ior : (str)CORBA reference of the device

version : (str) version

class tango.DbDevInfo(*args, **kwargs)¶

A structure containing available information for a device with the following members:

name : (str) name

_class : (str) device class

server : (str) server

class tango.DbHistory(*args, **kwargs)¶

A structure containing the modifications of a property. No public members.

get_attribute_name(self) → str¶

Returns the attribute name (empty for object properties or device properties)

Parameters: None
Return: (str) attribute name

get_date(self) → str¶

Returns the update date

Parameters: None
Return: (str) update date

get_name(self) → str¶

Returns the property name.

Parameters: None
Return: (str) property name

get_value(self) → DbDatum¶

Returns a COPY of the property value

Parameters: None
Return: (DbDatum) a COPY of the property value

is_deleted(self) → bool¶

Returns True if the property has been deleted or False otherwise

Parameters: None
Return: (bool) True if the property has been deleted or False otherwise

class tango.DbServerInfo(*args, **kwargs)¶

A structure containing available information for a device server with the following members:

name : (str) name

host : (str) host

mode : (str) mode

level : (str) level

Encoded API¶

This feature is only possible since PyTango 7.1.4

class tango.EncodedAttribute(*args, **kwargs)¶

decode_gray16(da, extract_as=None)¶

Decode a 16 bits grayscale image (GRAY16) and returns a 16 bits gray scale image.

param da

DeviceAttribute that contains the image

type da

DeviceAttribute

param extract_as

defaults to ExtractAs.Numpy

type extract_as

ExtractAs

return

the decoded data

In case String string is choosen as extract method, a tuple is returned:
width<int>, height<int>, buffer<str>

In case Numpy is choosen as extract method, a numpy.ndarray is returned with ndim=2, shape=(height, width) and dtype=numpy.uint16.

In case Tuple or List are choosen, a tuple<tuple<int>> or list<list<int>> is returned.

Warning

The PyTango calls that return a DeviceAttribute (like DeviceProxy.read_attribute() or DeviceProxy.command_inout()) automatically extract the contents by default. This method requires that the given DeviceAttribute is obtained from a call which DOESN’T extract the contents. Example:

dev = tango.DeviceProxy("a/b/c")
da = dev.read_attribute("my_attr", extract_as=tango.ExtractAs.Nothing)
enc = tango.EncodedAttribute()
data = enc.decode_gray16(da)

decode_gray8(da, extract_as=None)¶

Decode a 8 bits grayscale image (JPEG_GRAY8 or GRAY8) and returns a 8 bits gray scale image.

param da

DeviceAttribute that contains the image

type da

DeviceAttribute

param extract_as

defaults to ExtractAs.Numpy

type extract_as

ExtractAs

return

the decoded data

In case String string is choosen as extract method, a tuple is returned:
width<int>, height<int>, buffer<str>

In case Numpy is choosen as extract method, a numpy.ndarray is returned with ndim=2, shape=(height, width) and dtype=numpy.uint8.

In case Tuple or List are choosen, a tuple<tuple<int>> or list<list<int>> is returned.

Warning

The PyTango calls that return a DeviceAttribute (like DeviceProxy.read_attribute() or DeviceProxy.command_inout()) automatically extract the contents by default. This method requires that the given DeviceAttribute is obtained from a call which DOESN’T extract the contents. Example:

dev = tango.DeviceProxy("a/b/c")
da = dev.read_attribute("my_attr", extract_as=tango.ExtractAs.Nothing)
enc = tango.EncodedAttribute()
data = enc.decode_gray8(da)

decode_rgb32(da, extract_as=None)¶

Decode a color image (JPEG_RGB or RGB24) and returns a 32 bits RGB image.

param da

DeviceAttribute that contains the image

type da

DeviceAttribute

param extract_as

defaults to ExtractAs.Numpy

type extract_as

ExtractAs

return

the decoded data

In case String string is choosen as extract method, a tuple is returned:
width<int>, height<int>, buffer<str>

In case Numpy is choosen as extract method, a numpy.ndarray is returned with ndim=2, shape=(height, width) and dtype=numpy.uint32.

In case Tuple or List are choosen, a tuple<tuple<int>> or list<list<int>> is returned.

Warning

The PyTango calls that return a DeviceAttribute (like DeviceProxy.read_attribute() or DeviceProxy.command_inout()) automatically extract the contents by default. This method requires that the given DeviceAttribute is obtained from a call which DOESN’T extract the contents. Example:

dev = tango.DeviceProxy("a/b/c")
da = dev.read_attribute("my_attr", extract_as=tango.ExtractAs.Nothing)
enc = tango.EncodedAttribute()
data = enc.decode_rgb32(da)

encode_gray16(gray16, width=0, height=0)¶

Encode a 16 bit grayscale image (no compression)

param gray16

an object containning image information

type gray16

str or buffer or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if gray16 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if gray16 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type height

int

Note

When numpy.ndarray is given:

gray16 MUST be CONTIGUOUS, ALIGNED

if gray16.ndims != 2, width and height MUST be given and gray16.nbytes/2 MUST match width*height

if gray16.ndims == 2, gray16.itemsize MUST be 2 (typically, gray16.dtype is one of numpy.dtype.int16, numpy.dtype.uint16, numpy.dtype.short or numpy.dtype.ushort)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    data = numpy.arange(100, dtype=numpy.int16)
    data = numpy.array((data,data,data))
    enc.encode_gray16(data)
    attr.set_value(enc)

encode_gray8(gray8, width=0, height=0)¶

Encode a 8 bit grayscale image (no compression)

param gray8

an object containning image information

type gray8

str or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if gray8 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if gray8 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type height

int

Note

When numpy.ndarray is given:

gray8 MUST be CONTIGUOUS, ALIGNED

if gray8.ndims != 2, width and height MUST be given and gray8.nbytes MUST match width*height

if gray8.ndims == 2, gray8.itemsize MUST be 1 (typically, gray8.dtype is one of numpy.dtype.byte, numpy.dtype.ubyte, numpy.dtype.int8 or numpy.dtype.uint8)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    data = numpy.arange(100, dtype=numpy.byte)
    data = numpy.array((data,data,data))
    enc.encode_gray8(data)
    attr.set_value(enc)

encode_jpeg_gray8(gray8, width=0, height=0, quality=100.0)¶

Encode a 8 bit grayscale image as JPEG format

param gray8

an object containning image information

type gray8

str or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if gray8 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if gray8 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type height

int

param quality

Quality of JPEG (0=poor quality 100=max quality) (default is 100.0)

type quality

float

Note

When numpy.ndarray is given:

gray8 MUST be CONTIGUOUS, ALIGNED

if gray8.ndims != 2, width and height MUST be given and gray8.nbytes MUST match width*height

if gray8.ndims == 2, gray8.itemsize MUST be 1 (typically, gray8.dtype is one of numpy.dtype.byte, numpy.dtype.ubyte, numpy.dtype.int8 or numpy.dtype.uint8)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    data = numpy.arange(100, dtype=numpy.byte)
    data = numpy.array((data,data,data))
    enc.encode_jpeg_gray8(data)
    attr.set_value(enc)

encode_jpeg_rgb24(rgb24, width=0, height=0, quality=100.0)¶

Encode a 24 bit rgb color image as JPEG format.

param rgb24

an object containning image information

type rgb24

str or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if rgb24 is a string or if it is a numpy.ndarray with ndims != 3. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if rgb24 is a string or if it is a numpy.ndarray with ndims != 3. Otherwise it is calculated internally.

type height

int

param quality

Quality of JPEG (0=poor quality 100=max quality) (default is 100.0)

type quality

float

Note

When numpy.ndarray is given:

rgb24 MUST be CONTIGUOUS, ALIGNED

if rgb24.ndims != 3, width and height MUST be given and rgb24.nbytes/3 MUST match width*height

if rgb24.ndims == 3, rgb24.itemsize MUST be 1 (typically, rgb24.dtype is one of numpy.dtype.byte, numpy.dtype.ubyte, numpy.dtype.int8 or numpy.dtype.uint8) and shape MUST be (height, width, 3)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    # create an 'image' where each pixel is R=0x01, G=0x01, B=0x01
    arr = numpy.ones((10,10,3), dtype=numpy.uint8)
    enc.encode_jpeg_rgb24(data)
    attr.set_value(enc)

encode_jpeg_rgb32(rgb32, width=0, height=0, quality=100.0)¶

Encode a 32 bit rgb color image as JPEG format.

param rgb32

an object containning image information

type rgb32

str or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if rgb32 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if rgb32 is a string or if it is a numpy.ndarray with ndims != 2. Otherwise it is calculated internally.

type height

int

Note

When numpy.ndarray is given:

rgb32 MUST be CONTIGUOUS, ALIGNED

if rgb32.ndims != 2, width and height MUST be given and rgb32.nbytes/4 MUST match width*height

if rgb32.ndims == 2, rgb32.itemsize MUST be 4 (typically, rgb32.dtype is one of numpy.dtype.int32, numpy.dtype.uint32)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    data = numpy.arange(100, dtype=numpy.int32)
    data = numpy.array((data,data,data))
    enc.encode_jpeg_rgb32(data)
    attr.set_value(enc)

encode_rgb24(rgb24, width=0, height=0)¶

Encode a 24 bit color image (no compression)

param rgb24

an object containning image information

type rgb24

str or numpy.ndarray or seq< seq<element> >

param width

image width. MUST be given if rgb24 is a string or if it is a numpy.ndarray with ndims != 3. Otherwise it is calculated internally.

type width

int

param height

image height. MUST be given if rgb24 is a string or if it is a numpy.ndarray with ndims != 3. Otherwise it is calculated internally.

type height

int

Note

When numpy.ndarray is given:

rgb24 MUST be CONTIGUOUS, ALIGNED

if rgb24.ndims != 3, width and height MUST be given and rgb24.nbytes/3 MUST match width*height

if rgb24.ndims == 3, rgb24.itemsize MUST be 1 (typically, rgb24.dtype is one of numpy.dtype.byte, numpy.dtype.ubyte, numpy.dtype.int8 or numpy.dtype.uint8) and shape MUST be (height, width, 3)

Example

:

def read_myattr(self, attr):
    enc = tango.EncodedAttribute()
    # create an 'image' where each pixel is R=0x01, G=0x01, B=0x01
    arr = numpy.ones((10,10,3), dtype=numpy.uint8)
    enc.encode_rgb24(data)
    attr.set_value(enc)

The Utilities API¶

class tango.utils.EventCallback(format='{date} {dev_name} {name} {type} {value}', fd=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, max_buf=100)¶

Useful event callback for test purposes

Usage:

>>> dev = tango.DeviceProxy(dev_name)
>>> cb = tango.utils.EventCallback()
>>> id = dev.subscribe_event("state", tango.EventType.CHANGE_EVENT, cb, [])
2011-04-06 15:33:18.910474 sys/tg_test/1 STATE CHANGE [ATTR_VALID] ON

Allowed format keys are:

date (event timestamp)

reception_date (event reception timestamp)

type (event type)

dev_name (device name)

name (attribute name)

value (event value)

New in PyTango 7.1.4

get_events()¶

Returns the list of events received by this callback

Returns: the list of events received by this callback
Return type: sequence<obj>

push_event(evt)¶: Internal usage only

tango.utils.get_enum_labels(enum_cls)¶

Return list of enumeration labels from Enum class.

The list is useful when creating an attribute, for the enum_labels parameter. The enumeration values are checked to ensure they are unique, start at zero, and increment by one.

Parameters: enum_cls (enum.Enum) – the Enum class to be inspected
Returns: List of label strings
Return type: list
Raises: EnumTypeError – in case the given class is invalid

tango.utils.is_pure_str(obj)¶

Tells if the given object is a python string.

In python 2.x this means any subclass of basestring. In python 3.x this means any subclass of str.

Parameters: obj (object) – the object to be inspected
Returns: True is the given obj is a string or False otherwise
Return type: bool

tango.utils.is_seq(obj)¶

Tells if the given object is a python sequence.

It will return True for any collections.Sequence (list, tuple, str, bytes, unicode), bytearray and (if numpy is enabled) numpy.ndarray

Parameters: obj (object) – the object to be inspected
Returns: True is the given obj is a sequence or False otherwise
Return type: bool

tango.utils.is_non_str_seq(obj)¶

Tells if the given object is a python sequence (excluding string sequences).

It will return True for any collections.Sequence (list, tuple (and bytes in python3)), bytearray and (if numpy is enabled) numpy.ndarray

Parameters: obj (object) – the object to be inspected
Returns: True is the given obj is a sequence or False otherwise
Return type: bool

tango.utils.is_integer(obj)¶

Tells if the given object is a python integer.

It will return True for any int, long (in python 2) and (if numpy is enabled) numpy.integer

Parameters: obj (object) – the object to be inspected
Returns: True is the given obj is a python integer or False otherwise
Return type: bool

tango.utils.is_number(obj)¶

Tells if the given object is a python number.

It will return True for any numbers.Number and (if numpy is enabled) numpy.number

Parameters: obj (object) – the object to be inspected
Returns: True is the given obj is a python number or False otherwise
Return type: bool

tango.utils.is_bool(tg_type, inc_array=False)¶

Tells if the given tango type is boolean

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is boolean or False otherwise

Return type

bool

tango.utils.is_scalar_type(tg_type)¶

Tells if the given tango type is a scalar

Parameters: tg_type (tango.CmdArgType) – tango type
Returns: True if the given tango type is a scalar or False otherwise
Return type: bool

tango.utils.is_array_type(tg_type)¶

Tells if the given tango type is an array type

Parameters: tg_type (tango.CmdArgType) – tango type
Returns: True if the given tango type is an array type or False otherwise
Return type: bool

tango.utils.is_numerical_type(tg_type, inc_array=False)¶

Tells if the given tango type is numerical

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is a numerical or False otherwise

Return type

bool

tango.utils.is_int_type(tg_type, inc_array=False)¶

Tells if the given tango type is integer

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is integer or False otherwise

Return type

bool

tango.utils.is_float_type(tg_type, inc_array=False)¶

Tells if the given tango type is float

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is float or False otherwise

Return type

bool

tango.utils.is_bool_type(tg_type, inc_array=False)¶

Tells if the given tango type is boolean

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is boolean or False otherwise

Return type

bool

tango.utils.is_binary_type(tg_type, inc_array=False)¶

Tells if the given tango type is binary

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is binary or False otherwise

Return type

bool

tango.utils.is_str_type(tg_type, inc_array=False)¶

Tells if the given tango type is string

Parameters

tg_type (tango.CmdArgType) – tango type
inc_array (bool) – (optional, default is False) determines if include array in the list of checked types

Returns

True if the given tango type is string or False otherwise

Return type

bool

tango.utils.obj_2_str(obj, tg_type=None)¶

Converts a python object into a string according to the given tango type

Parameters

obj (object) – the object to be converted
tg_type (tango.CmdArgType) – tango type

Returns

a string representation of the given object

Return type

str

tango.utils.seqStr_2_obj(seq, tg_type, tg_format=None)¶

Translates a sequence<str> to a sequence of objects of give type and format

Parameters

seq (sequence<str>) – the sequence
tg_type (tango.CmdArgType) – tango type
tg_format (tango.AttrDataFormat) – (optional, default is None, meaning SCALAR) tango format

Returns

a new sequence

tango.utils.scalar_to_array_type(tg_type)¶

Gives the array tango type corresponding to the given tango scalar type. Example: giving DevLong will return DevVarLongArray.

Parameters: tg_type (tango.CmdArgType) – tango type
Returns: the array tango type for the given scalar tango type
Return type: tango.CmdArgType
Raises: ValueError – in case the given dtype is not a tango scalar type

tango.utils.get_home()¶

Find user’s home directory if possible. Otherwise raise error.

