loky 2.1.0

A robust implementation of concurrent.futures.ProcessPoolExecutor

Reusable Process Pool Executor
==============================
|Build Status| |Build status| |codecov|


Goal
~~~~

The aim of this project is to provide a robust, cross-platform and
cross-version implementation of the :class:`~concurrent.futures.ProcessPoolExecutor` class of
:mod:`concurrent.futures`. It notably features:

- **Deadlock free implementation**: one of the major concern in standard :class:`multiprocessing.pool.Pool` and in :class:`concurrent.futures.ProcessPoolExecutor` is their ability to handle crashes of worker processes. This library intends to fix those possible deadlocks and send back meaningful errors.

- **Consistent spawn behavior**: All processes are started using fork/exec on POSIX systems. This ensures safer interactions with third party libraries.

- **Reusable executor**: strategy to avoid re-spawning a complete executor every time. A singleton executor instance can be reused (and dynamically resized if necessary) across consecutive calls to limit spawning and shutdown overhead. The worker processes can be shutdown automatically after a configurable idling timeout to free system resources.

- **Transparent :mod:`cloudpickle` integration**: to call interactively defined functions and lambda expressions in parallel. It is also possible to register a custom pickler implementation to handle inter-process communications.

- **No need for ``if __name__ == "__main__":`` in scripts**: thanks to the use of :mod:`cloudpickle <https://github.com/cloudpipe/cloudpickle>` to call functions defined in the :mod:`__main__` module, it is not required to protect the code calling parallel functions under Windows.

Usage
~~~~~

The basic usage of :mod:`loky` relies on the :func:`~loky.get_reusable_executor`, which internally manages a custom :class:`~concurrent.futures.ProcessPoolExecutor` object, which is reused or re-spawned depending on the context.

.. code:: python

import os
from time import sleep
from loky import get_reusable_executor


def say_hello(k):
pid = os.getpid()
print("Hello from {} with arg {}".format(pid, k))
sleep(.01)
return pid


# Create an executor with 4 worker processes, that will
# automatically shutdown after idling for 2s
executor = get_reusable_executor(max_workers=4, timeout=2)

res = executor.submit(say_hello, 1)
print("Got results:", res.result())

results = executor.map(say_hello, range(50))
n_workers = len(set(results))
print("Number of used processes:", n_workers)
assert n_workers == 4


Acknowledgement
~~~~~~~~~~~~~~~

This work is supported by the Center for Data Science, funded by the
IDEX Paris-Saclay, ANR-11-IDEX-0003-02


.. |Build Status| image:: https://travis-ci.org/tomMoral/loky.svg?branch=master
:target: https://travis-ci.org/tomMoral/loky
.. |Build status| image:: https://ci.appveyor.com/api/projects/status/oifqilb5sb0p7fdp/branch/master?svg=true
:target: https://ci.appveyor.com/project/tomMoral/loky/branch/master
.. |codecov| image:: https://codecov.io/gh/tomMoral/loky/branch/master/graph/badge.svg
:target: https://codecov.io/gh/tomMoral/loky

.. _cloudpickle: https://github.com/cloudpipe/cloudpickle