This quick tour will guide you through the first steps on using PyTango. This is the new quick tour guide based on the ITango console. You can still find the old version of this tour based on a simple python console here.
Start an ipython tango console with:
$ itango
and type:
ITango [1]: PyTango.__version__ Result [1]: '8.0.0' ITango [2]: PyTango.__version_long__ Result [2]: '8.0.0dev0' ITango [3]: PyTango.__version_number__ Result [3]: 800 ITango [4]: PyTango.__version_description__ Result [4]: 'This version implements the C++ Tango 8.0 API.'
or alternatively:
ITango [1]: PyTango.Release.version Result [1]: '8.0.0' ITango [2]: PyTango.Release.version_long Result [2]: '8.0.0dev0' ITango [3]: PyTango.Release.version_number Result [3]: 800 ITango [4]: PyTango.Release.version_description Result [4]: 'This version implements the C++ Tango 8.0 API.'
Tip
When typing, try pressing <tab>. Since ITango has autocomplete embedded you should get a list of possible completions. Example:
PyTango.Release.<tab>
Should get a list of all members of PyTango.Release class.
From a client (This is only possible since PyTango 7.0.0)
ITango [1]: import PyTango.constants ITango [2]: PyTango.constants.TgLibVers Result [2]: '8.0.0'
From a server you can alternatively do:
u = PyTango.Util.instance()
tg_cpp_lib_ver = u.get_tango_lib_release()
One of the most basic examples is to get a reference to a device and determine if it is running or not.
ITango [1]: # What is a DeviceProxy, really? ITango [1]: DeviceProxy? 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 = PyTango.DeviceProxy("sys/tg_test/1") ITango [2]: tangotest = DeviceProxy("sys/tg_test/1") ITango [3]: # ping it ITango [4]: tangotest.ping() Result [4]: 110 ITango [5]: # Lets test the state ITango [6]: tangotest.state() Result [6]: PyTango._PyTango.DevState.RUNNING ITango [7]: # And now the status ITango [8]: tangotest.status() Result [8]: 'The device is in RUNNING state.'
Note
Did you notice that you didn’t write PyTango.DeviceProxy but instead just DeviceProxy ? This is because ITango automatically exports the DeviceProxy, AttributeProxy, Database and Group classes to the namespace. If you are writting code outside ITango you MUST use the PyTango module prefix.
Tip
When typing the device name in the DeviceProxy creation line, try pressing the <tab> key. You should get a list of devices:
tangotest = DeviceProxy("sys<tab>
Better yet (and since the Tango Class of ‘sys/tg_test/1’ is ‘TangoTest’), try doing:
tangotest = TangoTest("<tab>
Now the list of devices should be reduced to the ones that belong to the ‘TangoTest’ class. Note that TangoTest only works in ITango. If you are writting code outside ITango you MUST use PyTango.DeviceProxy instead.
As you can see in the following example, when scalar types are used, PyTango automatically manages the data types, and writing scripts is quite easy.
ITango [1]: tangotest = TangoTest("sys/tg_test/1") ITango [2]: # classical way ITango [2]: r = tangotest.command_inout("DevString", "Hello, world!") ITango [3]: print "Result of execution of DevString command =", r Result of execution of DevString command = Hello, world! ITango [4]: # 'pythonic' way ITango [5]: tangotest.DevString("Hello, world!") Result [5]: 'Hello, world!' ITango [6]: # type is automatically managed by PyTango ITango [7]: tangotest.DevULong(12456) Result [7]: 12456
In this case you have to use put your arguments data in the correct python structures.
ITango [1]: tangotest = TangoTest("sys/tg_test/1") ITango [2]: argin = [1, 2, 3], ["Hello", "World"] ITango [3]: tango_test.DevVarLongArray(argin) Result [3]: [array([1, 2, 3]), ['Hello', 'World']]
Note
notice that the command returns a list of two elements. The first element is a numpy.ndarray (assuming PyTango is compiled with numpy support). This is because PyTango does a best effort to convert all numeric array types to numpy arrays.
Basic read/write attribute operations.