Returns: user’s home directory
Return type: str

New in PyTango 7.1.4

tango.utils.requires_pytango(min_version=None, conflicts=(), software_name='Software')¶

Determines if the required PyTango version for the running software is present. If not an exception is thrown. Example usage:

from tango import requires_pytango

requires_pytango('7.1', conflicts=['8.1.1'], software='MyDS')

Parameters

min_version (None, str, LooseVersion) – minimum PyTango version [default: None, meaning no minimum required]. If a string is given, it must be in the valid version number format (see: LooseVersion)
conflics (seq<str|LooseVersion>) – a sequence of PyTango versions which conflict with the software using it
software_name (str) – software name using tango. Used in the exception message

Raises

Exception – if the required PyTango version is not met

New in PyTango 8.1.4

tango.utils.requires_tango(min_version=None, conflicts=(), software_name='Software')¶

Determines if the required Tango version for the running software is present. If not an exception is thrown. Example usage:

from tango import requires_tango

requires_tango('7.1', conflicts=['8.1.1'], software='MyDS')

Parameters

min_version (None, str, LooseVersion) – minimum Tango version [default: None, meaning no minimum required]. If a string is given, it must be in the valid version number format (see: LooseVersion)
conflics (seq<str|LooseVersion>) – a sequence of Tango versions which conflict with the software using it
software_name (str) – software name using Tango. Used in the exception message

Raises

Exception – if the required Tango version is not met

New in PyTango 8.1.4

Exception API¶

Exception definition¶

All the exceptions that can be thrown by the underlying Tango C++ API are available in the PyTango python module. Hence a user can catch one of the following exceptions:

DevFailed

ConnectionFailed

CommunicationFailed

WrongNameSyntax

NonDbDevice

WrongData

NonSupportedFeature

AsynCall

AsynReplyNotArrived

EventSystemFailed

NamedDevFailedList

DeviceUnlocked

When an exception is caught, the sys.exc_info() function returns a tuple of three values that give information about the exception that is currently being handled. The values returned are (type, value, traceback). Since most functions don’t need access to the traceback, the best solution is to use something like exctype, value = sys.exc_info()[:2] to extract only the exception type and value. If one of the Tango exceptions is caught, the exctype will be class name of the exception (DevFailed, .. etc) and the value a tuple of dictionary objects all of which containing the following kind of key-value pairs:

reason: a string describing the error type (more readable than the associated error code)
desc: a string describing in plain text the reason of the error.
origin: a string giving the name of the (C++ API) method which thrown the exception
severity: one of the strings WARN, ERR, PANIC giving severity level of the error.

import tango

#  How to protect the script from exceptions raised by the Tango
try:
    # Get proxy on a non existing device should throw an exception
    device = tango.DeviceProxy("non/existing/device")
except DevFailed as df:
    print("Failed to create proxy to non/existing/device:\n%s" % df)

Throwing exception in a device server¶

The C++ tango::Except class with its most important methods have been wrapped to Python. Therefore, in a Python device server, you have the following methods to throw, re-throw or print a Tango::DevFailed exception :

throw_exception() which is a static method
re_throw_exception() which is also a static method
print_exception() which is also a static method

The following code is an example of a command method requesting a command on a sub-device and re-throwing the exception in case of:

try:
    dev.command_inout("SubDevCommand")
except tango.DevFailed as df:
    tango.Except.re_throw_exception(df,
        "MyClass_CommandFailed",
        "Sub device command SubdevCommand failed",
        "Command()")

line 2: Send the command to the sub device in a try/catch block
line 4-6: Re-throw the exception and add a new level of information in the exception stack

Exception API¶

class tango.Except(*args, **kwargs)¶

Bases:

A containner for the static methods:

throw_exception

re_throw_exception

print_exception

compare_exception

class tango.DevError(*args, **kwargs)¶

Bases:

Structure describing any error resulting from a command execution, or an attribute query, with following members:

reason : (str) reason

severity : (ErrSeverity) error severty (WARN, ERR, PANIC)

desc : (str) error description

origin : (str) Tango server method in which the error happened

exception tango.DevFailed(*args, **kwargs)¶: Bases:

exception tango.ConnectionFailed(*args, **kwargs)¶

Bases:

This exception is thrown when a problem occurs during the connection establishment between the application and the device. The API is stateless. This means that DeviceProxy constructors filter most of the exception except for cases described in the following table.

The desc DevError structure field allows a user to get more precise information. These informations are :

DB_DeviceNotDefined
The name of the device not defined in the database

API_CommandFailed
The device and command name

API_CantConnectToDevice
The device name

API_CorbaException
The name of the CORBA exception, its reason, its locality, its completed flag and its minor code

API_CantConnectToDatabase
The database server host and its port number

API_DeviceNotExported
The device name

exception tango.CommunicationFailed(*args, **kwargs)¶

Bases:

This exception is thrown when a communication problem is detected during the communication between the client application and the device server. It is a two levels Tango::DevError structure. In case of time-out, the DevError structures fields are:

Level

Reason

Desc

Severity

0

API_CorbaException

CORBA exception fields translated into a string

ERR

1

API_DeviceTimedOut

String with time-out value and device name

ERR

For all other communication errors, the DevError structures fields are:

Level

Reason

Desc

Severity

0

API_CorbaException

CORBA exception fields translated into a string

ERR

1

API_CommunicationFailed

String with device, method, command/attribute name

ERR

exception tango.WrongNameSyntax(*args, **kwargs)¶: Bases:

This exception has only one level of Tango::DevError structure. The possible value for the reason field are :

API_UnsupportedProtocol
This error occurs when trying to build a DeviceProxy or an AttributeProxy instance for a device with an unsupported protocol. Refer to the appendix on device naming syntax to get the list of supported database modifier

API_UnsupportedDBaseModifier
This error occurs when trying to build a DeviceProxy or an AttributeProxy instance for a device/attribute with a database modifier unsupported. Refer to the appendix on device naming syntax to get the list of supported database modifier

API_WrongDeviceNameSyntax
This error occurs for all the other error in device name syntax. It is thrown by the DeviceProxy class constructor.

API_WrongAttributeNameSyntax
This error occurs for all the other error in attribute name syntax. It is thrown by the AttributeProxy class constructor.

API_WrongWildcardUsage
This error occurs if there is a bad usage of the wildcard character

exception tango.NonDbDevice(*args, **kwargs)¶: Bases:

This exception has only one level of Tango::DevError structure. The reason field is set to API_NonDatabaseDevice. This exception is thrown by the API when using the DeviceProxy or AttributeProxy class database access for non-database device.

exception tango.WrongData(*args, **kwargs)¶

Bases:

This exception has only one level of Tango::DevError structure. The possible value for the reason field are :

API_EmptyDbDatum
This error occurs when trying to extract data from an empty DbDatum object

API_IncompatibleArgumentType
This error occurs when trying to extract data with a type different than the type used to send the data

API_EmptyDeviceAttribute
This error occurs when trying to extract data from an empty DeviceAttribute object

API_IncompatibleAttrArgumentType
This error occurs when trying to extract attribute data with a type different than the type used to send the data

API_EmptyDeviceData
This error occurs when trying to extract data from an empty DeviceData object

API_IncompatibleCmdArgumentType
This error occurs when trying to extract command data with a type different than the type used to send the data

exception tango.NonSupportedFeature(*args, **kwargs)¶: Bases:

This exception is thrown by the API layer when a request to a feature implemented in Tango device interface release n is requested for a device implementing Tango device interface n-x. There is one possible value for the reason field which is API_UnsupportedFeature.

exception tango.AsynCall(*args, **kwargs)¶

Bases:

This exception is thrown by the API layer when a the asynchronous model id badly used. This exception has only one level of Tango::DevError structure. The possible value for the reason field are :

API_BadAsynPollId
This error occurs when using an asynchronous request identifier which is not valid any more.

API_BadAsyn
This error occurs when trying to fire callback when no callback has been previously registered

API_BadAsynReqType
This error occurs when trying to get result of an asynchronous request with an asynchronous request identifier returned by a non-coherent asynchronous request (For instance, using the asynchronous request identifier returned by a command_inout_asynch() method with a read_attribute_reply() attribute).

exception tango.AsynReplyNotArrived(*args, **kwargs)¶

Bases:

This exception is thrown by the API layer when:

a request to get asynchronous reply is made and the reply is not yet arrived

a blocking wait with timeout for asynchronous reply is made and the timeout expired.

There is one possible value for the reason field which is API_AsynReplyNotArrived.

exception tango.EventSystemFailed(*args, **kwargs)¶

Bases:

This exception is thrown by the API layer when subscribing or unsubscribing from an event failed. This exception has only one level of Tango::DevError structure. The possible value for the reason field are :

API_NotificationServiceFailed
This error occurs when the subscribe_event() method failed trying to access the CORBA notification service

API_EventNotFound
This error occurs when you are using an incorrect event_id in the unsubscribe_event() method

API_InvalidArgs
This error occurs when NULL pointers are passed to the subscribe or unsubscribe event methods

API_MethodArgument
This error occurs when trying to subscribe to an event which has already been subsribed to

API_DSFailedRegisteringEvent
This error means that the device server to which the device belongs to failed when it tries to register the event. Most likely, it means that there is no event property defined

API_EventNotFound
Occurs when using a wrong event identifier in the unsubscribe_event method

exception tango.DeviceUnlocked(*args, **kwargs)¶

Bases:

This exception is thrown by the API layer when a device locked by the process has been unlocked by an admin client. This exception has two levels of Tango::DevError structure. There is only possible value for the reason field which is

API_DeviceUnlocked
The device has been unlocked by another client (administration client)

The first level is the message reported by the Tango kernel from the server side. The second layer is added by the client API layer with informations on which API call generates the exception and device name.

exception tango.NotAllowed(*args, **kwargs)¶: Bases:

exception tango.NamedDevFailedList(*args, **kwargs)¶

Bases:

This exception is only thrown by the DeviceProxy::write_attributes() method. In this case, it is necessary to have a new class of exception to transfer the error stack for several attribute(s) which failed during the writing. Therefore, this exception class contains for each attributes which failed :

The name of the attribute

Its index in the vector passed as argumen tof the write_attributes() method

The error stack

How to¶

This is a small list of how-tos specific to PyTango. A more general Tango how-to list can be found here.

How to contribute¶

Everyone is welcome to contribute to PyTango project. If you don’t feel comfortable with writing core PyTango we are looking for contributors to documentation or/and tests.

It refers to the next section, see How to Contribute.

Check the default TANGO host¶

The default TANGO host can be defined using the environment variable TANGO_HOST or in a tangorc file (see Tango environment variables for complete information)

To check what is the current value that TANGO uses for the default configuration simple do:

>>> import tango
>>> tango.ApiUtil.get_env_var("TANGO_HOST")
'homer.simpson.com:10000'

Check TANGO version¶

There are two library versions you might be interested in checking: The PyTango version:

>>> import tango
>>> tango.__version__
'9.3.3'
>>> tango.__version_info__
(9, 3, 3)

and the Tango C++ library version that PyTango was compiled with:

>>> import tango
>>> tango.constants.TgLibVers
'9.3.3'

Report a bug¶

Bugs can be reported as issues in PyTango Github.

It is also helpful if you can put in the issue description the PyTango information. It can be a dump of:

$ python -c "from tango.utils import info; print(info())"

Test the connection to the Device and get it’s current state¶

One of the most basic examples is to get a reference to a device and determine if it is running or not:

from tango import DeviceProxy

# Get proxy on the tango_test1 device
print("Creating proxy to TangoTest device...")
tango_test = DeviceProxy("sys/tg_test/1")

# ping it
print(tango_test.ping())

# get the state
print(tango_test.state())

Read and write attributes¶

Basic read/write attribute operations:

from tango import DeviceProxy

# Get proxy on the tango_test1 device
print("Creating proxy to TangoTest device...")
tango_test = DeviceProxy("sys/tg_test/1")

# Read a scalar attribute. This will return a tango.DeviceAttribute
# Member 'value' contains the attribute value
scalar = tango_test.read_attribute("long_scalar")
print("Long_scalar value = {0}".format(scalar.value))

# PyTango provides a shorter way:
scalar = tango_test.long_scalar
print("Long_scalar value = {0}".format(scalar))

# Read a spectrum attribute
spectrum = tango_test.read_attribute("double_spectrum")
# ... or, the shorter version:
spectrum = tango_test.double_spectrum

# Write a scalar attribute
scalar_value = 18
tango_test.write_attribute("long_scalar", scalar_value)

#  PyTango provides a shorter way:
tango_test.long_scalar = scalar_value

# Write a spectrum attribute
spectrum_value = [1.2, 3.2, 12.3]
tango_test.write_attribute("double_spectrum", spectrum_value)
# ... or, the shorter version:
tango_test.double_spectrum = spectrum_value

# Write an image attribute
image_value = [ [1, 2], [3, 4] ]
tango_test.write_attribute("long_image", image_value)
# ... or, the shorter version:
tango_test.long_image = image_value

Note that if PyTango is compiled with numpy support the values got when reading a spectrum or an image will be numpy arrays. This results in a faster and more memory efficient PyTango. You can also use numpy to specify the values when writing attributes, especially if you know the exact attribute type:

import numpy
from tango import DeviceProxy

# Get proxy on the tango_test1 device
print("Creating proxy to TangoTest device...")
tango_test = DeviceProxy("sys/tg_test/1")

data_1d_long = numpy.arange(0, 100, dtype=numpy.int32)

tango_test.long_spectrum = data_1d_long

data_2d_float = numpy.zeros((10,20), dtype=numpy.float64)

tango_test.double_image = data_2d_float

Execute commands¶

As you can see in the following example, when scalar types are used, the Tango binding automagically manages the data types, and writing scripts is quite easy:

from tango import DeviceProxy

# Get proxy on the tango_test1 device
print("Creating proxy to TangoTest device...")
tango_test = DeviceProxy("sys/tg_test/1")

# First use the classical command_inout way to execute the DevString command
# (DevString in this case is a command of the Tango_Test device)

result = tango_test.command_inout("DevString", "First hello to device")
print("Result of execution of DevString command = {0}".format(result))

# the same can be achieved with a helper method
result = tango_test.DevString("Second Hello to device")
print("Result of execution of DevString command = {0}".format(result))

# Please note that argin argument type is automatically managed by python
result = tango_test.DevULong(12456)
print("Result of execution of DevULong command = {0}".format(result))

Execute commands with more complex types¶

In this case you have to use put your arguments data in the correct python structures:

from tango import DeviceProxy

# Get proxy on the tango_test1 device
print("Creating proxy to TangoTest device...")
tango_test = DeviceProxy("sys/tg_test/1")

# The input argument is a DevVarLongStringArray so create the argin
# variable containing an array of longs and an array of strings
argin = ([1,2,3], ["Hello", "TangoTest device"])

result = tango_test.DevVarLongStringArray(argin)
print("Result of execution of DevVarLongArray command = {0}".format(result))

Work with Groups¶

Todo

write this how to

Handle errors¶

Todo

write this how to

For now check Exception API.

Registering devices¶

Here is how to define devices in the Tango DataBase:

from tango import Database, DbDevInfo

#  A reference on the DataBase
db = Database()

# The 3 devices name we want to create
# Note: these 3 devices will be served by the same DServer
new_device_name1 = "px1/tdl/mouse1"
new_device_name2 = "px1/tdl/mouse2"
new_device_name3 = "px1/tdl/mouse3"

# Define the Tango Class served by this  DServer
new_device_info_mouse = DbDevInfo()
new_device_info_mouse._class = "Mouse"
new_device_info_mouse.server = "ds_Mouse/server_mouse"

# add the first device
print("Creating device: %s" % new_device_name1)
new_device_info_mouse.name = new_device_name1
db.add_device(new_device_info_mouse)

# add the next device
print("Creating device: %s" % new_device_name2)
new_device_info_mouse.name = new_device_name2
db.add_device(new_device_info_mouse)

# add the third device
print("Creating device: %s" % new_device_name3)
new_device_info_mouse.name = new_device_name3
db.add_device(new_device_info_mouse)

Setting up device properties¶

A more complex example using python subtilities. The following python script example (containing some functions and instructions manipulating a Galil motor axis device server) gives an idea of how the Tango API should be accessed from Python:

from tango import DeviceProxy

# connecting to the motor axis device
axis1 = DeviceProxy("microxas/motorisation/galilbox")

# Getting Device Properties
property_names = ["AxisBoxAttachement",
                  "AxisEncoderType",
                  "AxisNumber",
                  "CurrentAcceleration",
                  "CurrentAccuracy",
                  "CurrentBacklash",
                  "CurrentDeceleration",
                  "CurrentDirection",
                  "CurrentMotionAccuracy",
                  "CurrentOvershoot",
                  "CurrentRetry",
                  "CurrentScale",
                  "CurrentSpeed",
                  "CurrentVelocity",
                  "EncoderMotorRatio",
                  "logging_level",
                  "logging_target",
                  "UserEncoderRatio",
                  "UserOffset"]

axis_properties = axis1.get_property(property_names)
for prop in axis_properties.keys():
    print("%s: %s" % (prop, axis_properties[prop][0]))

# Changing Properties
axis_properties["AxisBoxAttachement"] = ["microxas/motorisation/galilbox"]
axis_properties["AxisEncoderType"] = ["1"]
axis_properties["AxisNumber"] = ["6"]
axis1.put_property(axis_properties)

Using clients with multiprocessing¶

Since version 9.3.0 PyTango provides cleanup() which resets CORBA connection. This static function is needed when you want to use tango with multiprocessing in your client code.

In the case when both your parent process and your child process create DeviceProxy, Database or/and AttributeProxy your child process inherits the context from your parent process, i.e. open file descriptors, the TANGO and the CORBA state. Sharing the above objects between the processes may cause unpredictable errors, e.g. TRANSIENT_CallTimedout, unidentifiable C++ exception. Therefore, when you start a new process you must reset CORBA connection:

import time
import tango

from multiprocessing import Process


class Worker(Process):

    def __init__(self):
        Process.__init__(self)

    def run(self):
        # reset CORBA connection
        tango.ApiUtil.cleanup()

        proxy = tango.DeviceProxy('test/tserver/1')

        stime = time.time()
        etime = stime
        while etime - stime < 1.:
            try:
                proxy.read_attribute("Value")
            except Exception as e:
                print(str(e))
            etime = time.time()


def runworkers():
    workers = [Worker() for _ in range(6)]
    for wk in workers:
        wk.start()
    for wk in workers:
        wk.join()


db = tango.Database()
dp = tango.DeviceProxy('test/tserver/1')

for i in range(4):
    runworkers()

After cleanup() all references to DeviceProxy, AttributeProxy or Database objects in the current process become invalid and these objects need to be reconstructed.

