license: mit
task_categories:
- text-generation
language:
- code
tags:
- code
- github
- source-code
- trending-developers
- software-engineering
size_categories:
- 1M<n<10M
GitHub Top Developer Source Code
A curated dataset of 1.3M+ source code files from GitHub's top ranked developers (2015-2025).
This dataset is based on the top ranked developers from this dataset: https://huggingface.co/datasets/ronantakizawa/github-top-developers
Dataset Summary
- 1.3M+ source code files from repositories across ~4,700 unique developers
- 80+ programming languages included (Python, JavaScript, TypeScript, Rust, Go, C/C++, Java, and more)
- Source code only — config files (JSON, YAML, TOML, etc.) and documentation (Markdown, TXT) are excluded
- Permissive licenses only (MIT, Apache-2.0, BSD, ISC, etc.)
- Rich metadata per file: repo stars, description, primary language, developer company affiliation
Schema
Each row represents a single source file:
| Column | Type | Description |
|---|---|---|
file_path |
string | Path within the repo (e.g. src/main.py) |
file_language |
string | Language detected from file extension (e.g. Python, JavaScript) |
content |
string | Raw source code (UTF-8) |
repo_name |
string | Full repository name (owner/repo) |
repo_stars |
int64 | GitHub star count at time of collection |
repo_description |
string | Repository description |
repo_primary_language |
string | GitHub-detected primary language of the repository |
developer_username |
string | GitHub username |
developer_name |
string | Developer display name |
developer_company |
string | Company affiliation |
Note on language columns: file_language is determined per-file from the file extension (e.g. a .py file is always Python). repo_primary_language is GitHub's auto-detected primary language for the entire repository. These may differ — for example, a C header file (.h → C/C++ Header) in a repo that GitHub classifies as Python.
Splits
| Split | Description |
|---|---|
train |
~90% of repos — for training |
test |
~5% of repos — for evaluation |
validation |
~5% of repos — for hyperparameter tuning |
Splits are assigned by repository (deterministic hash), so no repo appears in multiple splits. This prevents data leakage from files in the same project.
Usage
from datasets import load_dataset
# Load a specific split
train = load_dataset("ronantakizawa/github-top-code", split="train")
test = load_dataset("ronantakizawa/github-top-code", split="test")
# Filter by language
python_files = train.filter(lambda x: x["file_language"] == "Python")
# Filter by stars
popular = train.filter(lambda x: x["repo_stars"] > 1000)
# Get files from a specific developer
dev_files = train.filter(lambda x: x["developer_username"] == "torvalds")