Skip to main content

Classic computer science algorithms in Python

Project description

What is algos-py?

This package contains implementations of some classic computer science algorithms. My main goal is to understand these algorithms and the best way to do that is to implement them myself.

Along the way I practice test driven development (with pytest), continuous integration (with travis and appveyor), coverage tracking (with coveralls and codecov), version control (with git, github and gitlab), documentation (with sphinx and readthedocs) and a lot more.

How to test?

To run all of the unit-tests:

$ pytest -n 2

To run unit-tests for a specific module:

$ pytest ./tests/

To run all the unit-tests and produce a coverage report:

$ pytest -n 2 --cov=src

Where to find?

Primary repository:

Secondary (mirror) repository:

Release procedure:

$ # change version in
$ git add
$ git commit -m "Bump version to 1.0.0"
$ git tag v1.0.0
$ git push github main && git push github --tags
$ git push gitlab main && git push gitlab --tags
$ pip install --upgrade wheel
$ python bdist_wheel
$ pip install --upgrade twine
$ twine check ./dist/algos_py-1.0.0-py3-none-any.whl
$ twine upload ./dist/algos_py-1.0.0-py3-none-any.whl

Project details

Download files

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

Built Distribution

algos_py-0.5.1-py3-none-any.whl (37.1 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