Using clients with multithreading¶

When performing Tango I/O from user-created threads, there can be problems. This is often more noticeable with event subscription and unsubscription, but it could affect any Tango I/O. As PyTango wraps the cppTango library, we needs to consider how cppTango’s threads work.

cppTango was originally developed at a time where C++ didn’t have standard threads. All the threads currently created in cppTango are omni threads, since this is what the omniORB library is using to create threads and since this implementation is available for free with omniORB.

In C++, users used to create omni threads in the past so there was no issue. Since C++11, C++ comes with an implementation of standard threads. cppTango is currently (version 9.3.3) not directly thread safe when a user is using C++11 standard threads or threads different than omni threads. This lack of thread safety includes threads created from Python’s threading module.

In an ideal future cppTango should should protect itself, regardless of what type of threads are used. In the meantime, we need a work-around.

The work-around when using threads which are not omni threads is to create an object of the C++ class omni_thread::ensure_self in the user thread, just after the thread creation, and to delete this object only when the thread has finished its job. This omni_thread::ensure_self object provides a dummy omniORB ID for the thread. This ID is used when accessing thread locks within cppTango, so the ID must remain the same for the lifetime of the thread. Also note that this object MUST be released before the thread has exited, otherwise omniORB will throw an exception.

A Pythonic way to implement this work-around for multithreaded applications is available via the EnsureOmniThread class. It was added in PyTango version 9.3.2. This class is best used as a context handler to wrap the target method of the user thread. An example is shown below:

import tango
from threading import Thread
from time import sleep


def thread_task():
    with tango.EnsureOmniThread():
        eid = dp.subscribe_event(
            "double_scalar", tango.EventType.PERIODIC_EVENT, cb)
        while running:
            print("num events stored {}".format(len(cb.get_events())))
            sleep(1)
        dp.unsubscribe_event(eid)


cb = tango.utils.EventCallback()  # print events to stdout
dp = tango.DeviceProxy("sys/tg_test/1")
dp.poll_attribute("double_scalar", 1000)
thread = Thread(target=thread_task)
running = True
thread.start()
sleep(5)
running = False
thread.join()

Another way to create threads in Python is the concurrent.futures.ThreadPoolExecutor. The problem with this is that the API does not provide an easy way for the context handler to cover the lifetime of the threads, which are created as daemons. One option is to at least use the context handler for the functions that are submitted to the executor. I.e., executor.submit(thread_task). This is not guaranteed to work. A second option to investigate (if using at least Python 3.7) is the initializer argument which could be used to ensure a call to the __enter__() method for a thread-specific instance of EnsureOmniThread. However, calling the __exit__() method on the corresponding object at shutdown is a problem. Maybe it could be submitted as work.

Write a server¶

Before reading this chapter you should be aware of the TANGO basic concepts. This chapter does not explain what a Tango device or a device server is. This is explained in detail in the Tango control system manual

Since version 8.1, PyTango provides a helper module which simplifies the development of a Tango device server. This helper is provided through the tango.server module.

Here is a simple example on how to write a Clock device server using the high level API

 import time
 from tango.server import Device, attribute, command, pipe


 class Clock(Device):

     @attribute
     def time(self):
         return time.time()

     @command(dtype_in=str, dtype_out=str)
     def strftime(self, format):
         return time.strftime(format)

     @pipe
     def info(self):
         return ('Information',
                 dict(manufacturer='Tango',
                      model='PS2000',
                      version_number=123))


 if __name__ == "__main__":
     Clock.run_server()

line 2: import the necessary symbols
line 5: tango device class definition. A Tango device must inherit from tango.server.Device
line 7-9: definition of the time attribute. By default, attributes are double, scalar, read-only. Check the attribute for the complete list of attribute options.
line 11-13: the method strftime is exported as a Tango command. In receives a string as argument and it returns a string. If a method is to be exported as a Tango command, it must be decorated as such with the command() decorator
line 15-20: definition of the info pipe. Check the pipe for the complete list of pipe options.
line 24: start the Tango run loop. This method automatically determines the Python class name and exports it as a Tango class. For more complicated cases, check run() for the complete list of options

There is a more detailed clock device server in the examples/Clock folder.

Here is a more complete example on how to write a PowerSupply device server using the high level API. The example contains:

a read-only double scalar attribute called voltage
a read/write double scalar expert attribute current
a read-only double image attribute called noise
a ramp command
a host device property
a port class property

from time import time
from numpy.random import random_sample

from tango import AttrQuality, AttrWriteType, DispLevel
from tango.server import Device, attribute, command
from tango.server import class_property, device_property


class PowerSupply(Device):

    current = attribute(label="Current", dtype=float,
                        display_level=DispLevel.EXPERT,
                        access=AttrWriteType.READ_WRITE,
                        unit="A", format="8.4f",
                        min_value=0.0, max_value=8.5,
                        min_alarm=0.1, max_alarm=8.4,
                        min_warning=0.5, max_warning=8.0,
                        fget="get_current", fset="set_current",
                        doc="the power supply current")

    noise = attribute(label="Noise", dtype=((float,),),
                      max_dim_x=1024, max_dim_y=1024,
                      fget="get_noise")

    host = device_property(dtype=str)
    port = class_property(dtype=int, default_value=9788)

    @attribute
    def voltage(self):
        self.info_stream("get voltage(%s, %d)" % (self.host, self.port))
        return 10.0

    def get_current(self):
        return 2.3456, time(), AttrQuality.ATTR_WARNING

    def set_current(self, current):
        print("Current set to %f" % current)

    def get_noise(self):
        return random_sample((1024, 1024))

    @command(dtype_in=float)
    def ramp(self, value):
        print("Ramping up...")


if __name__ == "__main__":
    PowerSupply.run_server()

Server logging¶

This chapter instructs you on how to use the tango logging API (log4tango) to create tango log messages on your device server.

The logging system explained here is the Tango Logging Service (TLS). For detailed information on how this logging system works please check:

Usage

Property reference

The easiest way to start seeing log messages on your device server console is by starting it with the verbose option. Example:

python PyDsExp.py PyDs1 -v4

This activates the console tango logging target and filters messages with importance level DEBUG or more. The links above provided detailed information on how to configure log levels and log targets. In this document we will focus on how to write log messages on your device server.

Basic logging¶

The most basic way to write a log message on your device is to use the Device logging related methods:

debug_stream()

info_stream()

warn_stream()

error_stream()

fatal_stream()

Example:

def read_voltage(self):
    self.info_stream("read voltage attribute")
    # ...
    return voltage_value

This will print a message like:

1282206864 [-1215867200] INFO test/power_supply/1 read voltage attribute

every time a client asks to read the voltage attribute value.

The logging methods support argument list feature (since PyTango 8.1). Example:

def read_voltage(self):
    self.info_stream("read_voltage(%s, %d)", self.host, self.port)
    # ...
    return voltage_value

Logging with print statement¶

This feature is only possible since PyTango 7.1.3

It is possible to use the print statement to log messages into the tango logging system. This is achieved by using the python’s print extend form sometimes refered to as print chevron.

Same example as above, but now using print chevron:

def read_voltage(self, the_att):
    print >>self.log_info, "read voltage attribute"
    # ...
    return voltage_value

Or using the python 3k print function:

def read_Long_attr(self, the_att):
    print("read voltage attribute", file=self.log_info)
    # ...
    return voltage_value

Logging with decorators¶

This feature is only possible since PyTango 7.1.3

PyTango provides a set of decorators that place automatic log messages when you enter and when you leave a python method. For example:

@tango.DebugIt()
def read_Long_attr(self, the_att):
    the_att.set_value(self.attr_long)

will generate a pair of log messages each time a client asks for the ‘Long_attr’ value. Your output would look something like:

1282208997 [-1215965504] DEBUG test/pydsexp/1 -> read_Long_attr()
1282208997 [-1215965504] DEBUG test/pydsexp/1 <- read_Long_attr()

Decorators exist for all tango log levels:

The decorators receive three optional arguments:

show_args - shows method arguments in log message (defaults to False)
show_kwargs shows keyword method arguments in log message (defaults to False)
show_ret - shows return value in log message (defaults to False)

Example:

@tango.DebugIt(show_args=True, show_ret=True)
def IOLong(self, in_data):
    return in_data * 2

will output something like:

1282221947 [-1261438096] DEBUG test/pydsexp/1 -> IOLong(23)
1282221947 [-1261438096] DEBUG test/pydsexp/1 46 <- IOLong()

Multiple device classes (Python and C++) in a server¶

Within the same python interpreter, it is possible to mix several Tango classes. Let’s say two of your colleagues programmed two separate Tango classes in two separated python files: A PLC class in a PLC.py:

# PLC.py

from tango.server import Device

class PLC(Device):

    # bla, bla my PLC code

if __name__ == "__main__":
    PLC.run_server()

… and a IRMirror in a IRMirror.py:

# IRMirror.py

from tango.server import Device

class IRMirror(Device):

    # bla, bla my IRMirror code

if __name__ == "__main__":
    IRMirror.run_server()

You want to create a Tango server called PLCMirror that is able to contain devices from both PLC and IRMirror classes. All you have to do is write a PLCMirror.py containing the code:

# PLCMirror.py

from tango.server import run
from PLC import PLC
from IRMirror import IRMirror

run([PLC, IRMirror])

It is also possible to add C++ Tango class in a Python device server as soon as:

The Tango class is in a shared library
It exist a C function to create the Tango class

For a Tango class called MyTgClass, the shared library has to be called MyTgClass.so and has to be in a directory listed in the LD_LIBRARY_PATH environment variable. The C function creating the Tango class has to be called _create_MyTgClass_class() and has to take one parameter of type “char *” which is the Tango class name. Here is an example of the main function of the same device server than before but with one C++ Tango class called SerialLine:

import tango
import sys

if __name__ == '__main__':
    py = tango.Util(sys.argv)
    util.add_class('SerialLine', 'SerialLine', language="c++")
    util.add_class(PLCClass, PLC, 'PLC')
    util.add_class(IRMirrorClass, IRMirror, 'IRMirror')

    U = tango.Util.instance()
    U.server_init()
    U.server_run()

Line 6: The C++ class is registered in the device server
Line 7 and 8: The two Python classes are registered in the device server

Create attributes dynamically¶

It is also possible to create dynamic attributes within a Python device server. There are several ways to create dynamic attributes. One of the way, is to create all the devices within a loop, then to create the dynamic attributes and finally to make all the devices available for the external world. In C++ device server, this is typically done within the <Device>Class::device_factory() method. In Python device server, this method is generic and the user does not have one. Nevertheless, this generic device_factory method calls a method named dyn_attr() allowing the user to create his dynamic attributes. It is simply necessary to re-define this method within your <Device>Class and to create the dynamic attribute within this method:

dyn_attr(self, dev_list)

where dev_list is a list containing all the devices created by the generic device_factory() method.

There is another point to be noted regarding dynamic attribute within Python device server. The Tango Python device server core checks that for each attribute it exists methods named <attribute_name>_read and/or <attribute_name>_write and/or is_<attribute_name>_allowed. Using dynamic attribute, it is not possible to define these methods because attributes name and number are known only at run-time. To address this issue, the Device_3Impl::add_attribute() method has a diferent signature for Python device server which is:

add_attribute(self, attr, r_meth = None, w_meth = None, is_allo_meth = None)

attr is an instance of the Attr class, r_meth is the method which has to be executed with the attribute is read, w_meth is the method to be executed when the attribute is written and is_allo_meth is the method to be executed to implement the attribute state machine. The method passed here as argument as to be class method and not object method. Which argument you have to use depends on the type of the attribute (A WRITE attribute does not need a read method). Note, that depending on the number of argument you pass to this method, you may have to use Python keyword argument. The necessary methods required by the Tango Python device server core will be created automatically as a forward to the methods given as arguments.

Here is an example of a device which has a TANGO command called createFloatAttribute. When called, this command creates a new scalar floating point attribute with the specified name:

from tango import Util, Attr, AttrWriteType
from tango.server import Device, command

class MyDevice(Device):

    @command(dtype_in=str)
    def CreateFloatAttribute(self, attr_name):
        attr = Attr(attr_name, tango.DevDouble, AttrWriteType.READ_WRITE)
        self.add_attribute(attr, self.read_General, self.write_General)

    def read_General(self, attr):
        self.info_stream("Reading attribute %s", attr.get_name())
        attr.set_value(99.99)

    def write_General(self, attr):
        self.info_stream("Writting attribute %s", attr.get_name())

Create/Delete devices dynamically¶

This feature is only possible since PyTango 7.1.2

Starting from PyTango 7.1.2 it is possible to create devices in a device server “en caliente”. This means that you can create a command in your “management device” of a device server that creates devices of (possibly) several other tango classes. There are two ways to create a new device which are described below.

Tango imposes a limitation: the tango class(es) of the device(s) that is(are) to be created must have been registered before the server starts. If you use the high level API, the tango class(es) must be listed in the call to run(). If you use the lower level server API, it must be done using individual calls to add_class().

Dynamic device from a known tango class name¶

If you know the tango class name but you don’t have access to the tango.DeviceClass (or you are too lazy to search how to get it ;-) the way to do it is call create_device() / delete_device(). Here is an example of implementing a tango command on one of your devices that creates a device of some arbitrary class (the example assumes the tango commands ‘CreateDevice’ and ‘DeleteDevice’ receive a parameter of type DevVarStringArray with two strings. No error processing was done on the code for simplicity sake):

from tango import Util
from tango.server import Device, command

class MyDevice(Device):

    @command(dtype_in=[str])
    def CreateDevice(self, pars):
        klass_name, dev_name = pars
        util = Util.instance()
        util.create_device(klass_name, dev_name, alias=None, cb=None)

    @command(dtype_in=[str])
    def DeleteDevice(self, pars):
        klass_name, dev_name = pars
        util = Util.instance()
        util.delete_device(klass_name, dev_name)

An optional callback can be registered that will be executed after the device is registed in the tango database but before the actual device object is created and its init_device method is called. It can be used, for example, to initialize some device properties.

Dynamic device from a known tango class¶

If you already have access to the DeviceClass object that corresponds to the tango class of the device to be created you can call directly the create_device() / delete_device(). For example, if you wish to create a clone of your device, you can create a tango command called Clone:

class MyDevice(tango.Device):

    def fill_new_device_properties(self, dev_name):
        prop_names = db.get_device_property_list(self.get_name(), "*")
        prop_values = db.get_device_property(self.get_name(), prop_names.value_string)
        db.put_device_property(dev_name, prop_values)

        # do the same for attributes...
        ...

    def Clone(self, dev_name):
        klass = self.get_device_class()
        klass.create_device(dev_name, alias=None, cb=self.fill_new_device_properties)

    def DeleteSibling(self, dev_name):
        klass = self.get_device_class()
        klass.delete_device(dev_name)

Note that the cb parameter is optional. In the example it is given for demonstration purposes only.

Write a server (original API)¶

This chapter describes how to develop a PyTango device server using the original PyTango server API. This API mimics the C++ API and is considered low level. You should write a server using this API if you are using code generated by Pogo tool or if for some reason the high level API helper doesn’t provide a feature you need (in that case think of writing a mail to tango mailing list explaining what you cannot do).

The main part of a Python device server¶

The rule of this part of a Tango device server is to:

Create the Util object passing it the Python interpreter command line arguments

Add to this object the list of Tango class(es) which have to be hosted by this interpreter

Initialize the device server

Run the device server loop

The following is a typical code for this main function:

if __name__ == '__main__':
    util = tango.Util(sys.argv)
    util.add_class(PyDsExpClass, PyDsExp)

    U = tango.Util.instance()
    U.server_init()
    U.server_run()

Line 2: Create the Util object passing it the interpreter command line arguments
Line 3: Add the Tango class PyDsExp to the device server. The Util.add_class() method of the Util class has two arguments which are the Tango class PyDsExpClass instance and the Tango PyDsExp instance. This Util.add_class() method is only available since version 7.1.2. If you are using an older version please use Util.add_TgClass() instead.
Line 7: Initialize the Tango device server
Line 8: Run the device server loop

The PyDsExpClass class in Python¶

The rule of this class is to :

Host and manage data you have only once for the Tango class whatever devices of this class will be created

Define Tango class command(s)

Define Tango class attribute(s)

In our example, the code of this Python class looks like:

class PyDsExpClass(tango.DeviceClass):

    cmd_list = { 'IOLong' : [ [ tango.ArgType.DevLong, "Number" ],
                              [ tango.ArgType.DevLong, "Number * 2" ] ],
                 'IOStringArray' : [ [ tango.ArgType.DevVarStringArray, "Array of string" ],
                                     [ tango.ArgType.DevVarStringArray, "This reversed array"] ],
    }

    attr_list = { 'Long_attr' : [ [ tango.ArgType.DevLong ,
                                    tango.AttrDataFormat.SCALAR ,
                                    tango.AttrWriteType.READ],
                                  { 'min alarm' : 1000, 'max alarm' : 1500 } ],

                 'Short_attr_rw' : [ [ tango.ArgType.DevShort,
                                       tango.AttrDataFormat.SCALAR,
                                       tango.AttrWriteType.READ_WRITE ] ]
    }

Line 1: The PyDsExpClass class has to inherit from the DeviceClass class
Line 3 to 7: Definition of the cmd_list dict defining commands. The IOLong command is defined at lines 3 and 4. The IOStringArray command is defined in lines 5 and 6
Line 9 to 17: Definition of the attr_list dict defining attributes. The Long_attr attribute is defined at lines 9 to 12 and the Short_attr_rw attribute is defined at lines 14 to 16

If you have something specific to do in the class constructor like initializing some specific data member, you will have to code a class constructor. An example of such a contructor is

def __init__(self, name):
    tango.DeviceClass.__init__(self, name)
    self.set_type("TestDevice")

The device type is set at line 3.

