PyEpics Overview¶

The python epics package provides several function, modules, and classes to interact with EPICS Channel Access. The simplest approach uses the functions caget(), caput(), and cainfo() within the top-level epics module to get and put values of Epics Process Variables. These functions are similar to the standard command line utilities and the EZCA library interface, and are described in more detail below.

To use the epics package, import it with:

import epics

The main components of this module include

functions caget(), caput(), cainfo() and others described in more detail below.

a ca module, providing the low-level library as a set of functions, meant to be very close to the C library for Channel Access.

a PV object, representing a Process Variable (PV) and giving a higher-level interface to Epics Channel Access.

a Device object: a collection of related PVs, similar to an Epics Record.

a Motor object: a Device that represents an Epics Motor.

an Alarm object, which can be used to set up notifications when a PV’s values goes outside an acceptable bounds.

an epics.wx module that provides wxPython classes designed for use with Epics PVs.

If you’re looking to write quick scripts or a simple introduction to using Channel Access, the caget() and caput() functions are probably where you want to start.

If you’re building larger scripts and programs, using PV objects is recommended. The PV class provides a Process Variable (PV) object that has methods (including get() and put()) to read and change the PV, and attributes that are kept automatically synchronized with the remote channel. For larger applications where you find yourself working with sets of related PVs, you may find the Device class helpful.

The lowest-level CA functionality is exposed in the ca module, and companion dbr module. While not necessary recommended for most use cases, this module does provide a fairly complete wrapping of the basic EPICS CA library. For people who have used CA from C or other languages, this module should be familiar and seem quite usable, if a little more verbose and C-like than using PV objects.

In addition, the epics package contains more specialized modules for alarms, Epics motors, and several other devices (collections of PVs), and a set of wxPython widget classes for using EPICS PVs with wxPython.

The epics package is supported and well-tested on Linux, Mac OS X, and Windows with Python versions 2.7, and 3.5 and above.

Quick Start¶

Whether you’re familiar with Epics Channel Access or not, start here. You’ll then be able to use Python’s introspection tools and built-in help system, and the rest of this document as a reference and for detailed discussions.

Procedural Approach: caget(), caput()¶

To get values from PVs, you can use the caget() function:

>>> from epics import caget, caput, cainfo
>>> m1 = caget('XXX:m1.VAL')
>>> print(m1)
1.2001

To set PV values, you can use the caput() function:

>>> caput('XXX:m1.VAL', 1.90)
>>> print(caget('XXX:m1.VAL'))
1.9000

To see more detailed information about a PV, use the cainfo() function:

>>> cainfo('XXX:m1.VAL')
== XXX:m1.VAL  (time_double) ==
   value      = 1.9
   char_value = '1.9000'
   count      = 1
   nelm       = 1
   type       = time_double
   units      = mm
   precision  = 4
   host       = somehost.aps.anl.gov:5064
   access     = read/write
   status     = 0
   severity   = 0
   timestamp  = 1513352940.872 (2017-12-15 09:49:00.87179)
   posixseconds        = 1513352940.0
   nanoseconds= 871788105
   upper_ctrl_limit    = 50.0
   lower_ctrl_limit    = -48.0
   upper_disp_limit    = 50.0
   lower_disp_limit    = -48.0
   upper_alarm_limit   = 0.0
   lower_alarm_limit   = 0.0
   upper_warning_limit = 0.0
   lower_warning_limit = 0.0
   PV is internally monitored, with 0 user-defined callbacks:
=============================

The simplicity and clarity of these functions make them ideal for many uses.

Creating and Using PV Objects¶

If you are repeatedly referencing the same PV, you may find it more convenient to create a PV object and use it in a more object-oriented manner.

>>> from epics import PV
>>> pv1 = PV('XXX:m1.VAL')

PV objects have several methods and attributes. The most important methods are get() and put() to receive and send the PV’s value, and the value attribute which stores the current value. In analogy to the caget() and caput() examples above, the value of a PV can be fetched either with

>>> print(pv1.get())
1.90

or

>>> print(pv1.value)
1.90

To set a PV’s value, you can either use

>>> pv1.put(1.9)

or assign the value attribute

>>> pv1.value = 1.9

You can see a few of the most important properties of a PV by simply printing it:

>>> print(pv1)
<PV 'XXX:m1.VAL', count=1, type=time_double, access=read/write>

More complete information can be seen by printing the PVs info attribute:

