We have reviewed and compared 10,000 open source libraries for Python and selected the 34 most useful ones.
We have grouped these libraries into 8 categories.
Dit artikel is vertaald met de ondersteuning van EDISON Software, dat , evenals .
Python Toolkit
1. : Python Development Workflow for Humans.
2. : Development of retro games in Python.
3. : A framework that helps write short tests and scales for complex functional tests.
4. : Simplifies dependency management and packaging.
5. : Simplifies logging.
6. : a library for streaming applications.
7. : The Pattern Matching you dreamed of.
8. : Performant type-checking.
9. : a library for working with times and dates.
10. : a library for working with Noisy Intermediate Scale Quantum (NISQ) circuits.
11. : A framework for working with the command line.
Web
12. : HTML Parsing for Humans.
13. : interactive data visualization in modern browsers.
14. : fast, cool, and asynchronous.
15. : Displays HTML content in a separate window.
16. : Detection and circumvention of firewalls and web application security systems.
17. : a minimalist and fast framework for creating HTTP APIs.
Terminal
18. : records terminal session as SVG animation.
19. : records terminal sessions.
20. : command line tools that draw graphs.
Code Editor
21. : uncompromising code formatter.
22. : experimental code editor for writing algorithms.
23. : a refactoring tool at the syntax tree level.
Debugging
24. : allows you to visualize what your program spends time on without restarting it.
25. : a graphical debugger that uses AST.
26. : cute debugger.
Compiler
27. : Python 3.7 to JavaScript transpiler.
28. : data science stack in the browser.
Data Related
29.: data validation.
30. : Data driven programming framework for Data pipeline work (Web Crawler, Machine Learning, Quantitative Trading, etc.).
31. : comparative performance tests in Pandas operations.
Chart
32. : a collection of scripts for drawing beautiful figures and animating algorithms.
33. : helps data scientists create graphs.
34. : A tool for geometric representation of multidimensional data.
P.S.
Share your experience using these libraries or tell us about your findings in 2019.
Bron: habr.com