Defining commands¶

As shown in the previous example, commands have to be defined in a dict called cmd_list as a data member of the xxxClass class of the Tango class. This dict has one element per command. The element key is the command name. The element value is a python list which defines the command. The generic form of a command definition is:

'cmd_name' : [ [in_type, <"In desc">], [out_type, <"Out desc">], <{opt parameters}>]

The first element of the value list is itself a list with the command input data type (one of the tango.ArgType pseudo enumeration value) and optionally a string describing this input argument. The second element of the value list is also a list with the command output data type (one of the tango.ArgType pseudo enumeration value) and optionaly a string describing it. These two elements are mandatory. The third list element is optional and allows additional command definition. The authorized element for this dict are summarized in the following array:

key

Value

Definition

“display level”

DispLevel enum value

The command display level

“polling period”

Any number

The command polling period (mS)

“default command”

True or False

To define that it is the default command

Defining attributes¶

As shown in the previous example, attributes have to be defined in a dict called attr_list as a data member of the xxxClass class of the Tango class. This dict has one element per attribute. The element key is the attribute name. The element value is a python list which defines the attribute. The generic form of an attribute definition is:

'attr_name' : [ [mandatory parameters], <{opt parameters}>]

For any kind of attributes, the mandatory parameters are:

[attr data type, attr data format, attr data R/W type]

The attribute data type is one of the possible value for attributes of the tango.ArgType pseudo enunmeration. The attribute data format is one of the possible value of the tango.AttrDataFormat pseudo enumeration and the attribute R/W type is one of the possible value of the tango.AttrWriteType pseudo enumeration. For spectrum attribute, you have to add the maximum X size (a number). For image attribute, you have to add the maximun X and Y dimension (two numbers). The authorized elements for the dict defining optional parameters are summarized in the following array:

key

value

definition

“display level”

tango.DispLevel enum value

The attribute display level

“polling period”

Any number

The attribute polling period (mS)

“memorized”

“true” or “true_without_hard_applied”

Define if and how the att. is memorized

“label”

A string

The attribute label

“description”

A string

The attribute description

“unit”

A string

The attribute unit

“standard unit”

A number

The attribute standard unit

“display unit”

A string

The attribute display unit

“format”

A string

The attribute display format

“max value”

A number

The attribute max value

“min value”

A number

The attribute min value

“max alarm”

A number

The attribute max alarm

“min alarm”

A number

The attribute min alarm

“min warning”

A number

The attribute min warning

“max warning”

A number

The attribute max warning

“delta time”

A number

The attribute RDS alarm delta time

“delta val”

A number

The attribute RDS alarm delta val

The PyDsExp class in Python¶

The rule of this class is to implement methods executed by commands and attributes. In our example, the code of this class looks like:

class PyDsExp(tango.Device):

    def __init__(self,cl,name):
        tango.Device.__init__(self, cl, name)
        self.info_stream('In PyDsExp.__init__')
        PyDsExp.init_device(self)

    def init_device(self):
        self.info_stream('In Python init_device method')
        self.set_state(tango.DevState.ON)
        self.attr_short_rw = 66
        self.attr_long = 1246

    #------------------------------------------------------------------

    def delete_device(self):
        self.info_stream('PyDsExp.delete_device')

    #------------------------------------------------------------------
    # COMMANDS
    #------------------------------------------------------------------

    def is_IOLong_allowed(self):
        return self.get_state() == tango.DevState.ON

    def IOLong(self, in_data):
        self.info_stream('IOLong', in_data)
        in_data = in_data * 2
        self.info_stream('IOLong returns', in_data)
        return in_data

    #------------------------------------------------------------------

    def is_IOStringArray_allowed(self):
        return self.get_state() == tango.DevState.ON

    def IOStringArray(self, in_data):
        l = range(len(in_data)-1, -1, -1)
        out_index=0
        out_data=[]
        for i in l:
            self.info_stream('IOStringArray <-', in_data[out_index])
            out_data.append(in_data[i])
            self.info_stream('IOStringArray ->',out_data[out_index])
            out_index += 1
        self.y = out_data
        return out_data

    #------------------------------------------------------------------
    # ATTRIBUTES
    #------------------------------------------------------------------

    def read_attr_hardware(self, data):
        self.info_stream('In read_attr_hardware')

    def read_Long_attr(self, the_att):
        self.info_stream("read_Long_attr")

        the_att.set_value(self.attr_long)

    def is_Long_attr_allowed(self, req_type):
        return self.get_state() in (tango.DevState.ON,)

    def read_Short_attr_rw(self, the_att):
        self.info_stream("read_Short_attr_rw")

        the_att.set_value(self.attr_short_rw)

    def write_Short_attr_rw(self, the_att):
        self.info_stream("write_Short_attr_rw")

        self.attr_short_rw = the_att.get_write_value()

    def is_Short_attr_rw_allowed(self, req_type):
        return self.get_state() in (tango.DevState.ON,)

Line 1: The PyDsExp class has to inherit from the tango.Device (this will used the latest device implementation class available, e.g. Device_5Impl)
Line 3 to 6: PyDsExp class constructor. Note that at line 6, it calls the init_device() method
Line 8 to 12: The init_device() method. It sets the device state (line 9) and initialises some data members
Line 16 to 17: The delete_device() method. This method is not mandatory. You define it only if you have to do something specific before the device is destroyed
Line 23 to 30: The two methods for the IOLong command. The first method is called is_IOLong_allowed() and it is the command is_allowed method (line 23 to 24). The second method has the same name than the command name. It is the method which executes the command. The command input data type is a Tango long and therefore, this method receives a python integer.
Line 34 to 47: The two methods for the IOStringArray command. The first method is its is_allowed method (Line 34 to 35). The second one is the command execution method (Line 37 to 47). The command input data type is a string array. Therefore, the method receives the array in a python list of python strings.
Line 53 to 54: The read_attr_hardware() method. Its argument is a Python sequence of Python integer.
Line 56 to 59: The method executed when the Long_attr attribute is read. Note that before PyTango 7 it sets the attribute value with the tango.set_attribute_value function. Now the same can be done using the set_value of the attribute object
Line 61 to 62: The is_allowed method for the Long_attr attribute. This is an optional method that is called when the attribute is read or written. Not defining it has the same effect as always returning True. The parameter req_type is of type AttReqtype which tells if the method is called due to a read or write request. Since this is a read-only attribute, the method will only be called for read requests, obviously.
Line 64 to 67: The method executed when the Short_attr_rw attribute is read.
Line 69 to 72: The method executed when the Short_attr_rw attribute is written. Note that before PyTango 7 it gets the attribute value with a call to the Attribute method get_write_value with a list as argument. Now the write value can be obtained as the return value of the get_write_value call. And in case it is a scalar there is no more the need to extract it from the list.
Line 74 to 75: The is_allowed method for the Short_attr_rw attribute. This is an optional method that is called when the attribute is read or written. Not defining it has the same effect as always returning True. The parameter req_type is of type AttReqtype which tells if the method is called due to a read or write request.

General methods¶

The following array summarizes how the general methods we have in a Tango device server are implemented in Python.

Name	Input par (with “self”)	return value	mandatory
init_device	None	None	Yes
delete_device	None	None	No
always_executed_hook	None	None	No
signal_handler	`int`	None	No
read_attr_hardware	sequence<`int`>	None	No

Implementing a command¶

Commands are defined as described above. Nevertheless, some methods implementing them have to be written. These methods names are fixed and depend on command name. They have to be called:

is_<Cmd_name>_allowed(self)

<Cmd_name>(self, arg)

For instance, with a command called MyCmd, its is_allowed method has to be called is_MyCmd_allowed and its execution method has to be called simply MyCmd. The following array gives some more info on these methods.

Name	Input par (with “self”)	return value	mandatory
is_<Cmd_name>_allowed	None	Python boolean	No
Cmd_name	Depends on cmd type	Depends on cmd type	Yes

Please check Data types chapter to understand the data types that can be used in command parameters and return values.

The following code is an example of how you write code executed when a client calls a command named IOLong:

def is_IOLong_allowed(self):
    self.debug_stream("in is_IOLong_allowed")
    return self.get_state() == tango.DevState.ON

def IOLong(self, in_data):
    self.info_stream('IOLong', in_data)
    in_data = in_data * 2
    self.info_stream('IOLong returns', in_data)
    return in_data

Line 1-3: the is_IOLong_allowed method determines in which conditions the command ‘IOLong’ can be executed. In this case, the command can only be executed if the device is in ‘ON’ state.
Line 6: write a log message to the tango INFO stream (click here for more information about PyTango log system).
Line 7: does something with the input parameter
Line 8: write another log message to the tango INFO stream (click here for more information about PyTango log system).
Line 9: return the output of executing the tango command

Implementing an attribute¶

Attributes are defined as described in chapter 5.3.2. Nevertheless, some methods implementing them have to be written. These methods names are fixed and depend on attribute name. They have to be called:

is_<Attr_name>_allowed(self, req_type)

read_<Attr_name>(self, attr)

write_<Attr_name>(self, attr)

For instance, with an attribute called MyAttr, its is_allowed method has to be called is_MyAttr_allowed, its read method has to be called read_MyAttr and its write method has to be called write_MyAttr. The attr parameter is an instance of Attr. Unlike the commands, the is_allowed method for attributes receives a parameter of type AttReqtype.

Please check Data types chapter to understand the data types that can be used in attribute.

The following code is an example of how you write code executed when a client read an attribute which is called Long_attr:

def read_Long_attr(self, the_att):
    self.info_stream("read attribute name Long_attr")
    the_att.set_value(self.attr_long)

Line 1: Method declaration with “the_att” being an instance of the Attribute class representing the Long_attr attribute
Line 2: write a log message to the tango INFO stream (click here for more information about PyTango log system).
Line 3: Set the attribute value using the method set_value() with the attribute value as parameter.

The following code is an example of how you write code executed when a client write the Short_attr_rw attribute:

def write_Short_attr_rw(self,the_att):
    self.info_stream("In write_Short_attr_rw for attribute ",the_att.get_name())
    self.attr_short_rw = the_att.get_write_value(data)

Line 1: Method declaration with “the_att” being an instance of the Attribute class representing the Short_attr_rw attribute
Line 2: write a log message to the tango INFO stream (click here for more information about PyTango log system).
Line 3: Get the value sent by the client using the method get_write_value() and store the value written in the device object. Our attribute is a scalar short attribute so the return value is an int

How to Contribute¶

Everyone is welcome to contribute to PyTango project. If you don’t feel comfortable with writing core PyTango we are looking for contributors to documentation or/and tests.

Workflow¶

A normal Git workflow is used. You can find how to automate your git branching workflow example. Good practices:

There is no special policy regarding commit messages. They should be short (50 chars or less) and contain summary of all changes,
A CONTRIBUTING file is required,
Pull requests should be ALWAYS made to develop branch, not to a master branch.

reStructuredText and Sphinx¶

Documentation is written in reStructuredText and built with Sphinx - it’s easy to contribute. It also uses autodoc importing docstrings from tango package. Theme is not important, a theme prepared for Tango Community can be also used.

To test the docs locally requires Python >= 3.5:

$ python -m pip install sphinx sphinx_rtd_theme
$ python setup.py build_doc

To test the docs locally in a Sphinx Docker container:

(host) $ cd /path/to/pytango
(host) $ docker run --rm -ti -v $PWD:/docs sphinxdoc/sphinx bash
(container) $ python -m pip install six numpy sphinx_rtd_theme
(container) $ python -m sphinx doc build/sphinx

After building, open the build/doc/index.html page in your browser.

Source code standard¶

All code should be PEP8 compatible. We have set up checking code quality with Codacy which uses PyLint under the hood. You can see how well your code is rated on your PR’s page.

Note

The accepted policy is that your code cannot introduce more issues than it solves!

You can also use other tools for checking PEP8 compliance for your personal use. One good example of such a tool is Flake8 which combines PEP8 and PyFlakes. There are plugins for various IDEs so that you can use your favourite tool easily.

Using Docker for development¶

Docker containers are useful for developing, testing and debugging PyTango. See the folder .devcontainer in the root of the source repo. It includes instructions for building the Docker images and using them for development.

For direct usage, rather than PyTango developement, a Docker image with PyTango already installed is available: https://hub.docker.com/r/tangocs/tango-pytango.

Releasing a new version¶

From time to time a new version should be released. Anyone who wishes to see some features of the development branch released is free to make a new release. The basic steps required are as follows:

Pick a version number

Semantic version numbering is used: <major>.<minor>.<patch>
The major and minor version fields (9.3) track the TANGO C++ core version.
Small changes are done as patch releases. For these the version number should correspond the current development number since each release process finishes with a version bump.
Patch release example:
- 9.3.3.devN or 9.3.3aN or 9.3.3bN (current development branch)
- changes to 9.3.3 (the actual release)
- changes to 9.3.4.dev0 (bump the patch version at the end of the release process)

Create an issue in Github

This is to inform the community that a release is planned.
Use a checklist similar to the one below:

Task list:

- [ ] Read steps in the how-to-contribute docs for making a release

- [ ] Pull request to update changelog and bump version

- [ ] Merge PR (this is the last PR for the release)

- [ ] Merge develop into stable

- [ ] Make sure Travis and Appveyor are OK on stable branch

- [ ] Make sure the documentation is updated for stable (readthedocs)

- [ ] Create an annotated tag from stable branch

- [ ] Make sure the documentation is updated for release (readthedocs)

- [ ] Upload the new version to PyPI

- [ ] Bump the version with “-dev” in the develop branch

- [ ] Create and fill in the release description on GitHub

- [ ] Build conda packages

- [ ] Advertise the release on the mailing list

- [ ] Close this issue
A check list in this form on github can be ticked off as the work progresses.

Make a branch from develop to prepare the release

Example branch name: prepare-v9.3.3.
Edit the changelog (in docs/revision.rst). Include all pull requests since the version was bumped after the previous release.
Bump the versions (tango/release.py and appveyor.yml). E.g. version_info = (9, 3, 3), and version: 9.3.3.{build}
Create a pull request to get these changes reviewed before proceeding.

Merge stable into develop

Wait until the preparation branch pull request has been merged.
Merge stable into the latest develop. It is recommended to do a fast-forward merge in order to avoid a confusing merge commit. This can be done by simply pushing develop to stable using this command:

$ git push origin develop:stable

This way the release tag corresponds to the actual release commit both on the stable and develop branches.
In general, the stable branch should point to the latest release.

