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Documentation Index

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Every HelloGitHub monthly issue organizes projects by programming language category. This makes it easy to find projects relevant to your tech stack or the language you’re learning. From systems programming in C and Rust, to web development in JavaScript, to data science in Python, every issue is carefully structured so readers can jump straight to the categories that matter most to them.

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Categories Overview

The following language categories appear regularly across HelloGitHub issues. Each represents a collection of curated, beginner-friendly open-source projects that have been recommended by the community since 2016.

C

C#

C++

CSS

Go

Java

JS

Kotlin

Objective-C

PHP

Python

Ruby

Rust

Swift

Books

Machine Learning

Other

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How Categories Are Used

Each monthly issue is divided into sections by programming language. The section heading names the language, followed by a numbered list of project entries in that category. This consistent structure means you can skim an issue quickly, skipping languages you are less interested in and diving deep into the ones you love. Every project entry contains:
  • Project name — linked directly to its GitHub repository.
  • Description — a concise summary of what the project does and why it is interesting or beginner-friendly.
  • Optional screenshots or GIFs — many entries include visuals to show the project in action.
Issues are published on the 28th of each month and are available in both Chinese and English. The category structure has remained consistent across all 123 issues, making it straightforward to compare what was popular in a given language year over year.

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Example Entry Format

Below is a representative example of how a project appears inside a HelloGitHub issue, taken from the Python category: 
### Python

1. [black](https://github.com/psf/black): The uncompromising Python code formatter.
   Black is the uncompromising Python code formatter, giving you speed, determinism,
   and freedom from pycodestyle nagging about formatting.
The pattern is always the same: a numbered list item, the project name as a hyperlink to GitHub, a colon, and then a plain-text description. Screenshots follow as inline images where relevant. This uniform format makes issues easy to parse both by humans and by tooling.

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Finding Projects by Language

Because every issue follows the same category structure, you can navigate straight to a language section in any issue to see what was recommended that month. For a richer browsing experience across all 123 issues at once, the official website offers full-text search and language filtering.
Use hellogithub.com to search and filter all featured projects by programming language, making it faster to find projects relevant to your interests.

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Special Categories

Two categories span multiple programming languages and deserve special mention: Books — HelloGitHub regularly features open-source learning resources: free programming books, interactive tutorials, cheat sheets, and documentation projects hosted on GitHub. These are language-agnostic in nature and appeal to learners at every level. Examples include open-source books on algorithms, system design, operating systems, and language-specific deep dives. Machine Learning — As AI and ML became mainstream, HelloGitHub introduced a dedicated category for AI-related projects. This covers trained models, inference engines, datasets, annotation tools, experiment-tracking libraries, and end-to-end ML frameworks. Projects span Python, C++, and more, unified by their focus on artificial intelligence and data science workflows. Both special categories appear alongside the language-specific sections in recent issues and are browseable on the HelloGitHub website just like any other category.

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Keep Exploring

Full Archive

Browse all 123 issues from 2016 to today, organised by year.

Latest Issue

Read the most recent HelloGitHub monthly issue.

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