Skip to main content

Package to simplify process of parallelising tasks

Project description


Documentation Status AUR CircleCI

parallelize is a Python package to simplify the process of parallelising your taks in Python. It takes advantage of the multiprocessing module to spawn new processes for your job.


  • Python 3.X


To install parallelize, you can either install from the source code or using pip.

To install from source code, first clone the repository. Then, run python install in the root directory.


To build the documentation, run make html inside the docs/ folder. The documention will be found in the docs/build/html directory. Alternatively, view documentation here.


To parallelise a task in Python, you should wrap the entire code inside a function and have the first argument of your function receive the iterable your function will be operating over.

>>> from parallelize import parallelize
>>> def foo(iterable: list) -> int:
...    output = 0
...    for i in iterable:
...        output = i**4
...    return output

>>> numbers = list(range(50000000))
>>> %time foo(numbers)
Wall time: 21.5 s
>>> parallelize.parallel(foo, numbers, 6)
Completed 'parallel' in 6.2743 secs

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyparallelize-0.1.0.tar.gz (4.4 kB view hashes)

Uploaded source

Built Distribution

pyparallelize-0.1.0-py3-none-any.whl (5.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page