Make sure Travis and AppVeyor are OK on stable branch

On Travis, all tests, on all versions of Python must be passing. If not, bad luck - you’ll have to fix it first, and go back a few steps…
On AppVeyor, all builds, on all versions of Python must be passing. If not, bad luck - you’ll have to fix it first, and go back a few steps…

Make sure the documentation is updated

Log in to https://readthedocs.org.
Get account permissions for https://readthedocs.org/projects/pytango from another contributor, if necessary.
Readthedocs should automatically build the docs for each:
- push to develop (latest docs)
- push to stable (stable docs)
- new tags (e.g v9.3.3)
But, the webhooks are somehow broken, so it probably won’t work automatically!
- Trigger the builds manually here: https://readthedocs.org/projects/pytango/builds/
- Set the new version to “active” here: https://readthedocs.org/dashboard/pytango/versions/

Create an annotated tag for the release

Note: Github’s release page makes lightweight tags which we don’t want
Create tag:
- $ git checkout stable
- $ git pull
- $ git tag -a -m "tag v9.3.3" v9.3.3
- $ git push -v origin refs/tags/v9.3.3

Upload the new version to PyPI

Log in to https://pypi.org.
Get account permissions for PyTango from another contributor, if necessary.
If necessary, pip install twine: https://pypi.org/project/twine/)
Build release from the tagged commit:
- $ git clean -xfd # Warning - remove all non-versioned files and directories
- $ git fetch
- $ git checkout v9.3.3
- $ python setup.py sdist
Optional: Upload to https://test.pypi.org, and make sure all is well:
- $ twine upload -r testpypi dist/pytango-9.3.3.tar.gz
Optional: Test installation (in a virtualenv):
- $ pip install -i https://test.pypi.org/simple/ pytango
Upload the source tarball to the real PyPI:
- $ twine upload dist/pytango-9.3.3.tar.gz
Run build for the tag on AppVeyor, download artifacts, and upload wheels:
- $ twine upload dist/pytango-9.3.3-cp27-cp27m-win32.whl
- $ twine upload dist/pytango-9.3.3-cp27-cp27m-win_amd64.whl
- $ twine upload dist/pytango-9.3.3-cp36-cp36m-win32.whl
- $ twine upload dist/pytango-9.3.3-cp36-cp36m-win_amd64.whl
- $ twine upload dist/pytango-9.3.3-cp37-cp37m-win32.whl
- $ twine upload dist/pytango-9.3.3-cp37-cp37m-win_amd64.whl

Bump the version with “-dev” in the develop branch

Make branch like bump-dev-version from head of develop.
Change all references to next version and next + 1. E.g. if releasing v9.3.3, then update v9.3.4 to v9.3.5 and v9.3.3 to v9.3.4.
This includes files like README.rst, doc/howto.rst, doc/start.rst, doc/how-to-contribute.rst.
In tango/release.py, change version_info, e.g. from (9, 3, 3) to (9, 3, 4, 'dev', 0).
In appveyor.yml, change version, e.g. from 9.3.3.{build} to 9.3.4.dev0.{build}.
Create PR, merge to develop.

Create and fill in the release description on GitHub

Go to the Tags page: https://github.com/tango-controls/pytango/tags
Find the tag created above and click “Create release”.
Content must be the same as the details in the changelog. List all the pull requests since the previous version.

Build conda packages

This is tricky, so ask a contributor from the ESRF to do it.

Advertise the release on the mailing list

Post on the Python development list.
Example of a previous post: http://www.tango-controls.org/community/forum/c/development/python/pytango-921-release/

Close off release issue

All the items on the check list should be ticked off by now.
Close the issue.

Testing PyTango Devices¶

Provide a context to run a device without a database.

Approaches to testing Tango devices¶

Overview¶

The follow sections detail different approaches that can be used when automating tests. This includes starting the real devices as normal in a Tango facility, using the DeviceTestContext for a more lightweight test, a hybrid approach mixing DeviceTestContext and real Tango devices in a Tango facility, and starting multiple devices with the DeviceTestContext and MultiDeviceTestContext.

Testing a single device without DeviceTestContext¶

Note

This approach is not recommended for unit testing.

Testing without a DeviceTestContext requires a complete Tango environment to be running (this environment is orchestrated by Makefiles and Docker containers in our Tango Example repo). That is, the following four components/processes should be present and configured:

DSConfig tool

Tango Databaseds Server

MySQL/MariaDB

Tango Device Server (with Tango device under test inside it)

In order to successfully constitute a working Tango environment, the following sequence of operations is required:

A running MySQL/MariaDB service.

The Tango Databaseds Server configured to connect to the database.

The DSConfig tool can be run to bootstrap the database configuration of the Tango Device based on configuration from a file.

The Tango Device Server that has been initialised and running the Tango Device.

In the test, you can instantiate a PyTango DeviceProxy object to interact with the Tango device under test.

This is a lot of infrastructure and complicated to orchestrate - it is not conducive to lightweight, fast running unit tests. Thus it is not recommended.

_images/testing-approaches-real-facility.png

Figure 1. A schematic diagram showing the agents involved when testing a Tango device using the real Tango database and their interactions.

Examples:

test_2_test_server_using_client.py

test_3_test_motor_server.py

test_4_test_event_receiver_server.py

Testing a single device with DeviceTestContext¶

A utility class is provided by PyTango that aids in testing Tango Devices. It automates a lot of the operations required to start up a Tango runtime environment.:

from tango.test_context import DeviceTestContext

The DeviceTestContext accepts a Tango Device Python class, as an argument, that will be under test (PowerSupply). It also accepts some additional arguments such as properties - see the method signature of DeviceTestContext constructor. It will then do the following: Generate stubbed data file that has the minimum configuration details for a Tango Device Server to initialise the Tango Device under test (PowerSupply). It will start the Tango Device Server that contains the Tango Device (in a separate thread by default, but optionally in a subprocess). DServer is a “meta” Tango Device that provides an administrative interface to control all the devices in the Tango Device Server process. The DeviceProxy object can be retrieved from the DeviceContext and can be invoked to interact with Tango Device under test. A DeviceProxy object will expose all the attributes and commands specified for the Tango Device as Python objects, but invoking them will communicate with the real device via CORBA. If events are used, these are transported via ZeroMQ.

_images/testing-approaches-device-test-context.png

Figure 2. A schematic diagram showing the agents involved when testing a Tango device using the DeviceTestContext and their interactions.

You may now proceed to exercise the Tango Device’s interface by invoking the appropriate methods/properties on the proxy:

Example Code Snippet	Tango Concept	Description
`powersupply_proxy.turn_on()`	Tango Command	An action that the Tango Device performs.
`powersupply_proxy.voltage`	Tango Attribute	A value that the Tango Device exposes.

Example:

test_1_server_in_devicetestcontext.py

Testing a single device with DeviceTestContext combined with a real device(s) using the Tango database¶

This use case first requires the whole test infrastructure described in use case 1 above to be up before the tests can be run against the device (DishLeafNode) in the DeviceTestContext. The following sequence of events occur to run rests against the device (DishLeafNode):

Set up the test infrastructure for the real device - DishMaster (all the steps defined for use case 1 above apply).

Set up the test infrastructure for the device (DishLeafNode) in the DeviceTestContext (all steps in use case 2 above apply).

Create a proxy (dish_proxy) which exposes the attributes and commands of the real device to be tested.

There’s a proxy in the provisioned DeviceTestContext which knows about the real device but cannot expose its attributes and commands in that context, hence the need for the dish_proxy.

Figure 3. A schematic diagram showing the agents involved when testing multiple Tango devices using the DeviceTestContext together with the real Tango database and their interactions.

Examples:

DishLeafNode/conftest.py

Testing with multiple DeviceTestContexts¶

Note

This approach is not recommended - rather use MultiDeviceTestContext.

The testing scenario depicted in Figure 3 can be implemented without using the real Tango database. In this use case, the underlying device (DishMaster) is provisioned using the DeviceTestContext. Just like in the use case above, another proxy (dish_proxy) is created to expose the commands and attributes of the DishMaster Device. The sequence of events which take place to provision each of these DeviceTestContexts are exactly the same as described in use case 1. This is not recommended because it can be done more easily using the MultiDeviceTestContext, as shown in the next section.

_images/testing-approaches-device-test-context-x2.png

Figure 4. A schematic diagram showing the agents involved when testing multiple Tango devices using the DeviceTestContext and their interactions.

Examples:

Tango forum post

Testing with MultiDeviceTestContext¶

There is another testing class available in PyTango: MultiDeviceTestContext, which helps to simplify testing of multiple devices. In this case the multiple devices are all launched in a single device server.:

from tango.test_context import MultiDeviceTestContext

The testing scenario depicted in Figure 4 can be implemented with just a single MultiDeviceTestContext instead of two DeviceTestContext instances (and still without using the real Tango database). In this use case, both devices (DishMaster and DishLeafNode) are provisioned using the MultiDeviceTestContext. Just like in the use case above, another proxy (dish_proxy) is created to expose the commands and attributes of the DishMaster Device to the test runner. The sequence of events which take place to provision this MultiDeviceTestContexts is similar that use case 1. The main difference is the devices_info the must be specified beforehand. Here we can define the devices that must be started, their names, and initial properties.

_images/testing-approaches-multi-device-test-context.png

Figure 5. A schematic diagram showing the agents involved when testing multiple Tango devices using the MultiDeviceTestContext and their interactions.

Examples:

MultiDeviceTestContext with fixtures

Issues¶

The DeviceTestContext is quite a heavyweight utility class in terms of the dependent components it needs to orchestrate so that testing can be done. It requires the Tango runtime, including ZeroMQ for events, and a Database stub file as a minimum.

A single process that uses a DeviceTestContext more than once in threaded mode (so not a subprocess, with kwarg process=True), will get a segmentation fault. With process=True, we cannot access the internals of the class under test from the test runner - we have to use the Tango API via a DeviceProxy.

Forwarded attributes do not work.

There is no way to unit test (in the strict definition), since the Tango device objects cannot be directly instantiated.

Acknowledgement¶

Initial content for this page contributed by the Square Kilometre Array.

Device Test Context Classes API¶

The API of the testing classes are described here. For an overview of their behaviour, see Approaches to testing Tango devices.

DeviceTestContext¶

class tango.test_context.DeviceTestContext(device, device_cls=None, server_name=None, instance_name=None, device_name=None, properties=None, db=None, host=None, port=0, debug=3, process=False, daemon=False, timeout=None, memorized=None)¶

Bases: tango.test_context.MultiDeviceTestContext

Context to run a single device without a database.

The difference with respect to MultiDeviceTestContext is that it only allows to export a single device.

Example usage:

from time import sleep

from tango.server import Device, attribute, command
from tango.test_context import DeviceTestContext

class PowerSupply(Device):

    @attribute(dtype=float)
    def voltage(self):
        return 1.23

    @command
    def calibrate(self):
        sleep(0.1)

def test_calibrate():
    '''Test device calibration and voltage reading.'''
    with DeviceTestContext(PowerSupply, process=True) as proxy:
        proxy.calibrate()
        assert proxy.voltage == 1.23

Parameters

device (Device or DeviceImpl) – Device class to be run.
device_cls – The device class can be provided if using the low-level API. Optional. Not required for high-level API devices, of type Device.

append_db_file(server, instance, tangoclass, device_prop_info)¶: Generate a database file corresponding to the given arguments.

delete_db()¶: delete temporary database file only if it was created by this class

get_device(device_name)¶

Return the device proxy corresponding to the given device name.

Maintains previously accessed device proxies in a cache to not recreate then on every access.

get_device_access(device_name=None)¶: Return the full device name.

get_server_access()¶: Return the full server name.

start()¶: Run the server.

stop()¶: Kill the server.

MultiDeviceTestContext¶

class tango.test_context.MultiDeviceTestContext(devices_info, server_name=None, instance_name=None, db=None, host=None, port=0, debug=3, process=False, daemon=False, timeout=None)¶

Bases: object

Context to run device(s) without a database.

The difference with respect to DeviceTestContext is that it allows to export multiple devices (even of different Tango classes).

Example usage:

from tango.server import Device, attribute
from tango.test_context import MultiDeviceTestContext


class Device1(Device):

    @attribute
    def attr1(self):
        return 1.0


class Device2(Device):

    @attribute
    def read_attr2(self):
        return 2.0


devices_info = (
    {
        "class": Device1,
        "devices": [
            {
                "name": "test/device1/1"
            },
        ]
    },
    {
        "class": Device2,
        "devices": [
            {
                "name": "test/device2/1",
            },
        ]
    }
)

def test_devices():
    with MultiDeviceTestContext(devices_info, process=True) as context:
        proxy1 = context.get_device("test/device1/1")
        proxy2 = context.get_device("test/device2/1")
        assert proxy1.attr1 == 1.0
        assert proxy2.attr2 == 2.0

Parameters

devices_info (sequence<dict>) –
a sequence of dicts with information about devices to be exported. Each dict consists of the following keys:
- ”class” which value is either of:
  - : class:~tango.server.Device or the name of some such class
  - a sequence of two elements, the first element being a DeviceClass or the name of some such class, the second element being a DeviceImpl or the name of such such class
- ”devices” which value is a sequence of dicts with the following keys:
  - ”name” (str)
  - ”properties” (dict)
  - ”memorized” (dict)
server_name (str) – Name to use for the device server. Optional. Default is the first device’s class name.
instance_name (str) – Name to use for the device server instance. Optional. Default is lower-case version of the server name.
db (str) – Path to a pre-populated text file to use for the database. Optional. Default is to create a new temporary file and populate it based on the devices and properties supplied in devices_info.
host (str) – Hostname to use for device server’s ORB endpoint. Optional. Default is a local IP address.
port (int) – Port number to use for the device server’s ORB endpoint. Optional. Default is chosen by omniORB.
debug (int) – Debug level for the device server logging. 0=OFF, 1=FATAL, 2=ERROR, 3=WARN, 4=INFO, 5=DEBUG. Optional. Default is warn.
process (bool) – True if the device server should be launched in a new process, otherwise use a new thread. Note: if the context will be used mutiple times, it may seg fault if the thread mode is chosen. Optional. Default is thread.
daemon (bool) – True if the new thread/process must be created in daemon mode. Optional. Default is not daemon.
timeout (float) – How long to wait (seconds) for the device server to start up, and also how long to wait on joining the thread/process when stopping. Optional. Default differs for thread and process modes.

append_db_file(server, instance, tangoclass, device_prop_info)¶: Generate a database file corresponding to the given arguments.

delete_db()¶: delete temporary database file only if it was created by this class

get_device(device_name)¶

Return the device proxy corresponding to the given device name.

Maintains previously accessed device proxies in a cache to not recreate then on every access.

get_device_access(device_name)¶: Return the full device name.

get_server_access()¶: Return the full server name.

start()¶: Run the server.

stop()¶: Kill the server.

Mocking clients for Testing¶

Test Doubles: The idea behind mocking Tango entities¶

Suppose we want to test a Tango Device, Device A. In particular, we want to assert that when a certain action is invoked on Device A, it should produce an expected result. This will prove to us that Device A ‘s implementation sufficiently manifests the behaviour we would like it to have.

Now suppose Device A depends on Device B to complete its action. In other words, the result will depend, in part, on the state of Device B. This means that to test this scenario, both devices need to be in a base state that we control.

This might be difficult to achieve when using real devices since it might require a lot of orchestration and manipulation of details irrelevant to the test scenario, i.e. to get Device B into the required state.

A Test Double is a component that can act as a real device but is easier to manipulate and configure into the states that we want during testing. This means that we can replace Device B with its Test Double as long as it conforms to the interface that Device A expects.

What’s more, we can manipulate the Test Double to respond in the way we expect Device B to respond under the various conditions we want to test. A Mock is simply a type of Test Double that might have some conditional logic or behaviour to help in testing.

Tango’s DeviceProxys¶

In Tango, the DeviceProxy is an object that allows communication between devices. It can be regarded as the client part of a client-server interaction.

Thus, any Tango device (say, Device A) that depends on a secondary Tango device (Device B) will need to use a DeviceProxy to connect and communicate with the secondary device (Device B).

This invariably means that in the implementation of Device A, it will be instantiating and using a DeviceProxy object.

However, the mechanism by which this happens is a multi-step process which requires communication with a TangoDB DS and an appropriately configured Tango system that contains a deployed Device B.

If we can replace the DeviceProxy object that Device A will use to communicate to Device B with our own Mock object (DeviceProxyMock), we can test the behaviour of Device A while faking the responses it expects to receive from querying Device B. All this without the need for deploying a real Device B, since for all intents and purposes, the DeviceProxyMock would represent the real device.

_images/mocking-tango-db-access-crossed-out.png

In other words, mocking the DeviceProxy is sufficient to mock the underlying device it connects to, with reference to how DeviceProxy is used by Device A.

Mocking the DeviceProxy¶

In some PyTango devices, such as those in the SKA TMC Prototype, the DeviceProxy object is instantiated during the operation of the Device Under Test (DUT). Also, there isn’t usually an explicit interface to inject a DeviceProxyMock as a replacement for the real class.

As an example, the CentralNode (at v0.1.8) device from the TMC Prototype instantiates all the DeviceProxy objects it needs to connect to its child elements/components in its init_device method:

class CentralNode(SKABaseDevice):
...
  def init_device(self):
    ...
    self._leaf_device_proxy.append(DeviceProxy(self._dish_leaf_node_devices[name]))
    ...
    self._csp_master_leaf_proxy = DeviceProxy(self.CspMasterLeafNodeFQDN)
    ...
    self._sdp_master_leaf_proxy = DeviceProxy(self.SdpMasterLeafNodeFQDN)
    ...
    subarray_proxy = DeviceProxy(self.TMMidSubarrayNodes[subarray])

Unfortunately, the init_device method does not allow us to provide the class we want the device to use when it needs to instantiate its DeviceProxys.

So we will have to mock the DeviceProxy class that the DUT imports before it instantiates that class.

The diagram below illustrates the relationship between the TestCase, DUT and its transitive import of the DeviceProxy class from the PyTango module:

_images/mocking-tango-test-case-not-mocked.png

So, we want to replace the imported DeviceProxy class with our own Fake Constructor that will provide a Mocked Device Proxy for the DUT during tests.

