Top 10 Must‑Try Python Open‑Source Projects (April 2018)

Continuing the holiday charging series, Mybridge selected ten Python open‑source projects with an average of 2,135 GitHub stars.

Rank 1: Requests‑HTML v0.9 (7,385 stars on GitHub, by Kenneth Reitz)

This library aims to parse HTML as simply and intuitively as possible, supporting only Python 3.6.

Project URL: https://github.com/kennethreitz/requests-html

Rank 2: PyTest v3.5 (2,453 stars on GitHub, by pytest‑dev)

An extensible Python framework that makes writing small tests easy and supports more complex functional testing.

Project URL: https://github.com/pytest-dev/pytest

Rank 3: Lector (327 stars on GitHub, by BasioMeusPuga)

A Qt‑based e‑book reader.

Project URL: https://github.com/BasioMeusPuga/Lector

Rank 4: Asciinema v2.0 (5,491 stars on GitHub, by Asciinema)

A terminal session recorder written in Python.

Project URL: https://github.com/asciinema/asciinema

Rank 5: Snips‑nlu v0.13 (1,416 stars on GitHub, by Snips)

A Python library that parses natural‑language sentences and extracts structured information.

Project URL: https://github.com/snipsco/snips-nlu

Rank 6: Black (1,665 stars on GitHub, by Łukasz Langa)

A Python code formatter.

Project URL: https://github.com/ambv/black

Rank 7: Instagram‑terminal‑news‑feed (690 stars on GitHub, by Bill Cheng)

A terminal‑based Instagram feed viewer.

Project URL: https://github.com/billcccheng/instagram-terminal-news-feed

Rank 8: Makesite (481 stars on GitHub, by Sunaina Pai)

A simple, lightweight static site/blog generator for Python developers.

Project URL: https://github.com/sunainapai/makesite

Rank 9: Twitter‑scraper (832 stars on GitHub, by Kenneth Reitz)

A Python Twitter crawler without API rate limits, allowing efficient retrieval of any user's tweets.

Project URL: https://github.com/kennethreitz/twitter-scraper

Rank 10: Fast‑Pandas (667 stars on GitHub, by M. Mansour)

Pandas is one of the most flexible and powerful tools for data scientists and developers; Fast‑Pandas benchmarks various methods for specific tasks and includes dedicated functions for both NumPy and pandas.

Project URL: https://github.com/mm-mansour/Fast-Pandas