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 primary goal is to understand those algorithms and the best way to do that is to code 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:

$ python check --restructuredtext
$ # change version in
$ git add
$ git commit -m "Bump version to 1.0.0"
$ git tag v1.0.0
$ git push origin master && git push origin --tags
$ git push gitlab master && git push gitlab --tags
$ python bdist_wheel
$ 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.

Filename, size & hash SHA256 hash help File type Python version Upload date
algos_py-0.4.4-py3-none-any.whl (34.6 kB) Copy SHA256 hash SHA256 Wheel py3

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page