ITango [1]: # Read a scalar attribute ITango [2]: print tangotest.read_attribute("long_scalar") DeviceAttribute[ data_format = PyTango._PyTango.AttrDataFormat.SCALAR dim_x = 1 dim_y = 0 has_failed = False is_empty = False name = 'long_scalar' nb_read = 1 nb_written = 1 quality = PyTango._PyTango.AttrQuality.ATTR_VALID r_dimension = AttributeDimension(dim_x = 1, dim_y = 0) time = TimeVal(tv_nsec = 0, tv_sec = 1281084943, tv_usec = 461730) type = PyTango._PyTango.CmdArgType.DevLong value = 239 w_dim_x = 1 w_dim_y = 0 w_dimension = AttributeDimension(dim_x = 1, dim_y = 0) w_value = 0] ITango [3]: # Read a spectrum attribute ITango [4]: print tangotest.read_attribute("double_spectrum") DeviceAttribute[ data_format = PyTango._PyTango.AttrDataFormat.SPECTRUM dim_x = 20 dim_y = 0 has_failed = False is_empty = False name = 'double_spectrum' nb_read = 20 nb_written = 20 quality = PyTango._PyTango.AttrQuality.ATTR_VALID r_dimension = AttributeDimension(dim_x = 20, dim_y = 0) time = TimeVal(tv_nsec = 0, tv_sec = 1281085195, tv_usec = 244760) type = PyTango._PyTango.CmdArgType.DevDouble value = array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19.]) w_dim_x = 20 w_dim_y = 0 w_dimension = AttributeDimension(dim_x = 20, dim_y = 0) w_value = array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19.])] ITango [5]: # Write a scalar attribute ITango [6]: scalar_value = 18 ITango [7]: tangotest.write_attribute("long_scalar", scalar_value) ITango [8]: # Write a spectrum attribute ITango [9]: spectrum_value = numpy.random.rand(100)*10 ITango [10]: tangotest.write_attribute("double_spectrum", spectrum_value) ITango [11]: # Write an image attribute ITango [12]: image_value = numpy.random.randint(0,10,size=(10,10)) ITango [13]: tangotest.write_attribute("long_image", image_value)
Tip
If you are only interested in the attribute’s read value you can do insted:
ITango [1]: tangotest.long_scalar
Result [1]: 239
The same is valid for writting a new value to an attribute:
ITango [1]: tangotest.long_scalar = 18
Note
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.:
# Creating an unitialized double spectrum of 1000 elements
spectrum_value = PyTango.numpy_spectrum(PyTango.DevDouble, 1000)
# Creating an spectrum with a range
# Note that I do NOT use PyTango.DevLong here, BUT PyTango.NumpyType.DevLong
# numpy functions do not understand normal python types, so there's a
# translation available in PyTango.NumpyType
spectrum_value = numpy.arange(5, 1000, 2, PyTango.NumpyType.DevLong)
# Creating a 2x2 long image from an existing one
image_value = PyTango.numpy_image(PyTango.DevLong, [[1,2],[3,4]])
Defining devices in the Tango DataBase:
ITango [1]: # The 3 devices name we want to create ITango [2]: # Note: these 3 devices will be served by the same DServer ITango [3]: new_device_name1="px1/tdl/mouse1" ITango [4]: new_device_name2="px1/tdl/mouse2" ITango [5]: new_device_name3="px1/tdl/mouse3" ITango [6]: # Define the Tango Class served by this DServer ITango [7]: new_device_info_mouse = PyTango.DbDevInfo() ITango [8]: new_device_info_mouse._class = "Mouse" ITango [9]: new_device_info_mouse.server = "ds_Mouse/server_mouse" ITango [10]: # add the first device ITango [11]: new_device_info_mouse.name = new_device_name1 ITango [12]: db.add_device(new_device_info_mouse) ITango [13]: # add the next device ITango [14]: new_device_info_mouse.name = new_device_name2 ITango [15]: db.add_device(new_device_info_mouse) ITango [16]: # add the third device ITango [17]: new_device_info_mouse.name = new_device_name3 ITango [18]: db.add_device(new_device_info_mouse)
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.