>>> print(pv1.info)
== XXX:m1.VAL  (time_double) ==
   value      = 1.9
   char_value = '1.9000'
   count      = 1
   nelm       = 1
   type       = time_double
   units      = mm
   precision  = 4
   host       = somehost.aps.anl.gov:5064
   access     = read/write
   status     = 0
   severity   = 0
   timestamp  = 1513352940.872 (2017-12-15 09:49:00.87179)
   posixseconds        = 1513352940.0
   nanoseconds= 871788105
   upper_ctrl_limit    = 50.0
   lower_ctrl_limit    = -48.0
   upper_disp_limit    = 50.0
   lower_disp_limit    = -48.0
   upper_alarm_limit   = 0.0
   lower_alarm_limit   = 0.0
   upper_warning_limit = 0.0
   lower_warning_limit = 0.0
   PV is internally monitored, with 0 user-defined callbacks:
=============================

PV objects have several additional methods related to monitoring changes to the PV values or connection state including user-defined functions to be run when the value changes. There are also attributes associated with a PVs Control Attributes, like those shown above in the info attribute. Further details are at PV: Epics Process Variables.

Simple `epics` functions: caget(), caput(), etc.¶

As shown above, the simplest interface to EPICS Channel Access is found with the functions caget(), caput(), and cainfo(). There are also functions camonitor() and camonitor_clear() to setup and clear a simple monitoring of changes to a PV. These functions all take the name of an Epics Process Variable (PV) as the first argument and are similar to the EPICS command line utilities of the same names.

Internally, these functions keeps a cache of connected PV (in this case, using PV objects) so that repeated use of a PV name will not actually result in a new connection to the PV – see The get_pv() function and _PVcache_ cache of PVs for more details. Thus, though the functionality is simple and straightforward, the performance of using thes simple function can be quite good. In addition, there are also functions caget_many() and caput_many() for getting and putting values for multiple PVs at a time.

`caget()`¶

epics.caget(pvname[, as_string=False[, count=None[, as_numpy=True[, timeout=None[, use_monitor=True]]]]])¶

retrieves and returns the value of the named PV.

Parameters:

pvname – name of Epics Process Variable.
as_string (True/False) – whether to return string representation of the PV value.
count (integer or None) – number of elements to return for array data.
as_numpy (True/False) – whether to return the Numerical Python representation for array data.
timeout (float or None) – maximum time to wait (in seconds) for value before returning None.
use_monitor (True/False) – whether to rely on monitor callbacks or explicitly get value now.

The count and as_numpy options apply only to array or waveform data. The default behavior is to return the full data array and convert to a numpy array if available. The count option can be used to explicitly limit the number of array elements returned, and as_numpy can turn on or off conversion to a numpy array.

The timeout argument sets the maximum time to wait for a value to be fetched over the network. If the timeout is exceeded, caget() will return None. This might imply that the PV is not actually available, but it might also mean that the data is large or network slow enough that the data just hasn’t been received yet, but may show up later.

The use_monitor argument sets whether to rely on the monitors from the underlying PV. The default is True, so that cached values will be used. Using False will make the each caget() explicitly ask the value to be sent instead of relying on the automatic monitoring normally used for persistent PVs. This will make caget() act more like command-line tools, and slightly less efficient than creating a PV and getting values with it. If performance is a concern, using monitors is recommended. For more details on making caget() more efficient, see Automatic Monitoring of a PV and The wait and timeout options for get(), ca.get_complete().

The as_string argument tells the function to return the string representation of the value. The details of the string representation depends on the variable type of the PV. For integer (short or long) and string PVs, the string representation is pretty easy: 0 will become ‘0’, for example. For float and doubles, the internal precision of the PV is used to format the string value. For enum types, the name of the enum state is returned:

>>> from epics import caget, caput, cainfo
>>> print(caget('XXX:m1.VAL'))     # A double PV
0.10000000000000001

>>> print(caget('XXX:m1.DESC'))    # A string PV
'Motor 1'
>>> print(caget('XXX:m1.FOFF'))    # An Enum PV
1

Adding the as_string=True argument always results in string being returned, with the conversion method depending on the data type, for example using the precision field of a double PV to determine how to format the string, or using the names of the enumeration states for an enum PV:

>>> print(caget('XXX:m1.VAL', as_string=True))
'0.10000'

>>> print(caget('XXX:m1.FOFF', as_string=True))
'Frozen'

