Calculate the number of CPUs available taking into account system constraints
Project description
cpu_count
Modified version of python's cpu_count
that takes into account system
constraints to calculate the number of available CPUs
Motivation
The Python standard library offers an implementation of cpu_count that returns
the real number of CPUs even when they are not actually available to be used by
the python process (due to constraints such as CPU affinity or CPU scheduler
configurations). This is the preferred behaviour for most applications. However,
when the interest is the amount of CPUs available for data processing, that
approach could be misleading. Especially when it is used behind the scenes such
as by the concurrent.futures.Executor
when defining its defaults.
The purpose of this module is to provide this functionality in an API equal to the standard implementation. By taking into account the described constraints, this implementation attempts to return the amount of usable CPUs that are available. If no constraint is identified the result will be the same as the standard implementation.
How to install
pip install cpu_count
How to use
As an external module
This is the standard way. Just import and call cpu_count
from cpu_count import cpu_count
print(cpu_count())
# $> 8
Monkey-patch standard lib
This an alternative way that replaces python's standard cpu_count
with the
one from this module (Affected internal modules are posix
, os
and
multiprocessing
). The advantage of this approach is not needing to port any
code, just import and call setup_monkey_patch
ate the begin of your
application and everything will just work™.
Note: This will also have implications in the behaviour of standard libraries that use this function
import os
from cpu_count.monkey_patch import setup_monkey_patch
print(os.cpu_count())
# $> 12
setup_monkey_patch()
print(os.cpu_count())
# $> 8
Limitation
This approach has one limitation: it can't replace previous code that
imported the standard implementation using from os import cpu_count
.
from os import cpu_count
from cpu_count.monkey_patch import setup_monkey_patch
print(cpu_count())
# $> 12
setup_monkey_patch()
print(cpu_count())
# $> 12
System wide monkey-patch
This approach also replaces python's standard cpu_count
. However instead of
calling this module's setup_monkey_patch
in your application code, it will be
called at python startup. For this to work you need to create a file called
cpu_count_monkey_patch.pth
at your python's global or local site-package's
folder with the following content:
import cpu_count; cpu_count.monkey_patch.setup_monkey_patch()
NOTE: This approach is specially useful when creating container images of python applications. An example of using this on a Dockerfile can be found here
TODO
- Add logic for Realtime Scheduler constraint
- Create unit tests
Contributions
All contributions are very welcome.
Code styles is defined in the Editorconfig file. Besides that I use black and isort for auto-format, their configurations are defined in the Editorconfig and the black.toml files respectively.
License
BSD 3-Clause “New” or “Revised” License
See LICENSE
Project details
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