ITango [1]: # connecting to the motor axis device ITango [2]: axis1 = DeviceProxy ("microxas/motorisation/galilbox") ITango [3]: # Getting Device Properties ITango [4]: property_names = ["AxisBoxAttachement", ....: "AxisEncoderType", ....: "AxisNumber", ....: "CurrentAcceleration", ....: "CurrentAccuracy", ....: "CurrentBacklash", ....: "CurrentDeceleration", ....: "CurrentDirection", ....: "CurrentMotionAccuracy", ....: "CurrentOvershoot", ....: "CurrentRetry", ....: "CurrentScale", ....: "CurrentSpeed", ....: "CurrentVelocity", ....: "EncoderMotorRatio", ....: "logging_level", ....: "logging_target", ....: "UserEncoderRatio", ....: "UserOffset"] ITango [5]: axis_properties = axis1.get_property(property_names) ITango [6]: for prop in axis_properties.keys(): ....: print "%s: %s" % (prop, axis_properties[prop][0]) ITango [7]: # Changing Properties ITango [8]: axis_properties["AxisBoxAttachement"] = ["microxas/motorisation/galilbox"] ITango [9]: axis_properties["AxisEncoderType"] = ["1"] ITango [10]: axis_properties["AxisNumber"] = ["6"] ITango [11]: axis1.put_property(axis_properties) ITango [12]: # Reading attributes ITango [13]: att_list = axis.get_attribute_list() ITango [14]: for att in att_list: ....: att_val = axis.read_attribute(att) ....: print "%s: %s" % (att.name, att_val.value) ITango [15]: # Changing some attribute values ITango [16]: axis1.write_attribute("AxisBackslash", 0.5) ITango [17]: axis1.write_attribute("AxisDirection", 1.0) ITango [18]: axis1.write_attribute("AxisVelocity", 1000.0) ITango [19]: axis1.write_attribute("AxisOvershoot", 500.0) ITango [20]: # Testing some device commands ITango [21]: pos1=axis1.read_attribute("AxisCurrentPosition") ITango [22]: axis1.command_inout("AxisBackward") ITango [23]: while pos1.value > 1000.0: ....: pos1 = axis1.read_attribute("AxisCurrentPosition") ....: print "position axis 1 = ", pos1.value ITango [24]: axis1.command_inout("AxisStop")
To write a tango device server in python, you must first import the PyTango module in your code.
Below is the python code for a Tango device server with two commands and two attributes. The commands are:
The attributes are:
The following code is the complete device server code:
import PyTango
class PyDsExp(PyTango.Device_4Impl):
def __init__(self,cl,name):
PyTango.Device_4Impl.__init__(self,cl,name)
self.debug_stream('In PyDsExp __init__')
PyDsExp.init_device(self)
def init_device(self):
self.debug_stream('In Python init_device method')
self.set_state(PyTango.DevState.ON)
self.attr_short_rw = 66
self.attr_long = 1246
def delete_device(self):
self.debug_stream('[delete_device] for device %s ' % self.get_name())
#------------------------------------------------------------------
# COMMANDS
#------------------------------------------------------------------
def is_IOLong_allowed(self):
return self.get_state() == PyTango.DevState.ON
def IOLong(self, in_data):
self.debug_stream('[IOLong::execute] received number %s' % str(in_data))
in_data = in_data * 2;
self.debug_stream('[IOLong::execute] return number %s' % str(in_data))
return in_data;
def is_IOStringArray_allowed(self):
return self.get_state() == PyTango.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.debug_stream('[IOStringArray::execute] received String' % in_data[out_index])
out_data.append(in_data[i])
self.debug_stream('[IOStringArray::execute] return String %s' %out_data[out_index])
out_index += 1
self.y = out_data
return out_data
#------------------------------------------------------------------
# ATTRIBUTES
#------------------------------------------------------------------
def read_attr_hardware(self, data):
self.debug_stream('In read_attr_hardware')
def read_Long_attr(self, the_att):
self.debug_stream('[PyDsExp::read_attr] attribute name Long_attr')
the_att.set_value(self.attr_long)
def read_Short_attr_rw(self, the_att):
self.debug_stream('[PyDsExp::read_attr] attribute name Short_attr_rw')
the_att.set_value(self.attr_short_rw)
def write_Short_attr_rw(self, the_att):
self.debug_stream('In write_Short_attr_rw for attribute %s' % the_att.get_name())
data = the_att.get_write_value()
self.attr_short_rw = data[0]
class PyDsExpClass(PyTango.DeviceClass):
def __init__(self, name):
PyTango.DeviceClass.__init__(self, name)
self.set_type("PyDsExp")
cmd_list = { 'IOLong' : [ [ PyTango.ArgType.DevLong, "Number" ],
[ PyTango.ArgType.DevLong, "Number * 2" ] ],
'IOStringArray' : [ [ PyTango.ArgType.DevVarStringArray, "Array of string" ],
[ PyTango.ArgType.DevVarStringArray, "This reversed array"] ],
}
attr_list = { 'Long_attr' : [ [ PyTango.ArgType.DevLong ,
PyTango.AttrDataFormat.SCALAR ,
PyTango.AttrWriteType.READ],
{ 'min alarm' : 1000, 'max alarm' : 1500 } ],
'Short_attr_rw' : [ [ PyTango.ArgType.DevShort,
PyTango.AttrDataFormat.SCALAR,
PyTango.AttrWriteType.READ_WRITE ] ]
}
def main():
PyTango.server_run({"PyDsExp" : (PyDsExpClass, PyDsExp)})
if __name__ == '__main__':
main()