For integer or double array data from Epics waveform records, the regular value will be a numpy array (or a python list if numpy is not installed). The string representation will be something like ‘<array size=128, type=int>’ depending on the size and type of the waveform. An array of doubles might be:

>>> print(caget('XXX:scan1.P1PA'))  # A Double Waveform
array([-0.08      , -0.078     , -0.076     , ...,
    1.99599814, 1.99799919,  2.     ])

>>> print(caget('XXX:scan1.P1PA', as_string=True))
'<array size=2000, type=time_double>'

As an important special case CHAR waveform records will be turned to Python strings when as_string is True. This is useful to work around the low limit of the maximum length (40 characters!) of EPICS strings which has inspired the fairly common usage of CHAR waveforms to represent longer strings:

>>> epics.caget('MyAD:TIFF1:FilePath')
array([ 47, 104, 111, 109, 101,  47, 101, 112, 105,  99, 115,  47, 115,
        99, 114,  97, 116,  99, 104,  47,   0], dtype=uint8)
>>> epics.caget('MyAD:TIFF1:FilePath', as_string=True)
'/home/epics/scratch/'

Of course,character waveforms are not always used for long strings, but can also hold byte array data, such as may come from some detectors and devices.

`caput()`¶

epics.caput(pvname, value[, wait=False[, timeout=60]])¶

set the value of the named PV.

Parameters:

pvname – name of Epics Process Variable
value – value to send.
wait (True/False) – whether to wait until the processing has completed.
timeout (double) – how long to wait (in seconds) for put to complete before giving up.

Return type:

integer

The optional wait argument tells the function to wait until the processing completes. This can be useful for PVs which take significant time to complete, either because it causes a physical device (motor, valve, etc) to move or because it triggers a complex calculation or data processing sequence. The timeout argument gives the maximum time to wait, in seconds. The function will return after this (approximate) time even if the caput() has not completed.

This function returns 1 on success. It will return None if the timeout has been exceeded.

>>> from epics import caget, caput, cainfo
>>> caput('XXX:m1.VAL',2.30)
1
>>> caput('XXX:m1.VAL',-2.30, wait=True)
... waits a few seconds ...

`cainfo()`¶

epics.cainfo(pvname[, print_out=True])¶

prints (or returns as a string) an informational paragraph about the PV, including Control Settings.

Parameters:

pvname – name of Epics Process Variable
print_out – whether to write results to standard output (otherwise the string is returned).

`camonitor()`¶

epics.camonitor(pvname[, writer=None[, callback=None]])¶

This sets a monitor on the named PV, which will cause something to be done each time the value changes. By default the PV name, time, and value will be printed out (to standard output) when the value changes, but the action that actually happens can be customized.

Parameters:

pvname – name of Epics Process Variable
writer (None or a callable function that takes a string argument.) – where to write results to standard output .
callback (None or callable function) – user-supplied function to receive result

One can specify any function that can take a string as writer, such as the write() method of an open file that has been open for writing. If left as None, messages of changes will be sent to sys.stdout.write(). For more complete control, one can specify a callback function to be called on each change event. This callback should take keyword arguments for pvname, value, and char_value. See User-supplied Callback functions for information on writing callback functions for camonitor().

>>> from epics import camonitor
>>> camonitor('XXX.m1.VAL')
XXX.m1.VAL 2010-08-01 10:34:15.822452 1.3
XXX.m1.VAL 2010-08-01 10:34:16.823233 1.2
XXX.m1.VAL 2010-08-01 10:34:17.823233 1.1
XXX.m1.VAL 2010-08-01 10:34:18.823233 1.0

`camonitor_clear()`¶

epics.camonitor_clear(pvname)¶

clears a monitor set on the named PV by camonitor().

Parameters:: pvname – name of Epics Process Variable

This simple example monitors a PV with camonitor() for while, with changes being saved to a log file. After a while, the monitor is cleared and the log file is inspected:

>>> import epics
>>> fh = open('PV1.log','w')
>>> epics.camonitor('XXX:DMM1Ch2_calc.VAL',writer=fh.write)
>>> .... wait for changes ...
>>> epics.camonitor_clear('XXX:DMM1Ch2_calc.VAL')
>>> fh.close()
>>> fh = open('PV1.log','r')
>>> for i in fh.readlines(): print(i[:-1])
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:40.536946 -183.5035
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:41.536757 -183.6716
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:42.535568 -183.5112
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:43.535379 -183.5466
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:44.535191 -183.4890
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:45.535001 -183.5066
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:46.535813 -183.5085
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:47.536623 -183.5223
 XXX:DMM1Ch2_calc.VAL 2010-03-24 11:56:48.536434 -183.6832

`caget_many()`¶

epics.caget_many(pvlist[, as_string=False[, count=None[, as_numpy=True[, timeout=None]]]])¶

get a list of PVs as quickly as possible. Returns a list of values for each PV in the list. Unlike caget(), this method does not use automatic monitoring (see Automatic Monitoring of a PV).

