Simple interface to Linux process information
The Python package proc exposes process information available in the Linux process information pseudo-file system available at /proc. The proc package is currently tested on cPython 2.6, 2.7, 3.4, 3.5 and PyPy (2.7). The automated test suite regularly runs on Ubuntu Linux but other Linux variants (also those not based on Debian Linux) should work fine. For usage instructions please refer to the documentation.
The proc package is available on PyPI which means installation should be as simple as:
$ pip install proc
There’s actually a multitude of ways to install Python packages (e.g. the per user site-packages directory, virtual environments or just installing system wide) and I have no intention of getting into that discussion here, so if this intimidates you then read up on your options before returning to these instructions ;-).
Once you’ve installed the proc package head over to the documentation for some examples of how the proc package can be used.
The proc package was created with the following considerations in mind:
- Completely specialized to Linux
- It parses /proc and nothing else ;-).
- Fully implemented in Python
- No binary/compiled components, as opposed to psutil which is way more portable but requires a compiler for installation.
- Very well documented
- The documentation should make it easy to get started (as opposed to procfs which I evaluated and eventually gave up on because I had to resort to reading through its source code just to be disappointed in its implementation).
- Robust implementation
- Reading /proc is inherently sensitive to race conditions and the proc package takes this into account, in fact the test suite contains a test that creates race conditions in order to verify that they are handled correctly. The API of the proc package hides race conditions as much as possible and where this is not possible the consequences are clearly documented.
- Layered API design (where each layer is documented)
Builds higher level abstractions on top of lower level abstractions:
- The proc.unix module
- Defines a simple process class that combines process IDs and common UNIX signals to implement process control primitives like waiting for a process to end and gracefully or forcefully terminating a process.
- The proc.core module
- Builds on top of the proc.unix module to provide a simple, fast and easy to use API for the process information available in /proc. If you’re looking for a simple and/or fast interface to /proc that does the heavy lifting (parsing) for you then this is what you’re looking for.
- The proc.tree module
- Builds on top of the proc.core module to provide an in-memory tree data structure that mimics the actual process tree, enabling easy searching and navigation through the process tree.
- The proc.apache module
- Builds on top of the proc.tree module to implement an easy to use Python API that does metrics collection for monitoring of Apache web server worker memory usage, including support for WSGI process groups.
- The proc.cron module
- Implements the command line program cron-graceful which gracefully terminates cron daemons. This module builds on top of the proc.tree module as a demonstration of the possibilities of the proc package and as a practical tool that is ready to be used on any Linux system that has Python and cron installed.
- The proc.notify module
- Implements the command line program notify-send-headless which can be used to run the program notify-send in headless environments like cron jobs and system daemons.
I’ve been writing shell and Python scripts that parse /proc for years now (it seems so temptingly easy when you get started ;-). Sometimes I resorted to copy/pasting snippets of Python code between personal and work projects because the code was basically done, just not available in an easy to share form.
Once I started fixing bugs in diverging copies of that code I decided it was time to combine all of the features I’d grown to appreciate into a single well tested and well documented Python package with an easy to use API and share it with the world.
This means that, although I made my first commit on the proc package in March 2015, much of its code has existed for years in various forms.
Below are several other Python libraries that expose process information. If the proc package isn’t working out for you consider trying one of these. The summaries are copied and/or paraphrased from the documentation of each package:
- A cross-platform library for retrieving information on running processes and system utilization (CPU, memory, disks, network) in Python.
- A Python wrapper for the procps library and a module containing higher level classes (with some extensions compared to procps).
- Python API for the Linux /proc virtual filesystem.
The latest version of proc is available on PyPI and GitHub. The documentation is hosted on Read the Docs and includes a changelog. For bug reports please create an issue on GitHub. If you have questions, suggestions, etc. feel free to send me an e-mail at email@example.com.
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