• Added support for Windows. Support has a few caveats:

    • When using worker insights the arguments of the top 5 longest tasks are not available

    • Progress bar is not supported when using threading as start method

    • When using dill and an exception occurs, or when the exception occurs in an exit function, it can print additional OSError messages in the terminal, but these can be safely ignored.



  • Fixed a bug with newer versions of tqdm. The progress bar would throw an AttributeError when connected to a dashboard.

  • README and documentation updated



  • Workers now have their own task queue, which speeds up tasks with bigger payloads

  • Fixed progress bar showing error information when completed without error

  • Fixed progress bar and worker insights not displaying properly when using threading

  • Progress bar handling improved accross several scenarios

  • Dashboard can now handle progress bars when using spawn or forkserver as start method

  • Added closing of multiprocessing.JoinableQueue objects, to clean up intermediate junk

  • Removed numpy dependency

  • Made dill optional again. In many cases it slows processing down



  • Worker insights added, providing users insight in multiprocessing efficiency

  • worker_init and worker_exit parameters added to each map function

  • max_active_tasks is now set to n_jobs * 2 when max_active_tasks=None, to speed up most jobs

  • n_splits is now set to n_jobs * 64 when both chunk_size and n_splits are None

  • Dashboard ports can now be configured

  • Renamed func_pointer to func in each map function

  • Fixed a bug with the threading backend not terminating correctly

  • Fixed a bug with the progress bar not showing correctly in notebooks

  • Using multiprocess is now the default

  • Added some debug logging

  • Refactored a lot of code

  • Minor bug fixes, which should make things more stable.

  • Removed Python 3.5 support

  • Removed add_task, get_result, insert_poison_pill, stop_workers, and join functions from mpire.WorkerPool. Made start_workers private. There wasn’t any reason to use these functions.



  • Updated documentation CSS which fixes bullet lists not showing properly



  • Updated some unittests and fixed some linting issues

  • Minor improvements in documentation



  • Workers can be kept alive in between consecutive map calls

  • Setting CPU affinity is no longer restricted to Linux platforms

  • README updated to use RST format for better compatibility with PyPI

  • Added classifiers to the setup file



  • First public release on Github and PyPi



  • Added missing typing information

  • Updated some docstrings

  • Added license



  • Changed collections.Iterable to due to deprecation of the former



  • Removed custom progress bar support to fix Jupyter notebook support

  • New progress_bar_position parameter is now available to set the position of the progress bar when using nested worker pools

  • Screen resizing is now supported when using a progress bar



  • Added the MPIRE dashboard

  • Added threading as a possible backend

  • Progress bar handling now occurs in a separate process, instead of a thread, to improve responsiveness

  • Refactoring of code and small bug fixes in error handling

  • Removed deprecated functionality



  • Added support for using different start methods (‘spawn’ and ‘forkserver’) instead of only the default method ‘fork’

  • Added optional support for using dill in multiprocessing by utilizing the multiprocess library

  • The mpire.Worker class is no longer directly available



  • Fixed bug when process would hang when progress bar was set to True and an empty iterable was provided



  • Added support for worker state

  • Chunking numpy arrays is now done using numpy slicing

  • now supports automatic concatenation of numpy array output



  • Small bug fix when not passing on a boolean or tqdm object for the progress_bar parameter



  • You can now pass on a dictionary as an argument which will be unpacked accordingly using the **-operator.

  • New function mpire.utils.make_single_arguments() added which allows you to create an iterable of single argument tuples out of an iterable of single arguments



  • mpire.utils.chunk_tasks() is now available as a public function

  • Chunking in above function and map functions now accept a n_splits parameter

  • iterable_of_args in map functions can now contain single values instead of only iterables

  • tqdm is now available from the MPIRE package which automatically switches to the Jupyter/IPython notebook widget when available

  • Small bugfix in cleaning up a worker pool when no map function was called



  • Fixed a second bug where the main process could get unresponsive when an exception was raised



  • Fixed bug where sometimes exceptions fail to pickle

  • Fixed a bug where the main process could get unresponsive when an exception was raised

  • Child processes are now cleaned up in parallel when an exception was raised



  • restart_workers parameter is now deprecated and will be removed from v1.0.0

  • Progress bar functionality added (using tqdm)

  • Improved error handling in user provided functions

  • Fixed randomly occurring BrokenPipeErrors and deadlocks



  • Child processes can now also be pinned to a range of CPUs, instead of only a single one. You can also specify a single CPU or range of CPUs that have to be shared between all child processes



  • Added CPU pinning.

  • Default number of processes to spawn when using n_jobs=None is now set to the number of CPUs available, instead of cpu_count() - 1



  • Workers can now be started as normal child processes (non-deamon) such that nested mpire.WorkerPool s are possible





  • Added docs


First release