mpire 1.2.0

A Python package for easy multiprocessing, but faster than multiprocessing

MPIRE is a Python package for multiprocessing, but faster and more user-friendly than the default multiprocessing package. It combines the convenient map like functions of multiprocessing.Pool with the benefits of using copy-on-write shared objects of multiprocessing.Process.

Full documentation is available at https://slimmer-ai.github.io/mpire/.

Features

• Multiprocessing with map/map_unordered/imap/imap_unordered functions

• Easy use of copy-on-write shared objects with a pool of workers

• Each worker can have its own state (e.g., to load a memory-intensive model only once for each worker without the need of sending it through a queue)

• Automatic task chunking for all available map functions to speed up processing of small task queues (including numpy arrays)

• Adjustable maximum number of active tasks to avoid memory problems

• Automatic restarting of workers after a specified number of tasks to reduce memory footprint

• Nested pool of workers are allowed when setting the daemon option

• Child processes can be pinned to specific or a range of CPUs

• Multiple process start methods available, including: fork (default), forkserver, spawn, and threading

• Progress bar support using tqdm

• Progress dashboard support

• (Optional) dill support

Installation

Through pip (PyPi):

pip install mpire

From source:

python setup.py install

Documentation

If you want to build the documentation, please install the documentation dependencies by executing:

pip install mpire[docs]

or

pip install .[docs]

Documentation can then be build by executing:

python setup.py build_docs

Documentation can also be build from the docs folder directly. In that case MPIRE should be installed and available in your current working environment. Then execute:

make html

in the docs folder.