In other words, we want to replace the thing that instantiates the DeviceProxy (i.e. the constructor) with our own callable object that constructs a mocked DeviceProxy object instead of the real one. We want to move from the original implementation to the mocked implementation shown in the diagram below:

_images/mocking-tango-test-case-real-vs-mocked.png

Solution¶

This can be achieved by using the unittest.mock library that comes with Python 3 or the third-party library mock for Python 2.7.

The mock.patch() method allows us to temporarily change the object that a name points to with another one.

We use this mechanism to replace the DeviceProxy class (constructor) with our own fake constructor (a mock) that returns a Mock object:

with mock.patch(device_proxy_import_path) as patched_constructor:
    patched_constructor.side_effect = lambda device_fqdn: proxies_to_mock.get(device_fqdn, Mock())
    patched_module = importlib.reload(sys.modules[device_under_test.__module__])

An alternative to using mock.patch is pytest’s monkeypatch. Its .setattr method provides the same functionality, i.e. allowing you to intercept what an object call would normally do and substituting its full execution with your own specification. There are more examples of its use in the OET implementation which is discussed below.

proxies_to_mock is a dictionary that maps DeviceProxyMock objects to their associated Tango device addresses that we expect the DUT to use when instantiating DeviceProxy objects. A brand new generic Mock() is returned if a specific mapping isn’t provided.

Since the DeviceProxy class is defined at import time, we will need to reload the module that holds the DUT. This is why we explicitly call importlib.reload(…) in the context of mock.patch().

For full details and code that implement this solution, see the following merge requests:

https://gitlab.com/ska-telescope/tmc-prototype/-/merge_requests/23

https://gitlab.com/ska-telescope/tmc-prototype/-/merge_requests/35

Moving on¶

Once we mocked DeviceProxy, then we can use the constructor of this object to return a device that is fake. This can be:

a stub device, programmed to behave in a way that suits the tests that we are writing; in this case we are using the stub to inject other inputs to the DUT, under control of the test case;

a mock device, a stub device where we can inspect also how the DUT interacted with it, and we can write assertions.

The benefits that we can achieve with the technique described here are:

ability to test the DUT in isolation

ability to create tests that are very fast (no network, no databases)

ability to inject into the DUT indirect inputs

ability to observe the indirect outputs of the DUT

ability to observe the interactions that the DUT has with the mock.

Using pytest and fixtures¶

The above mocking techniques can be achieved in a very succint way using pytest fixtures. Examples of this can be found in the pytango/examples. And more examples are available in the last section of the Unit testing Tango devices in Python presentation from the Tango 2020 November status update meeting.

Acknowledgement¶

Initial content for this page contributed by the Square Kilometre Array.

FAQ¶

Answers to general Tango questions can be found in the general tango tutorial.

Please also check the general tango how to.

How can I report an issue?

Bug reports are very valuable for the community.

Please open a new issue on the GitHub issues page.

How can I contribute to PyTango and the documentation?

Contribution are always welcome!

You can open pull requests on the GitHub PRs page.

I got a libbost_python error when I try to import tango module…

For instance:

>>> import tango
ImportError: libboost_python.so.1.53.0: cannot open shared object file: No such file or directory

You must check that you have the correct boost python installed on your computer. To see which boost python file PyTango needs, type:

$ ldd /usr/lib64/python2.7/site-packages/tango/_tango.so
    linux-vdso.so.1 =>  (0x00007ffea7562000)
    libtango.so.9 => /lib64/libtango.so.9 (0x00007fac04011000)
    libomniORB4.so.1 => /lib64/libomniORB4.so.1 (0x00007fac03c62000)
    libboost_python.so.1.53.0 => not found
    [...]

I have more questions, where can I ask?

The Tango forum is a good place to get some support. Meet us in the Python section.

PyTango Enhancement Proposals¶

TEP 1 - Device Server High Level API¶

TEP:	1
Title:	Device Server High Level API
Version:	2.2.0
Last-Modified:	10-Sep-2014
Author:	Tiago Coutinho <tcoutinho@cells.es>
Status:	Active
Type:	Standards Track
Content-Type:	text/x-rst
Created:	17-Oct-2012

Abstract¶

This TEP aims to define a new high level API for writting device servers.

Rationale¶

The code for Tango device servers written in Python often obey a pattern. It would be nice if non tango experts could create tango device servers without having to code some obscure tango related code. It would also be nice if the tango programming interface would be more pythonic. The final goal is to make writting tango device servers as easy as:

class Motor(Device):
    __metaclass__ = DeviceMeta

    position = attribute()

    def read_position(self):
        return 2.3

    @command()
    def move(self, position):
        pass

if __name__ == "__main__":
    server_run((Motor,))

Places to simplify¶

After looking at most python device servers one can see some patterns:

At <Device> class level:

<Device> always inherits from latest available DeviceImpl from pogo version

constructor always does the same:

calls super constructor

debug message

calls init_device

all methods have debug_stream as first instruction

init_device does additionaly get_device_properties()
read attribute methods follow the pattern:
def read_Attr(self, attr):
  self.debug_stream()
  value = get_value_from_hardware()
  attr.set_value(value)
write attribute methods follow the pattern:
def write_Attr(self, attr):
  self.debug_stream()
  w_value = attr.get_write_value()
  apply_value_to_hardware(w_value)

At <Device>Class class level:

A <Device>Class class exists for every <DeviceName> class

The <Device>Class class only contains attributes, commands and properties descriptions (no logic)

The attr_list description always follows the same (non explicit) pattern (and so does cmd_list, class_property_list, device_property_list)

the syntax for attr_list, cmd_list, etc is far from understandable

At main() level:

The main() method always does the same:

create Util

register tango class

when registering a python class to become a tango class, 99.9% of times the python class name is the same as the tango class name (example: Motor is registered as tango class “Motor”)

call server_init()

call server_run()

High level API¶

The goals of the high level API are:

Maintain all features of low-level API available from high-level API¶

Everything that was done with the low-level API must also be possible to do with the new API.

All tango features should be available by direct usage of the new simplified, cleaner high-level API and through direct access to the low-level API.

Automatic inheritance from the latest** `DeviceImpl`¶

Currently Devices need to inherit from a direct Tango device implementation (DeviceImpl, or Device_2Impl, Device_3Impl, Device_4Impl, etc) according to the tango version being used during the development.

In order to keep the code up to date with tango, every time a new Tango IDL is released, the code of every device server needs to be manually updated to ihnerit from the newest tango version.

By inheriting from a new high-level Device (which itself automatically decides from which DeviceImpl version it should inherit), the device servers are always up to date with the latest tango release without need for manual intervention (see tango.server).

Low-level way:

class Motor(PyTango.Device_4Impl):
    pass

High-level way:

class Motor(PyTango.server.Device):
    pass

Default implementation of `Device` constructor¶

99% of the different device classes which inherit from low level DeviceImpl only implement __init__ to call their init_device (see tango.server).

Device already calls init_device.

Low-level way:

class Motor(PyTango.Device_4Impl):

    def __init__(self, dev_class, name):
        PyTango.Device_4Impl.__init__(self, dev_class, name)
        self.init_device()

High-level way:

class Motor(PyTango.server.Device):

    # Nothing to be done!

    pass

Default implementation of `init_device()`¶

99% of different device classes which inherit from low level DeviceImpl have an implementation of init_device which at least calls get_device_properties() (see tango.server).

init_device() already calls get_device_properties().

Low-level way:

class Motor(PyTango.Device_4Impl):

    def init_device(self):
        self.get_device_properties()

High-level way:

class Motor(PyTango.server.Device):
    # Nothing to be done!
    pass

Remove the need to code `DeviceClass`¶

99% of different device servers only need to implement their own subclass of DeviceClass to register the attribute, commands, device and class properties by using the corresponding attr_list, cmd_list, device_property_list and class_property_list.

With the high-level API we completely remove the need to code the DeviceClass by registering attribute, commands, device and class properties in the Device with a more pythonic API (see tango.server)

Hide <Device>Class class completely
simplify main()

Low-level way:

class Motor(PyTango.Device_4Impl):

    def read_Position(self, attr):
        pass

class MotorClass(PyTango.DeviceClass):

    class_property_list = { }
    device_property_list = { }
    cmd_list = { }

    attr_list = {
        'Position':
            [[PyTango.DevDouble,
            PyTango.SCALAR,
            PyTango.READ]],
        }

    def __init__(self, name):
        PyTango.DeviceClass.__init__(self, name)
        self.set_type(name)

High-level way:

class Motor(PyTango.server.Device):

    position = PyTango.server.attribute(dtype=float, )

    def read_position(self):
        pass

Pythonic read/write attribute¶

With the low level API, it feels strange for a non tango programmer to have to write:

def read_Position(self, attr):
    # ...
    attr.set_value(new_position)

def read_Position(self, attr):
    # ...
    attr.set_value_date_quality(new_position, time.time(), AttrQuality.CHANGING)

A more pythonic away would be:

def read_position(self):
    # ...
    self.position = new_position

def read_position(self):
    # ...
    self.position = new_position, time.time(), AttrQuality.CHANGING

Or even:

def read_position(self):
    # ...
    return new_position

def read_position(self):
    # ...
    return new_position, time.time(), AttrQuality.CHANGING

Simplify main()¶

the typical main() method could be greatly simplified. initializing tango, registering tango classes, initializing and running the server loop and managing errors could all be done with the single function call to server_run()

Low-level way:

def main():
    try:
        py = PyTango.Util(sys.argv)
        py.add_class(MotorClass,Motor,'Motor')

        U = PyTango.Util.instance()
        U.server_init()
        U.server_run()

    except PyTango.DevFailed,e:
        print '-------> Received a DevFailed exception:',e
    except Exception,e:
        print '-------> An unforeseen exception occured....',e

High-level way:

def main():
    classes = Motor,
    PyTango.server_run(classes)

In practice¶

Currently, a pogo generated device server code for a Motor having a double attribute position would look like this:

#!/usr/bin/env python
# -*- coding:utf-8 -*-


##############################################################################
## license :
##============================================================================
##
## File :        Motor.py
##
## Project :
##
## $Author :      t$
##
## $Revision :    $
##
## $Date :        $
##
## $HeadUrl :     $
##============================================================================
##            This file is generated by POGO
##    (Program Obviously used to Generate tango Object)
##
##        (c) - Software Engineering Group - ESRF
##############################################################################

""""""

__all__ = ["Motor", "MotorClass", "main"]

__docformat__ = 'restructuredtext'

import PyTango
import sys
# Add additional import
#----- PROTECTED REGION ID(Motor.additionnal_import) ENABLED START -----#

#----- PROTECTED REGION END -----#  //      Motor.additionnal_import

##############################################################################
## Device States Description
##
## No states for this device
##############################################################################

class Motor (PyTango.Device_4Impl):

#--------- Add you global variables here --------------------------
#----- PROTECTED REGION ID(Motor.global_variables) ENABLED START -----#

#----- PROTECTED REGION END -----#  //      Motor.global_variables
#------------------------------------------------------------------
#    Device constructor
#------------------------------------------------------------------
    def __init__(self,cl, name):
        PyTango.Device_4Impl.__init__(self,cl,name)
        self.debug_stream("In " + self.get_name() + ".__init__()")
        Motor.init_device(self)

#------------------------------------------------------------------
#    Device destructor
#------------------------------------------------------------------
    def delete_device(self):
        self.debug_stream("In " + self.get_name() + ".delete_device()")
        #----- PROTECTED REGION ID(Motor.delete_device) ENABLED START -----#

        #----- PROTECTED REGION END -----#  //      Motor.delete_device

#------------------------------------------------------------------
#    Device initialization
#------------------------------------------------------------------
    def init_device(self):
        self.debug_stream("In " + self.get_name() + ".init_device()")
        self.get_device_properties(self.get_device_class())
        self.attr_Position_read = 0.0
        #----- PROTECTED REGION ID(Motor.init_device) ENABLED START -----#

        #----- PROTECTED REGION END -----#  //      Motor.init_device

#------------------------------------------------------------------
#    Always excuted hook method
#------------------------------------------------------------------
    def always_executed_hook(self):
        self.debug_stream("In " + self.get_name() + ".always_excuted_hook()")
        #----- PROTECTED REGION ID(Motor.always_executed_hook) ENABLED START -----#

        #----- PROTECTED REGION END -----#  //      Motor.always_executed_hook

#==================================================================
#
#    Motor read/write attribute methods
#
#==================================================================

#------------------------------------------------------------------
#    Read Position attribute
#------------------------------------------------------------------
    def read_Position(self, attr):
        self.debug_stream("In " + self.get_name() + ".read_Position()")
        #----- PROTECTED REGION ID(Motor.Position_read) ENABLED START -----#
        self.attr_Position_read = 1.0
        #----- PROTECTED REGION END -----#  //      Motor.Position_read
        attr.set_value(self.attr_Position_read)

#------------------------------------------------------------------
#    Read Attribute Hardware
#------------------------------------------------------------------
    def read_attr_hardware(self, data):
        self.debug_stream("In " + self.get_name() + ".read_attr_hardware()")
        #----- PROTECTED REGION ID(Motor.read_attr_hardware) ENABLED START -----#

        #----- PROTECTED REGION END -----#  //      Motor.read_attr_hardware


#==================================================================
#
#    Motor command methods
#
#==================================================================


#==================================================================
#
#    MotorClass class definition
#
#==================================================================
class MotorClass(PyTango.DeviceClass):

    #    Class Properties
    class_property_list = {
        }


    #    Device Properties
    device_property_list = {
        }


    #    Command definitions
    cmd_list = {
        }


    #    Attribute definitions
    attr_list = {
        'Position':
            [[PyTango.DevDouble,
            PyTango.SCALAR,
            PyTango.READ]],
        }


#------------------------------------------------------------------
#    MotorClass Constructor
#------------------------------------------------------------------
    def __init__(self, name):
        PyTango.DeviceClass.__init__(self, name)
        self.set_type(name);
        print "In Motor Class  constructor"

#==================================================================
#
#    Motor class main method
#
#==================================================================
def main():
    try:
        py = PyTango.Util(sys.argv)
        py.add_class(MotorClass,Motor,'Motor')

        U = PyTango.Util.instance()
        U.server_init()
        U.server_run()

    except PyTango.DevFailed,e:
        print '-------> Received a DevFailed exception:',e
    except Exception,e:
        print '-------> An unforeseen exception occured....',e

if __name__ == '__main__':
    main()

To make things more fair, let’s analyse the stripified version of the code instead:

import PyTango
import sys

class Motor (PyTango.Device_4Impl):

    def __init__(self,cl, name):
        PyTango.Device_4Impl.__init__(self,cl,name)
        self.debug_stream("In " + self.get_name() + ".__init__()")
        Motor.init_device(self)

    def delete_device(self):
        self.debug_stream("In " + self.get_name() + ".delete_device()")

    def init_device(self):
        self.debug_stream("In " + self.get_name() + ".init_device()")
        self.get_device_properties(self.get_device_class())
        self.attr_Position_read = 0.0

    def always_executed_hook(self):
        self.debug_stream("In " + self.get_name() + ".always_excuted_hook()")

    def read_Position(self, attr):
        self.debug_stream("In " + self.get_name() + ".read_Position()")
        self.attr_Position_read = 1.0
        attr.set_value(self.attr_Position_read)

    def read_attr_hardware(self, data):
        self.debug_stream("In " + self.get_name() + ".read_attr_hardware()")


class MotorClass(PyTango.DeviceClass):

    class_property_list = {
        }


    device_property_list = {
        }


    cmd_list = {
        }


    attr_list = {
        'Position':
            [[PyTango.DevDouble,
            PyTango.SCALAR,
            PyTango.READ]],
        }

    def __init__(self, name):
        PyTango.DeviceClass.__init__(self, name)
        self.set_type(name);
        print "In Motor Class  constructor"


def main():
    try:
        py = PyTango.Util(sys.argv)
        py.add_class(MotorClass,Motor,'Motor')

        U = PyTango.Util.instance()
        U.server_init()
        U.server_run()

    except PyTango.DevFailed,e:
        print '-------> Received a DevFailed exception:',e
    except Exception,e:
        print '-------> An unforeseen exception occured....',e

if __name__ == '__main__':
    main()

And the equivalent HLAPI version of the code would be:

#!/usr/bin/env python

from PyTango import DebugIt, server_run
from PyTango.server import Device, DeviceMeta, attribute


class Motor(Device):
    __metaclass__ = DeviceMeta

    position = attribute()

    @DebugIt()
    def read_position(self):
        return 1.0

def main():
    server_run((Motor,))

if __name__ == "__main__":
    main()

References¶

tango.server

Changes¶

from 2.1.0 to 2.2.0¶

Changed module name from hlapi to server

from 2.0.0 to 2.1.0¶

Changed module name from api2 to hlapi (High Level API)

From 1.0.0 to 2.0.0¶

API Changes
- changed Attr to attribute
- changed Cmd to command
- changed Prop to device_property
- changed ClassProp to class_property
Included command and properties in the example
Added references to API documentation

Copyright¶

This document has been placed in the public domain.

