What are the most popular Python repos out there?
Any idea about who will make it to the podium?
n° 20: Pandas (18.5k ⭐️)
Used by a lot of people in the wide data field, Pandas is a very simple and powerful data-analysis/manipulation tool.
n° 19: Algorithm Interview Notes Chinese (19.4k ⭐️)
Can't really add anything to this one. I'd love to have some feedback from Chinese-speaking readers.
n° 18: Python patterns (19.6k ⭐️)
A collection of design patterns/idioms in Python. My go-to place when designing new solutions.
n° 17: 100 Days of ML code (20.7k ⭐️)
An incredible introduction to ML by Siraj Raval and Avik Jain.
n° 16: Face Recognition (21.9k ⭐️)
The world's simplest facial recognition api for Python and the command line. Think
requests, but for face recognition.
import face_recognition image = face_recognition.load_image_file("your_file.jpg") face_locations = face_recognition.face_locations(image)
n° 15: Home Assistant (22k ⭐️)
Open source home automation that puts local control and privacy first. Pleasantly surprised to see this one this close to the top.
n° 14: CPython (22.9k ⭐️)
Funny to see that the most famous and widely used Python implementation did not even made it to the top 10.
If it is not a sign of super-active ecosystem then I don't know what it is.
n° 13: The algorithms in Python (23.4k ⭐️)
All Algorithms implemented in Python. A very useful ressource for student, beginners and people trying to train for an interview.
n° 12: Certbot (24.5k ⭐️)
An amazing tool that allows you to automatically enable HTTPS on your website with EFF's Certbot and deploy Let's Encrypt certificates.
n° 11: Scrapy (31.8k ⭐️)
Scrapy is a fast high-level web crawling & scraping framework for Python. It allows you to scrape thousands of web pages in 20 lines of codes and as many seconds.
n° 10: Scikit-learn (33.8k ⭐️)
Probably the most famous machine learning lib out there. Scikit-learn allow anyone to learn about ML thanks to its low entry point and its very wide and developped community.
Initiated by David Cournapeau during a Google Summer of code project it has now been maintained for the last 8 years. Congrats !!!
n° 9: Ansible (35.9k ⭐️)
Welcome to the devOps world. Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications — automate in a language that approaches plain English, using SSH, with no agents to install on remote systems.
n° 8: Request (37.6k ⭐️)
Easy, simple and elegant API make requests one of the most famous Python repos.
I use this package daily and I honestly don't know an easier way to do an http request in Python, see by yourself:
>>> import requests >>> r = requests.get('https://api.github.com/user', auth=('user', 'pass')) >>> r.status_code 200
n° 7: Keras (39.1k ⭐️)
Keras is an open-source neural-network library written in Python. Can be used on top of TensorFlow and other ML library.
Supported by the team behing Tensorflow since 2017, Keras is more considered as an interface rather than a pure ML library.
n° 6: Django (40.1k ⭐️)
One of the two most famous Python web framework. The other one is not far below.
n° 5: httpie (40.2k ⭐️)
A easier and user-friendlier alternative to
curl with intuitive UI, JSON support and much more. Has anyone ever tried this one?
n° 4: The Fuck (42k ⭐️)
Magnificent app which corrects your previous console command. Very, very, very useful.
n° 3: Flask (42k ⭐️)
My favorite Python web framework made it to top 3. Interestingly, it's only recently that Flask is more popular than Django.
n° 2: Awsome Python (64k ⭐️)
A curated list of awesome Python frameworks, libraries, software and resources. Very useful as a first entry point for your new project.
n° 1: TensorFlow (123k ⭐️)
TensorFlow is an open source software library for numerical computation using data flow graphs. Originally developed by the Google Brain team for internal Google use, It was later open-sourced in 2015.
I think it is safe to say that Pythonistas really love ML, simple API and learning new things.
I must say I am surprised to see TensorFlow dominate this top 20 by this margin.
It would be very interesting to compare this kind of top 20 with top 20 for other languages. It will probably be the subject of another post.
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