$npx skillfedfor your agent

pyepics

Epics Channel Access for Python

With conditionsPyPI Scientific/EngineeringReleased May 2026105.0K downloads / moPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — pyepics-3.5.10-py3-none-any.whl
v3.5.10 · released 2026-05-20 · Python >=3.10 · 2 runtime deps: numpy, pyparsing

Yes, if you work with EPICS control systems. The package is actively maintained, has low install friction, no known vulnerabilities, and provides a well-established interface to a standard scientific control protocol. Verify the Epics Open License terms for your use case before committing to a production deployment.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later.
  • EPICS Channel Access shared libraries are provided for Windows, MacOS, and Linux by default, but can be overridden via environment variable if you wish to use your own CA library versions.
  • Low install friction with a pure-Python wheel distribution.

License · maintenance · safety

(unclear) — License treatment is unclear in the metadata; the package description states it is distributed under the Epics Open License, but this is not formally declared in standard SPDX or license_raw fields. Verify the actual license terms before use in proprietary or restricted contexts.

last release 2026-05-20 (86 days) · last repo commit 2026-08-12 · 113 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 104,965 downloads/mo, #12,729 on PyPI

Verify before relying

pip install pyepics

from epics import caget, caput, cainfo
value = caget('XXX:m1.VAL')
caput('XXX:m1.VAL', 2.30)
cainfo('XXX:m1.VAL')
  • Whether the Epics Open License is compatible with your project's licensing requirements (not formally declared in package metadata).
  • Whether wxPython widget integration mentioned in the description is actively maintained and documented.
  • Support status for Python 3.13 and 3.14, which appear in classifiers but are beyond the stated 3.8-3.12 testing range.
Same gist for agents: .md · .json

What it is and what it does

PyEpics is a Python wrapper around the EPICS Channel Access (CA) protocol, a standard for controlling scientific instruments and distributed systems in research facilities. It uses ctypes to bind the underlying C library, avoiding the need for compiled C extensions while maintaining thread safety and cross-platform compatibility.

The package offers two main interfaces: simple procedural functions (caget, caput, cainfo) for quick queries, and an object-oriented PV class for sustained interaction with process variables. It handles connection management transparently, supports user callbacks when values or connection status change, and provides access to full control records and enumeration strings. It is actively maintained and supports modern Python versions.

Use it for

  • Query and modify EPICS process variables from Python scripts in scientific or accelerator control environments.
  • Monitor EPICS PV changes in real time using callback functions to trigger actions when values or connection status change.
  • Build Python-based control applications that interact with EPICS motors, detectors, and other instrumentation.
  • Integrate EPICS data acquisition into data analysis pipelines alongside numpy and other scientific tools.
  • Automate routine operations on EPICS systems without writing C code or using command-line utilities.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you work with EPICS control systems.

The package is actively maintained, has low install friction, no known vulnerabilities, and provides a well-established interface to a standard scientific control protocol. Verify the Epics Open License terms for your use case before committing to a production deployment.

Install

pyepics on PyPI

Before you install

Low install friction with a pure-Python wheel distribution. Maintenance is active with a recent release (86 days ago) and ongoing repository activity. Runtime dependencies are minimal: numpy and pyparsing.

Requires Python 3.10 or later. EPICS Channel Access shared libraries are provided for Windows, MacOS, and Linux by default, but can be overridden via environment variable if you wish to use your own CA library versions.

License in practice

License treatment is unclear in the metadata; the package description states it is distributed under the Epics Open License, but this is not formally declared in standard SPDX or license_raw fields. Verify the actual license terms before use in proprietary or restricted contexts.

Quickstart

pip install pyepics

from epics import caget, caput, cainfo
value = caget('XXX:m1.VAL')
caput('XXX:m1.VAL', 2.30)
cainfo('XXX:m1.VAL')

Verify before relying

  • Whether the Epics Open License is compatible with your project's licensing requirements (not formally declared in package metadata).
  • Whether wxPython widget integration mentioned in the description is actively maintained and documented.
  • Support status for Python 3.13 and 3.14, which appear in classifiers but are beyond the stated 3.8-3.12 testing range.

Package facts

LicenseNot declared unclear
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependencies
2 packages
numpypyparsing
MaintenanceActively maintained 86 days since the last release
Last repo commit
First released
Downloads104,965 / month, #12,729 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/Engineering

Evidence: pyepics-3.5.10-py3-none-any.whl

Tags

Capabilities
epics channel access pythonepics control system interfaceread write epics process variablesepics pv python wrapperepics ca library pythonepics monitoring callbacksepics motor control python
Topics
epics-control-systemsscientific-instrumentationhardware-interface
PyPI keywords
epics

Let your AI agent find packages like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.

wish › “epics channel access python”

  • pyepicsPyEpics provides a Python interface to the EPICS Channel Access…
  • epicscorelibsProvides compiled EPICS Core libraries and development headers for…
  • phoebusgenGenerates Phoebus Display Builder XML format programmatically from…

Give your agent the search over MCP, or paste the wish link into any chat.

More Scientific/Engineering packages

numpy Worth it
PyPI · Software Development · released Aug 2026

NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.

BSD-3-Clause AND 0BSD AND MIT AND Zlib AND CC0-1.0compiled wheel · 3.12+
1.1Bdownloads / mo
pandas Worth it
PyPI · Scientific/Engineering · released Jul 2026

pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.

BSD-3-Clausecompiled wheel · 3.11+
769.1Mdownloads / mo
scipy Worth it
PyPI · Libraries · released Jun 2026

scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.

BSD-3-Clausecompiled wheel · 3.12+
449.0Mdownloads / mo
scikit-learn Worth it
PyPI · Software Development · released Jun 2026

scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.

Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.

BSD-3-Clausecompiled wheel · 3.11+
235.5Mdownloads / mo
dill Worth it
PyPI · Software Development · released Jan 2026

dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.

BSD-3-Clausepure Python · 3.9+
208.1Mdownloads / mo
multiprocess Worth it
PyPI · Software Development · released Jan 2026

Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.

Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.

BSD-3-Clausepure Python · 3.9+
202.7Mdownloads / mo

See also epicscorelibs · ophyd · phoebusgen · epik8s-tools · ophyd-async · pyemvue · wincertstore · mscerts · pyasn1