TEP 2 - Tango database serverless¶

TEP:	2
Title:	Tango database serverless
Version:	1.0.0
Last-Modified:	17-Oct-2012
Author:	Tiago Coutinho <tcoutinho@cells.es>
Status:	Active
Type:	Standards Track
Content-Type:	text/x-rst
Created:	17-Oct-2012
Post-History:	17-Oct-2012

Abstract¶

This TEP aims to define a python DataBaseds which doesn’t need a database server behind. It would make tango easier to try out by anyone and it could greatly simplify tango installation on small environments (like small, independent laboratories).

Motivation¶

I was given a openSUSE laptop so that I could do the presentation for the tango meeting held in FRMII on October 2012. Since I planned to do a demonstration as part of the presentation I installed all mysql libraries, omniorb, tango and pytango on this laptop.

During the flight to Munich I realized tango was not working because of a strange mysql server configuration done by the openSUSE distribution. I am not a mysql expert and I couldn’t google for a solution. Also it made me angry to have to install all the mysql crap (libmysqlclient, mysqld, mysql-administrator, bla, bla) just to have a demo running.

At the time of writting the first version of this TEP I still didn’t solve the problem! Shame on me!

Also at the same tango meetting during the tango archiving discussions I heard fake whispers or changing the tango archiving from MySQL/Oracle to NoSQL.

I started thinking if it could be possible to have an alternative implementation of DataBaseds without the need for a mysql server.

Requisites¶

no dependencies on external packages

no need for a separate database server process (at least, by default)

no need to execute post install scripts to fill database

Step 1 - Gather database information¶

It turns out that python has a Database API specification (PEP 249). Python distribution comes natively (>= 2.6) with not one but several persistency options (Data Persistence):

module	Native	Platforms	API	Database	Description
Native python 2.x
`pickle`	Yes	all	dump/load	file	python serialization/marchalling module
`shelve`	Yes	all	dict	file	high level persistent, dictionary-like object
`marshal`	Yes	all	dump/load	file	Internal Python object serialization
`anydbm`	Yes	all	dict	file	Generic access to DBM-style databases. Wrapper for `dbhash`, `gdbm`, `dbm` or `dumbdbm`
`dbm`	Yes	all	dict	file	Simple “database” interface
`gdbm`	Yes	unix	dict	file	GNU’s reinterpretation of dbm
`dbhash`	Yes	unix?	dict	file	DBM-style interface to the BSD database library (needs `bsddb`). Removed in python 3
`bsddb`	Yes	unix?	dict	file	Interface to Berkeley DB library. Removed in python 3
`dumbdbm`	Yes	all	dict	file	Portable DBM implementation
`sqlite3`	Yes	all	DBAPI2	file, memory	DB-API 2.0 interface for SQLite databases
Native Python 3.x
`pickle`	Yes	all	dump/load	file	python serialization/marchalling module
`shelve`	Yes	all	dict	file	high level persistent, dictionary-like object
`marshal`	Yes	all	dump/load	file	Internal Python object serialization
`dbm`	Yes	all	dict	file	Interfaces to Unix “databases”. Wrapper for `dbm.gnu`, `dbm.ndbm`, `dbm.dumb`
`dbm.gnu`	Yes	unix	dict	file	GNU’s reinterpretation of dbm
`dbm.ndbm`	Yes	unix	dict	file	Interface based on ndbm
`dbm.dumb`	Yes	all	dict	file	Portable DBM implementation
`sqlite3`	Yes	all	DBAPI2	file, memory	DB-API 2.0 interface for SQLite databases

third-party DBAPI2

third-party NOSQL

(these may or not have python DBAPI2 interface)

CouchDB - couchdb.client

MongoDB - pymongo - NoSQL database

Cassandra - pycassa

third-party database abstraction layer

SQLAlchemy - sqlalchemy - Python SQL toolkit and Object Relational Mapper

Step 2 - Which module to use?¶

herrrr… wrong question!

The first decision I thought it should made is which python module better suites the needs of this TEP. Then I realized I would fall into the same trap as the C++ DataBaseds: hard link the server to a specific database implementation (in their case MySQL).

I took a closer look at the tables above and I noticed that python persistent modules come in two flavors: dict and DBAPI2. So naturally the decision I thought it had to be made was: which flavor to use?

But then I realized both flavors could be used if we properly design the python DataBaseds.

Step 3 - Architecture¶

If you step back for a moment and look at the big picture you will see that what we need is really just a mapping between the Tango DataBase set of attributes and commands (I will call this Tango Device DataBase API) and the python database API oriented to tango (I will call this TDB interface).

The TDB interface should be represented by the ITangoDB. Concrete databases should implement this interface (example, DBAPI2 interface should be represented by a class TangoDBAPI2 implementing ITangoDB).

Connection to a concrete ITangoDB should be done through a factory: TangoDBFactory

The Tango DataBase device should have no logic. Through basic configuration it should be able to ask the TangoDBFactory for a concrete ITangoDB. The code of every command and attribute should be simple forward to the ITangoDB object (a part of some parameter translation and error handling).

$digraph uml { fontname = "Bitstream Vera Sans" fontsize = 8 node [ fontname = "Bitstream Vera Sans" fontsize = 8 shape = "record" ] edge [ fontname = "Bitstream Vera Sans" fontsize = 8 ] subgraph tangodbPackage { label = "Package tangodb" ITangoDB [ label = "{ITangoDB|+ add_device()=0\l+delete_device()=0\l+export_device()=0\l...}" ] DBAPI2 [ label = "{TangoDBAPI2}" ] Dict [ label = "{TangoDBDict}" ] DBSqlite3 [ label = "{TangoDBSqlite3}" ] mxODBC [ label = "{TangoDBmxODBC}" ] MySQLdb [ label = "{TangoDBMySQLdb}" ] Shelve [ label = "{TangoDBShelve}" ] TangoDBFactory [ label = "{TangoDBFactory|+get_tango_db(): ITangoDB}" ] DBAPI2 -> ITangoDB Dict -> ITangoDB DBSqlite3 -> DBAPI2 mxODBC -> DBAPI2 MySQLdb -> DBAPI2 Shelve -> Dict } DeviceImpl [ label = "{Tango::DeviceImpl}" ] DataBase [ label = "{DataBase|+DbAddDevice()\l+DbDeleteDevice()\l+DbExportDevice()\l...}" ] DataBase -> DeviceImpl }$

Step 4 - The python DataBaseds¶

If we can make a python device server which has the same set of attributes and commands has the existing C++ DataBase (and of course the same semantic behavior), the tango DS and tango clients will never know the difference (BTW, that’s one of the beauties of tango).

The C++ DataBase consists of around 80 commands and 1 mandatory attribute (the others are used for profiling) so making a python Tango DataBase device from scratch is out of the question.

Fortunately, C++ DataBase is one of the few device servers that were developed since the beginning with pogo and were successfully adapted to pogo 8. This means there is a precious DataBase.xmi available which can be loaded to pogo and saved as a python version. The result of doing this can be found here here (this file was generated with a beta version of the pogo 8.1 python code generator so it may contain errors).

Step 5 - Default database implementation¶

The decision to which database implementation should be used should obey the following rules:

should not require an extra database server process

should be a native python module

should implement python DBAPI2

It came to my attention the sqlite3 module would be perfect as a default database implementation. This module comes with python since version 2.5 and is available in all platforms. It implements the DBAPI2 interface and can store persistently in a common OS file or even in memory.

There are many free scripts on the web to translate a mysql database to sqlite3 so one can use an existing mysql tango database and directly use it with the python DataBaseds with sqlite3 implementation.

Development¶

The development is being done in PyTango SVN trunk in the tango.databaseds module.

You can checkout with:

$ svn co https://tango-cs.svn.sourceforge.net/svnroot/tango-cs/bindings/PyTango/trunk PyTango-trunk

Disadvantages¶

A serverless, file based, database has some disadvantages when compared to the mysql solution:

Not possible to distribute load between Tango DataBase DS and database server (example: run the Tango DS in one machine and the database server in another)

Not possible to have two Tango DataBase DS pointing to the same database

Harder to upgrade to newer version of sql tables (specially if using dict based database)

Bare in mind the purpose of this TED is to simplify the process of trying tango and to ease installation and configuration on small environments (like small, independent laboratories).

References¶

http://wiki.python.org/moin/DbApiCheatSheet

http://wiki.python.org/moin/DbApiModuleComparison

http://wiki.python.org/moin/DatabaseProgramming

http://wiki.python.org/moin/DbApiFaq

PEP 249

http://wiki.python.org/moin/ExtendingTheDbApi

http://wiki.python.org/moin/DbApi3

History of changes¶

Contributers: T. Coutinho
Last Update: Jun 12, 2022

Document revisions¶

Date	Revision	Description	Author
18/07/03	1.0	Initial Version	M. Ounsy
06/10/03	2.0	Extension of the “Getting Started” paragraph	A. Buteau/M. Ounsy
14/10/03	3.0	Added Exception Handling paragraph	M. Ounsy
13/06/05	4.0	Ported to Latex, added events, AttributeProxy and ApiUtil	V. Forchì
13/06/05	4.1	fixed bug with python 2.5 and and state events new Database constructor	V. Forchì
15/01/06	5.0	Added Device Server classes	E.Taurel
15/03/07	6.0	Added AttrInfoEx, AttributeConfig events, 64bits, write_attribute	T. Coutinho
21/03/07	6.1	Added groups	T. Coutinho
15/06/07	6.2	Added dynamic attributes doc	E. Taurel
06/05/08	7.0	Update to Tango 6.1. Added DB methods, version info	T. Coutinho
10/07/09	8.0	Update to Tango 7. Major refactoring. Migrated doc	T. Coutinho/R. Suñe
24/07/09	8.1	Added migration info, added missing API doc	T. Coutinho/R. Suñe
21/09/09	8.2	Added migration info, release of 7.0.0beta2	T. Coutinho/R. Suñe
12/11/09	8.3	Update to Tango 7.1.	T. Coutinho/R. Suñe
??/12/09	8.4	Update to PyTango 7.1.0 rc1	T. Coutinho/R. Suñe
19/02/10	8.5	Update to PyTango 7.1.1	T. Coutinho/R. Suñe
06/08/10	8.6	Update to PyTango 7.1.2	T. Coutinho
05/11/10	8.7	Update to PyTango 7.1.3	T. Coutinho
08/04/11	8.8	Update to PyTango 7.1.4	T. Coutinho
13/04/11	8.9	Update to PyTango 7.1.5	T. Coutinho
14/04/11	8.10	Update to PyTango 7.1.6	T. Coutinho
15/04/11	8.11	Update to PyTango 7.2.0	T. Coutinho
12/12/11	8.12	Update to PyTango 7.2.2	T. Coutinho
24/04/12	8.13	Update to PyTango 7.2.3	T. Coutinho
21/09/12	8.14	Update to PyTango 8.0.0	T. Coutinho
10/10/12	8.15	Update to PyTango 8.0.2	T. Coutinho
20/05/13	8.16	Update to PyTango 8.0.3	T. Coutinho
28/08/13	8.13	Update to PyTango 7.2.4	T. Coutinho
27/11/13	8.18	Update to PyTango 8.1.1	T. Coutinho
16/05/14	8.19	Update to PyTango 8.1.2	T. Coutinho
30/09/14	8.20	Update to PyTango 8.1.4	T. Coutinho
01/10/14	8.21	Update to PyTango 8.1.5	T. Coutinho
05/02/15	8.22	Update to PyTango 8.1.6	T. Coutinho
03/02/16	8.23	Update to PyTango 8.1.8	T. Coutinho
12/08/16	8.24	Update to PyTango 8.1.9	V. Michel
26/02/16	9.2.0a	Update to PyTango 9.2.0a	T. Coutinho
15/08/16	9.2.0	9.2.0 Release	V. Michel
23/01/17	9.2.1	9.2.1 Release	V. Michel
27/09/17	9.2.2	9.2.2 Release	G. Cuni/V. Michel/J. Moldes
30/05/18	9.2.3	9.2.3 Release	V. Michel
30/07/18	9.2.4	9.2.4 Release	V. Michel
28/11/18	9.2.5	9.2.5 Release	A. Joubert
13/03/19	9.3.0	9.3.0 Release	T. Coutinho
08/08/19	9.3.1	9.3.1 Release	A. Joubert
30/04/20	9.3.2	9.3.2 Release	A. Joubert
24/12/20	9.3.3	9.3.3 Release	A. Joubert

