Chapter 1: Introduction to the Most Popular Python Projects

Happy New Year 2022! As we step into the new year, I'm eager to explore the most popular Python projects to date. GitHub serves as the ideal platform for these statistics. While not every open-source project is actively maintained, there’s truly no other place that can provide such comprehensive data.

To keep things straightforward, I’ll share my code for fetching this ranked list from the GitHub API. Let's dive into how we can retrieve this information with just a few lines of code, categorize the projects based on my criteria, and provide brief overviews.

The Top 30 GitHub projects are categorized as follows:

• 7 repositories that enhance productivity
• 3 frameworks for programming
• 5 repositories supporting machine learning
• 4 projects that assist in real-life applications
• 6 repositories that gather and organize valuable information
• 5 educational resources

This first video demonstrates how to kick off Python projects effectively.

What’s great is that you don’t need to register or request an API key to use this endpoint. It does have a rate limit of 10 requests per minute, but this is sufficient for testing our code and retrieving the ranked list.

To start, we need to utilize Python’s built-in requests module, which many of you are likely familiar with, along with Pandas for data manipulation.

import requests

import pandas as pd

Next, we can call this API endpoint using the requests module with the GET method and convert the results into a Python dictionary.

res = requests.get(url)

res_dict = res.json()

All search results will be contained in an array under the key "items". This allows us to extract the repository information as follows. The default page size is 30, so we will obtain exactly the Top 30 Python Repos.

repos = res_dict['items']

len(repos)

The result dictionary contains additional information; if we remove the item array, we can see that there are a total of 8,046,758 Python repositories at the time of my request.

Let’s convert the items array into a Pandas DataFrame.

repo_df = pd.DataFrame(repos)

Next, I’ll eliminate unneeded columns and add a new column called years_on_github to indicate how long each project has been active on GitHub.

repo_df = repo_df[['name', 'full_name', 'html_url', 'created_at', 'stargazers_count', 'watchers', 'forks', 'open_issues']]

repo_df['created_at'] = pd.to_datetime(repo_df['created_at'])

repo_df['created_year'] = repo_df['created_at'].dt.year

repo_df['years_on_github'] = 2022 - repo_df['created_at'].dt.year

Here’s the complete list of the Top 30 Repos:

Repositories That Enhance Productivity

These projects help improve daily workflows and productivity by adding features to operating systems.

1. thefxxk (6th ranked, 65,988 stars)

   This tool assists in correcting mistakes made in previous commands within console environments like Linux or GitBash.

   

2. httpie (9th ranked, 53,255 stars)

   A command-line HTTP client designed to make interaction with web services straightforward and user-friendly.

   

3. you-get (12th ranked, 42,791 stars)

   A simple command-line tool for downloading media content from the web when no other methods are available.

4. localstack (16th ranked, 38,008 stars)

   This repository emulates cloud services in a single container on your local machine, facilitating local development without connecting to a cloud provider.

5. shadowsocks (20th ranked, 33,099 stars)

   An open-source encryption protocol commonly used in China to bypass internet censorship.

6. rich (23rd ranked, 32,075 stars)

   A library that enhances terminal output with color and style, supporting tables, progress bars, and syntax highlighting.

7. certbot (30th ranked, 28,587 stars)

   A client that automates the process of obtaining and renewing SSL certificates from Let's Encrypt.

Repositories That Are Programming Frameworks

These repositories are well-known frameworks for web development or software creation.

1. flask (7th ranked, 57,584 stars)

   A widely-used framework for web development in Python.

2. scrapy (14th ranked, 42,471 stars)

   A framework essential for web scraping, simplifying and automating data extraction from websites.

3. fastapi (15th ranked, 40,363 stars)

   A popular framework for developing web APIs with minimal code.

Repositories That Facilitate Machine Learning

Machine learning is one of the most significant applications of Python, and numerous projects in this domain are represented here.

1. models (5th ranked, 72,417 stars)

   Also known as the TensorFlow Model Garden, this repository organizes machine learning models implemented with TensorFlow.

2. keras (8th ranked, 53,638 stars)

   A widely used high-level API for building and training deep learning models.

3. face_recognition (13th ranked, 42,762 stars)

   A library for face recognition and manipulation, boasting simplicity and ease of use.

4. Real-Time-Voice-Cloning (21st ranked, 32,607 stars)

   A project that can replicate a person's voice from a short audio clip, presenting ethical considerations for its use.

5. DeepFaceLab (27th ranked, 30,651 stars)

   Known for creating "deepfake" videos by swapping faces in videos.

Repositories That Assist in Real-Life Applications

These projects, while coded in Python, have practical applications that enhance daily life.

1. core (11th ranked, 48,763 stars)

   An open-source home automation framework focused on local control and privacy.

2. openpilot (24th ranked, 31,998 stars)

   An open-source driver assistance system offering features like adaptive cruise control and lane centering.

3. XX-Net (26th ranked, 31,002 stars)

   A proxy tool used to bypass internet restrictions in China.

4. 12306 (28th ranked, 30,401 stars)

   An automated tool for booking train tickets in China, addressing the challenges of ticket shortages.

Repositories That Gather and Organize Valuable Information

These repositories may not contain extensive code but provide valuable information or resources related to Python.

1. public-apis (1st ranked, 173,658 stars)

   A collection of free APIs useful for software and web development.

2. awesome-python (4th ranked, 112,609 stars)

   A curated list of outstanding Python projects.

3. awesome-machine-learning (10th ranked, 52,487 stars)

   A repository compiling various machine learning projects.

4. funNLP (17th ranked, 35,922 stars)

   A Chinese repository offering NLP dictionaries and learning materials.

5. interview_internal_reference (19th ranked, 33,135 stars)

   A collection of interview questions and foundational knowledge for data developers.

6. Deep-Learning-Papers-Reading-Roadmap (24th ranked, 31,521 stars)

   A roadmap for learning machine learning through academic papers.

Repositories That Educate on Various Subjects

These repositories function as open-source "books" that provide educational content.

1. system-design-primer (2nd ranked, 157,775 stars)

   A comprehensive resource for aspiring system architects.

2. Python-100-Days (3rd ranked, 113,812 stars)

   A structured program for learning Python over 100 days, popular among developers in China.

3. PayloadsAllTheThings (18th ranked, 33,407 stars)

   A resource detailing payloads and security measures for web applications.

4. AiLearning (22nd ranked, 32,517 stars)

   A Chinese repository teaching Python fundamentals to advanced topics.

5. d2l-zh (29th ranked, 29,618 stars)

   A "Dive into Deep Learning" book that provides resources for learning deep learning principles.

Conclusion

The popularity of repositories is often determined by their star ratings, reflecting user engagement. Educational and information-organizing repositories tend to rank highly as users frequently star them as bookmarks. The code is available for you to explore further and satisfy your curiosity.

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