Parameters:

pvlist (list or tuple of str) – A list of process variable names.
as_string (True/False) – whether to return string representation of the PV values.
count (integer or None) – number of elements to return for array data.
as_numpy (True/False) – whether to return the Numerical Python representation for array data.
timeout (float or None) – maximum time to wait (in seconds) for value before returning None.

For detailed information about the arguments, see the documentation for caget(). Also see Strategies for connecting to a large number of PVs for more discussion.

`caput_many()`¶

epics.caput_many(pvlist, values[, wait=False[, connection_timeout=None[, put_timeout=60]]])¶

put values to a list of PVs as quickly as possible. Returns a list of ints for each PV in the list: 1 if the put was successful, -1 if it timed out. Unlike caput(), this method does not use automatic monitoring (see Automatic Monitoring of a PV).

Parameters:

pvlist (list or tuple of str) – A list of process variable names.
values (list or tuple) – values to put to each PV.
wait – if 'each', caput_many() will wait for each PV to process before starting the next. If 'all', caput_many() will issue puts for all PVs immediately, then wait for all of them to complete. If any other value, caput_many() will not wait for put processing to complete.
connection_timeout (float or None) – maximum time to wait (in seconds) for a connection to be established to each PV.
put_timeout (float or None) – maximum time to wait (in seconds) for processing to complete for each PV (if wait is 'each'), or for processing to complete for all PVs (if wait is 'all').

Because connections to channels normally connect very quickly (less than a second), but processing a put may take a significant amount of time (due to a physical device moving, or due to complex calculations or data processing sequences), a separate timeout duration can be specified for connections and processing puts.

Motivation and design concepts¶

There are other Python wrappings for Epics Channel Access, so it it useful to outline the design goals for PyEpics. The motivations for PyEpics3 included:

providing both low-level (C-like) and higher-level access (Python objects) to the EPICS Channel Access protocol.

supporting as many features of Epics 3.14 and greater as possible, including preemptive callbacks and thread support.

easy support and distribution for Windows and Unix-like systems.

support for both Python 2 (now no longer supported) and Python 3.

using Python’s ctypes library.

The idea is to provide both a low-level interface to Epics Channel Access (CA) that closely resembled the C interface to CA, and to build higher level functionality and complex objects on top of that foundation. The Python ctypes library conveniently allows such direct wrapping of a shared libraries, and requires no compiled code for the bridge between Python and the CA library. This makes it very easy to wrap essentially all of CA from Python code, and support multiple platforms. Since ctypes loads a shared object library at runtime, the underlying CA library can be upgraded without having to re-build the Python wrapper. The ctypes interface provides the most reliable thread-safety available, as each call to the underlying C library is automatically made thread-aware without explicit code. Finally, by avoiding the C API altogether, supporting both Python2 and Python3 is greatly simplified.

Status¶

The PyEpics package is actively maintained, but the core library is reasonably stable and ready to use in production code. Features are being added slowly, and testing is integrated into development so that the chance of introducing bugs into existing codes is minimized. The package is targeted and tested to work on all supported versions of Python, currently Python 3.6 and higher.

Table of Contents

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This Page

PyEpics Overview¶

Quick Start¶

Procedural Approach: caget(), caput()¶

Creating and Using PV Objects¶

Simple `epics` functions: caget(), caput(), etc.¶

`caget()`¶

`caput()`¶

`cainfo()`¶

`camonitor()`¶

`camonitor_clear()`¶

`caget_many()`¶

`caput_many()`¶

Motivation and design concepts¶

Status¶

PyEpics Overview¶

Quick Start¶

Procedural Approach: caget(), caput()¶

Creating and Using PV Objects¶

Simple epics functions: caget(), caput(), etc.¶

Motivation and design concepts¶

Status¶

Simple `epics` functions: caget(), caput(), etc.¶