Version history¶

Version	Changes
9.3.3	9.3.3 release. Features: Pull Request #378: Add string support for MultiDeviceTestContext devices_info class field Pull Request #384: Add test context support for memorized attributes Pull Request #395: Fix Windows build and add CI test suite (#355, #368, #369) Changes: Pull Request #365: Preserve cause of exception when getting/setting attribute in DeviceProxy (#364) Pull Request #385: Improve mandatory + default device property error message (#380) Pull Request #397: Add std namespace prefix in C++ code Bug/doc fixes: Pull Request #360: Fix convert2array for Unicode to DevVarStringArray (Py3) (#361) Pull Request #386: Fix DeviceProxy repr/str memory leak (#298) Pull Request #352: Fix sphinx v3 warning Pull Request #359: MultiDeviceTestContext example Pull Request #363: Change old doc links from ESRF to RTD Pull Request #370: Update CI to use cppTango 9.3.4rc6 Pull Request #389: Update CI and dev Docker to cpptango 9.3.4 Pull Request #376: Update Windows CI and dev containers to boost 1.73.0 Pull Request #377: VScode remote development container support Pull Request #391: Add documentation about testing Pull Request #393: Fix a typo in get_server_info documentation (#392)
9.3.2	9.3.2 release. Features: Pull Request #314: Add MultiDeviceTestContext for testing more than one Device Pull Request #317: Add get_device_attribute_list and missing pipe methods to Database interface (#313) Pull Request #327: Add EnsureOmniThread and is_omni_thread (#307, #292) Changes: Pull Request #316: Reduce six requirement from 1.12 to 1.10 (#296) Pull Request #326: Add Docker development container Pull Request #330: Add enum34 to Python 2.7 docker images Pull Request #329: Add test to verify get_device_properties called on init Pull Request #341: Build DevFailed origin from format_exception (#340) Bug/doc fixes: Pull Request #301: Fix documentation error Pull Request #334: Update green mode docs and asyncio example (#333) Pull Request #335: Generalise search for libboost_python on POSIX (#300, #310) Pull Request #343: Extend the info on dependencies in README Pull Request #345: Fix power_supply client example PowerOn -> TurnOn Pull Request #347: Fix memory leak for DevEncoded attributes Pull Request #348: Fix dynamic enum attributes created without labels (#56)
9.3.1	9.3.1 release. Changes: Pull Request #277: Windows builds using AppVeyor (#176) Pull Request #290: Update docs: int types maps to DevLong64 (#282) Pull Request #293: Update exception types in proxy docstrings Bug fixes: Pull Request #270: Add six >= 1.12 requirement (#269) Pull Request #273: DeviceAttribute.is_empty not working correctly with latest cpp tango version (#271) Pull Request #274: Add unit tests for spectrum attributes, including empty (#271) Pull Request #281: Fix DevEncoded commands on Python 3 (#280) Pull Request #288: Make sure we only convert to string python unicode/str/bytes objects (#285) Pull Request #289: Fix compilation warnings and conda build (#286)
9.3.0	9.3.0 release. Changes: Pull Request #242: Improve Python version check for enum34 install Pull Request #250: Develop 9.3.0 Pull Request #258: Change Travis CI builds to xenial Bug fixes: Pull Request #245: Change for collections abstract base class Pull Request #247: Use IP address instead of hostname (fix #246) Pull Request #252: Fix wrong link to tango dependency (#235) Pull Request #254: Fix mapping of AttrWriteType WT_UNKNOWN Pull Request #257: Fix some docs and docstrings Pull Request #260: add ApiUtil.cleanup() Pull Request #262: Fix compile error under Linux Pull Request #263: Fix #251: Python 2 vs Python 3: DevString with bytes
9.2.5	9.2.5 release. Changes: Pull Request #212: Skip databaseds backends in PyTango compatibility module Pull Request #221: DevEnum attributes can now be directly assigned labels Pull Request #236: Cleanup db_access module Pull Request #237: Add info about how to release a new version Bug fixes: Pull Request #209 (issue #207): Fix documentation warnings Pull Request #211: Yet another fix to the gevent threadpool error wrapping Pull Request #214 (issue #213): DevEncoded attribute should produce a bytes object in python 3 Pull Request #219: Fixing icons in documentation Pull Request #220: Fix ‘DevFailed’ object does not support indexing Pull Request #225 (issue #215): Fix exception propagation in python 3 Pull Request #226 (issue #216): Add missing converter from python bytes to char* Pull Request #227: Gevent issue #1260 should be fixed by now Pull Request #232: use special case-insensitive weak values dictionary for Tango nodes
9.2.4	9.2.4 release. Changes: Pull Request #194 (issue #188): Easier access to DevEnum attribute using python enum Pull Request #199 (issue #195): Support python enum as dtype argument for attributes Pull Request #205 (issue #202): Python 3.7 compatibility Bug fixes: Pull Request #193 (issue #192): Fix a gevent green mode memory leak introduced in v9.2.3
9.2.3	9.2.3 release. Changes: Pull Request #169: Use tango-controls theme for the documentation Pull Request #170 (issue #171): Use a private gevent ThreadPool Pull Request #180: Use same default encoding for python2 and python3 (utf-8) Bug fixes: Pull Request #178 (issue #177): Make CmdDoneEvent.argout writable Pull Request #178: Add GIL control for ApiUtil.get_asynch_replies Pull Request #187 (issue #186): Fix and extend client green mode
9.2.2	9.2.2 release. Features: Pull Request #104: Pipe Events Pull Request #106: Implement pipe write (client and server, issue #9) Pull Request #122: Dynamic commands Pull Request #124: Add forward attribute Pull Request #129: Implement mandatory property (issue #30) Changes: Pull Request #109: Device Interface Change Events Pull Request #113: Adding asyncio green mode documentation and a how-to on contributing Pull Request #114: Added PEP8-ified files in tango module. Pull Request #115: Commands polling tests (client and server) Pull Request #116: Attribute polling tests (client and server) Pull Request #117: Use official tango-controls conda channel Pull Request #125: Forward attribute example Pull Request #134: Linting pytango (with pylint + flake8) Pull Request #137: Codacy badge in README and code quality policy in How to Contribute Pull Request #143: Added missing PipeEventData & DevIntrChangeEventData Bug fixes: Pull Request #85 (issue #84): Fix Gevent ThreadPool exceptions Pull Request #94 (issue #93): Fix issues in setup file (GCC-7 build) Pull Request #96: Filter badges from the long description Pull Request #97: Fix/linker options Pull Request #98: Refactor green mode for client and server APIs Pull Request #101 (issue #100) check for None and return null string Pull Request #102: Update server tests Pull Request #103: Cache build objects to optimize travis builds Pull Request #112 (issue #111): Use _DeviceClass as tango device class constructor Pull Request #128 (issue #127): Set default worker in server.py Pull Request #135: Better exception handling in server.run and test context (issue #131) Pull Request #142 (issue #142): Added missing PipeEventData & DevIntrChangeEventData Pull Request #148 (issue #144): Expose utils helpers Pull Request #149: Fix return value of proxy.subscribe_event Pull Request #158 (issue #155): Fix timestamp and casing in utils.EventCallback
9.2.1	9.2.1 release. Features: Pull Requests #70: Add test_context and test_utils modules, used for pytango unit-testing Changes: Issue #51: Refactor platform specific code in setup file Issue #67: Comply with PEP 440 for pre-releases Pull Request #70: Add unit-testing for the server API Pull Request #70: Configure Travis CI for continuous integration Pull Request #76: Add unit-testing for the client API Pull Request #78: Update the python version classifiers Pull Request #80: Move tango object server to its own module Pull Request #90: The metaclass definition for tango devices is no longer mandatory Bug fixes: Issue #24: Fix dev_status dangling pointer bug Issue #57: Fix dev_state/status to be gevent safe Issue #58: Server gevent mode internal call hangs Pull Request #62: Several fixes in tango.databaseds Pull Request #63: Follow up on issue #21 (Fix Group.get_device method) Issue #64: Fix AttributeProxy.__dev_proxy to be initialized with python internals Issue #74: Fix hanging with an asynchronous tango server fails to start Pull Request #81: Fix DeviceImpl documentation Issue #82: Fix attribute completion for device proxies with IPython >= 4 Issue #84: Fix gevent threadpool exceptions
9.2.0	9.2.0 release. Features: Issue #37: Add display_level and polling_period as optional arguments to command decorator Bug fixes: Fix cache problem when using DeviceProxy through an AttributeProxy Fix compilation on several platforms Issue #19: Defining new members in DeviceProxy has side effects Fixed bug in beacon.add_device Fix for get_device_list if server_name is ‘*’ Fix get_device_attribute_property2 if prop_attr is not None Accept StdStringVector in put_device_property Map ‘int’ to DevLong64 and ‘uint’ to DevULong64 Issue #22: Fix push_data_ready_event() deadlock Issue #28: Fix compilation error for constants.cpp Issue #21: Fix Group.get_device method Issue #33: Fix internal server documentation Changes: Move ITango to another project Use setuptools instead of distutils Add six as a requirement Refactor directory structure Rename PyTango module to tango (import PyTango still works for backward compatibility) Add a ReST readme for GitHub and PyPI ITango changes (moved to another project): Fix itango event logger for python 3 Avoid deprecation warning with IPython 4.x Use entry points instead of scripts
9.2.0a	9.2 alpha release. Missing: writtable pipes (client and server) dynamic commands (server) device interface change event (client and server) pipe event (client and server) Bug fixes: 776: [pytango][8.1.8] SyntaxError: invalid syntax
8.1.9	Features: PR #2: asyncio support for both client and server API PR #6: Expose AutoTangoMonitor and AutoTangoAllowThreads Bug fixes: PR #31: Get -l flags from pkg-config PR #15: Rename itango script to itango3 for python3 PR #14: Avoid deprecation warning with IPython 4.x
8.1.8	Features: PR #3: Add a run_server class method to Device PR #4: Add device inheritance 110: device property with auto update in database Bug fixes: 690: Description attribute property 700: [pytango] useless files in the source distribution 701: Memory leak in command with list argument 704: Assertion failure when calling command with string array input type 705: Support boost_python lib name on Gentoo 714: Memory leak in PyTango for direct server command calls 718: OverflowErrors with float types in 8.1.6 724: PyTango DeviceProxy.command_inout(<str>) memory leaks 736: pytango FTBFS with python 3.4 747: PyTango event callback in gevent mode gets called in non main thread
8.1.6	Bug fixes: 698: PyTango.Util discrepancy 697: PyTango.server.run does not accept old Device style classes
8.1.5	Bug fixes: 687: [pytango] 8.1.4 unexpected files in the source package 688: PyTango 8.1.4 new style server commands don’t work
8.1.4	Features: 107: Nice to check Tango/PyTango version at runtime Bug fixes: 659: segmentation fault when unsubscribing from events 664: problem while installing PyTango 8.1.1 with pip (using pip 1.4.1) 678: [pytango] 8.1.2 unexpected files in the source package 679: PyTango.server tries to import missing __builtin__ module on Python 3 680: Cannot import PyTango.server.run 686: Device property substitution for a multi-device server
8.1.3	SKIPPED
8.1.2	Features: 98: PyTango.server.server_run needs additional post_init_callback parameter 102: DevEncoded attribute should support a python buffer object 103: Make creation of *EventData objects possible in PyTango Bug fixes: 641: python3 error handling issue 648: PyTango unicode method parameters fail 649: write_attribute of spectrum/image fails in PyTango without numpy 650: [pytango] 8.1.1 not compatible with ipyton 1.2.0-rc1 651: PyTango segmentation fault when run a DS that use attr_data.py 660: command_inout_asynch (polling mode) fails 666: PyTango shutdown sometimes blocks.
8.1.1	Features: Implemented tango C++ 8.1 API Bug fixes: 527: set_value() for ULong64 573: [pytango] python3 error with unregistered device 611: URGENT fail to write attribute with PyTango 8.0.3 612: [pytango][8.0.3] failed to build from source on s390 615: Threading problem when setting a DevULong64 attribute 622: PyTango broken when running on Ubuntu 13 626: attribute_history extraction can raised an exception 628: Problem in installing PyTango 8.0.3 on Scientific Linux 6 635: Reading of ULong64 attributes does not work 636: PyTango log messages are not filtered by level 637: [pytango] segfault doing write_attribute on Group
8.1.0	SKIPPED
8.0.3	Features: 88: Implement Util::server_set_event_loop method in python Bug fixes: 3576353: [pytango] segfault on ‘RestartServer’ 3579062: [pytango] Attribute missing methods 3586337: [pytango] Some DeviceClass methods are not python safe 3598514: DeviceProxy.__setattr__ break python’s descriptors 3607779: [pytango] IPython 0.10 error 598: Import DLL by PyTango failed on windows 605: [pytango] use distutils.version module
8.0.2	Bug fixes: 3570970: [pytango] problem during the python3 building 3570971: [pytango] itango does not work without qtconsole 3570972: [pytango] warning/error when building 8.0.0 3570975: [pytango] problem during use of python3 version 3574099: [pytango] compile error with gcc < 4.5
8.0.1	SKIPPED
8.0.0	Features: Implemented tango C++ 8.0 API Python 3k compatible Bug fixes: 3023857: DevEncoded write attribute not supported 3521545: [pytango] problem with tango profile 3530535: PyTango group writting fails 3564959: EncodedAttribute.encode_xxx() methods don’t accept bytearray
7.2.4	Bug fixes: 551: [pytango] Some DeviceClass methods are not python safe
7.2.3	Features: 3495607: DeviceClass.device_name_factory is missing Bug fixes: 3103588: documentation of PyTango.Attribute.Group 3458336: Problem with pytango 7.2.2 3463377: PyTango memory leak in read encoded attribute 3487930: [pytango] wrong python dependency 3511509: Attribute.set_value_date_quality for encoded does not work 3514457: [pytango] TANGO_HOST multi-host support 3520739: command_history(…) in PyTango
7.2.2	Features: 3305251: DS dynamic attributes discards some Attr properties 3365792: DeviceProxy.<cmd_name> could be documented 3386079: add support for ipython 0.11 3437654: throw python exception as tango exception 3447477: spock profile installation Bug fixes: 3372371: write attribute of DevEncoded doesn’t work 3374026: [pytango] pyflakes warning 3404771: PyTango.MultiAttribute.get_attribute_list missing 3405580: PyTango.MultiClassAttribute missing
7.2.1	SKIPPED
7.2.0	Features: 3286678: Add missing EncodedAttribute JPEG methods
7.1.6	Bug fixes: 7.1.5 distribution is missing some files
7.1.5	Bug fixes: 3284174: 7.1.4 does not build with gcc 4.5 and tango 7.2.6 3284265: [pytango][7.1.4] a few files without licence and copyright 3284318: copyleft vs copyright 3284434: [pytango][doc] few ERROR during the doc generation 3284435: [pytango][doc] few warning during the doc generation 3284440: [pytango][spock] the profile can’t be installed 3285185: PyTango Device Server does not load Class Properties values 3286055: PyTango 7.1.x DS using Tango C++ 7.2.x seg faults on exit
7.1.4	Features: 3274309: Generic Callback for events Bug fixes: 3011775: Seg Faults due to removed dynamic attributes 3105169: PyTango 7.1.3 does not compile with Tango 7.2.X 3107243: spock profile does not work with python 2.5 3124427: PyTango.WAttribute.set_max_value() changes min value 3170399: Missing documentation about is_<attr>_allowed method 3189082: Missing get_properties() for Attribute class 3196068: delete_device() not called after server_admin.Kill() 3257286: Binding crashes when reading a WRITE string attribute 3267628: DP.read_attribute(, extract=List/tuple) write value is wrong 3274262: Database.is_multi_tango_host missing 3274319: EncodedAttribute is missing in PyTango (<= 7.1.3) 3277269: read_attribute(DevEncoded) is not numpy as expected 3278946: DeviceAttribute copy constructor is not working Documentation: Added The Utilities API chapter Added Encoded API chapter Improved Write a server (original API) chapter
7.1.3	Features: tango logging with print statement tango logging with decorators from sourceforge: 3060380: ApiUtil should be exported to PyTango Bug fixes: added licence header to all source code files spock didn’t work without TANGO_HOST env. variable (it didn’t recognize tangorc) spock should give a proper message if it tries to be initialized outside ipython 3048798: licence issue GPL != LGPL 3073378: DeviceImpl.signal_handler raising exception crashes DS 3088031: Python DS unable to read DevVarBooleanArray property 3102776: PyTango 7.1.2 does not work with python 2.4 & boost 1.33.0 3102778: Fix compilation warnings in linux
7.1.2	Features: 2995964: Dynamic device creation 3010399: The DeviceClass.get_device_list that exists in C++ is missing 3023686: Missing DeviceProxy.<attribute name> 3025396: DeviceImpl is missing some CORBA methods 3032005: IPython extension for PyTango 3033476: Make client objects pickable 3039902: PyTango.Util.add_class would be useful Bug fixes: 2975940: DS command with DevVarCharArray return type fails 3000467: DeviceProxy.unlock is LOCKING instead of unlocking! 3010395: Util.get_device_* methods don’t work 3010425: Database.dev_name does not work 3016949: command_inout_asynch callback does not work 3020300: PyTango does not compile with gcc 4.1.x 3030399: Database put(delete)_attribute_alias generates segfault
7.1.1	Features: Improved setup script Interfaced with PyPI Cleaned build script warnings due to unclean python C++ macro definitions 2985993: PyTango numpy command support 2971217: PyTango.GroupAttrReplyList slicing Bug fixes: 2983299: Database.put_property() deletes the property 2953689: can not write_attribute scalar/spectrum/image 2953030: PyTango doc installation
7.1.0	Features: 2908176: read_, write_ and is_*_allowed() methods can now be defined 2941036: TimeVal conversion to time and datetime added str representation on Attr, Attribute, DeviceImpl and DeviceClass Bug fixes: 2903755: get_device_properties() bug reading DevString properties 2909927: PyTango.Group.read_attribute() return values 2914194: DevEncoded does not work 2916397: PyTango.DeviceAttribute copy constructor does not work 2936173: PyTango.Group.read_attributes() fails 2949099: Missing PyTango.Except.print_error_stack
7.1.0rc1	Features: v = image_attribute.get_write_value() returns square sequences (arrays of arrays, or numpy objects) now instead of flat lists. Also for spectrum attributes a numpy is returned by default now instead. image_attribute.set_value(v) accepts numpy arrays now or square sequences instead of just flat lists. So, dim_x and dim_y are useless now. Also the numpy path is faster. new enum AttrSerialModel Attribute new methods: set(get)_attr_serial_model, set_change_event, set_archive_event, is_change_event, is_check_change_event, is_archive_criteria, is_check_archive_criteria, remove_configuration added support for numpy scalars in tango operations like write_attribute (ex: now a DEV_LONG attribute can receive a numpy.int32 argument in a write_attribute method call) Bug fixes: DeviceImpl.set_value for scalar attributes DeviceImpl.push_*_event server commands with DevVar*StringArray as parameter or as return type in windows,a bug in PyTango.Util prevented servers from starting up DeviceImpl.get_device_properties for string properties assigns only first character of string to object member instead of entire string added missing methods to Util exported SubDevDiag class error in read/events of attributes of type DevBoolean READ_WRITE error in automatic unsubscribe events of DeviceProxy when the object disapears (happens only on some compilers with some optimization flags) fix possible bug when comparing attribute names in DeviceProxy pretty print of DevFailed -> fix deprecation warning in python 2.6 device class properties where not properly fetched when there is no property value defined memory leak when converting DevFailed exceptions from C++ to python python device server file without extension does not start Documentation: Improved FAQ Improved compilation chapter Improved migration information

Indexes¶

Last update: Jun 12, 2022

Contents¶

Getting started¶

Installing¶

Linux¶

PyPi¶

Windows¶

Compiling¶

Linux¶

Windows¶

Testing¶

Quick tour¶

Fundamental TANGO concepts¶

Minimum setup¶

Client¶

Server¶

ITango¶

Green mode¶

Client green modes¶

futures mode¶

gevent mode¶

asyncio mode¶

Server green modes¶

gevent mode¶

asyncio mode¶

PyTango API¶

Data types¶

Pipe data types¶

DevEnum pythonic usage¶

Client API¶

DeviceProxy¶

AttributeProxy¶

Group¶

Group class¶

GroupReply classes¶

Green API¶

API util¶

Information classes¶

Attribute¶

Command¶

Other¶

Storage classes¶

Attribute: DeviceAttribute¶

Command: DeviceData¶

Callback related classes¶

Event related classes¶

Event configuration information¶

Event arrived structures¶

History classes¶

Enumerations & other classes¶

Enumerations¶

Other classes¶

Server API¶

High level server API¶

Device¶

DeviceImpl¶

DeviceClass¶

Logging decorators¶

LogIt¶

DebugIt¶

InfoIt¶

WarnIt¶

ErrorIt¶

FatalIt¶

Attribute classes¶

Attr¶

Attribute¶

WAttribute¶

MultiAttribute¶

UserDefaultAttrProp¶

Util¶

Database API¶

Encoded API¶

The Utilities API¶

Exception API¶

Exception definition¶

Throwing exception in a device server¶

Exception API¶

How to¶

How to contribute¶

Check the default TANGO host¶

Automatic inheritance from the latest** `DeviceImpl`¶

Default implementation of `Device` constructor¶

Default implementation of `init_device()`¶

Remove the need to code `DeviceClass`¶