Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/awesomelistsio/awesome-python
A curated list of awesome frameworks, libraries, tools, and resources for Python programming.
https://github.com/awesomelistsio/awesome-python
List: awesome-python
awesome awesome-list awesome-lists python
Last synced: 22 days ago
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A curated list of awesome frameworks, libraries, tools, and resources for Python programming.
- Host: GitHub
- URL: https://github.com/awesomelistsio/awesome-python
- Owner: awesomelistsio
- Created: 2024-11-17T21:49:18.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-11-17T21:50:00.000Z (about 1 month ago)
- Last Synced: 2024-11-26T18:41:56.521Z (25 days ago)
- Topics: awesome, awesome-list, awesome-lists, python
- Language: Python
- Homepage:
- Size: 4.88 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-python - A curated list of awesome frameworks, libraries, tools, and resources for Python programming. (Other Lists / PowerShell Lists)
README
# Awesome Python [](https://github.com/awesomelistsio/awesome)
[](https://tinyurl.com/2h9aktmd) [](https://tinyurl.com/d4xnrptz) [](https://tinyurl.com/mr22naua) [](https://tinyurl.com/e8ymxdw3)
> A curated list of awesome frameworks, libraries, tools, and resources for Python programming.
## Contents
- [Libraries](#libraries)
- [Core Libraries](#core-libraries)
- [Web Frameworks](#web-frameworks)
- [Data Science](#data-science)
- [Machine Learning](#machine-learning)
- [Testing](#testing)
- [Database](#database)
- [JSON and Data Parsing](#json-and-data-parsing)
- [Networking](#networking)
- [Tools](#tools)
- [Build Tools](#build-tools)
- [IDEs and Editors](#ides-and-editors)
- [Learning Resources](#learning-resources)
- [Books](#books)
- [Community](#community)
## Libraries
### Core Libraries
- [requests](https://github.com/psf/requests) - A simple and elegant HTTP library for Python.
- [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/) - A library for parsing HTML and XML documents.
- [PyYAML](https://github.com/yaml/pyyaml) - A YAML parser and emitter for Python.
- [NumPy](https://numpy.org/) - The fundamental package for numerical computation in Python.
### Web Frameworks
- [Django](https://www.djangoproject.com/) - A high-level Python web framework that encourages rapid development.
- [Flask](https://flask.palletsprojects.com/) - A lightweight WSGI web application framework.
- [FastAPI](https://fastapi.tiangolo.com/) - A modern, fast (high-performance) web framework for building APIs with Python 3.7+.
- [Tornado](https://www.tornadoweb.org/) - A scalable, non-blocking web server and web application framework.
### Data Science
- [Pandas](https://pandas.pydata.org/) - A powerful data analysis and manipulation library.
- [Matplotlib](https://matplotlib.org/) - A comprehensive library for creating static, animated, and interactive visualizations in Python.
- [Seaborn](https://seaborn.pydata.org/) - A Python visualization library based on Matplotlib that provides a high-level interface.
- [SciPy](https://www.scipy.org/) - A library used for scientific and technical computing.
### Machine Learning
- [scikit-learn](https://scikit-learn.org/) - A library for machine learning, providing simple and efficient tools for data mining and data analysis.
- [TensorFlow](https://www.tensorflow.org/) - An open-source platform for machine learning.
- [PyTorch](https://pytorch.org/) - An open-source machine learning framework that accelerates the path from research prototyping to production.
- [Keras](https://keras.io/) - A user-friendly neural network library written in Python.
### Testing
- [pytest](https://pytest.org/) - A framework that makes building simple and scalable test cases easy.
- [unittest](https://docs.python.org/3/library/unittest.html) - A built-in Python module for testing.
- [Hypothesis](https://hypothesis.readthedocs.io/) - A library for property-based testing.
### Database
- [SQLAlchemy](https://www.sqlalchemy.org/) - A SQL toolkit and Object-Relational Mapping (ORM) library.
- [Django ORM](https://docs.djangoproject.com/en/stable/topics/db/models/) - The ORM used by the Django web framework.
- [Peewee](https://docs.peewee-orm.com/) - A small, expressive ORM for Python.
- [Redis-Py](https://github.com/redis/redis-py) - The Python client for Redis.
### JSON and Data Parsing
- [json](https://docs.python.org/3/library/json.html) - The built-in library for JSON encoding and decoding.
- [ujson](https://github.com/ultrajson/ultrajson) - Ultra JSON, a fast JSON encoder and decoder for Python.
- [xmltodict](https://github.com/martinblech/xmltodict) - A Python library that makes working with XML as easy as JSON.
### Networking
- [socket](https://docs.python.org/3/library/socket.html) - A built-in module for low-level networking.
- [paramiko](https://www.paramiko.org/) - A Python implementation of SSH for connecting to remote servers.
- [Twisted](https://twistedmatrix.com/trac/) - An event-driven networking engine in Python.
## Tools
- [Jupyter Notebook](https://jupyter.org/) - An open-source tool for interactive computing and sharing code.
- [Pipenv](https://pipenv.pypa.io/) - Python's officially recommended packaging tool.
- [Poetry](https://python-poetry.org/) - A tool for dependency management and packaging in Python.
- [Black](https://black.readthedocs.io/) - An uncompromising code formatter for Python.
## Build Tools
- [Setuptools](https://setuptools.pypa.io/en/latest/) - A build system for creating Python packages.
- [Wheel](https://pypi.org/project/wheel/) - The official binary distribution format for Python.
- [tox](https://tox.readthedocs.io/) - A tool for automating testing across multiple Python environments.
## IDEs and Editors
- [PyCharm](https://www.jetbrains.com/pycharm/) - A powerful IDE for Python by JetBrains.
- [VS Code](https://code.visualstudio.com/) - A free, open-source editor with Python support via extensions.
- [Spyder](https://www.spyder-ide.org/) - An IDE designed for data science and machine learning.
## Learning Resources
- [Official Python Documentation](https://docs.python.org/3/) - The official docs for the Python programming language.
- [Real Python](https://realpython.com/) - Tutorials, articles, and guides for Python developers.
- [Python Crash Course](https://ehmatthes.github.io/pcc/) - A beginner-friendly Python book.
## Books
- *Automate the Boring Stuff with Python* by Al Sweigart - A book on practical Python projects.
- *Python Cookbook* by David Beazley and Brian K. Jones - A book filled with Python recipes and tips.
- *Fluent Python* by Luciano Ramalho - A deep dive into Python's most powerful features.
## Community
- [Python Discord](https://discord.gg/python) - A large, active Python community on Discord.
- [Reddit: r/Python](https://www.reddit.com/r/Python/) - A subreddit for Python programming news and discussions.
- [Stack Overflow](https://stackoverflow.com/questions/tagged/python) - A Q&A site for Python developers.
## Contribute
Contributions are welcome!
## License
[](http://creativecommons.org/licenses/by-sa/4.0/)