Duplicate from nick007x/github-code-2025

Co-authored-by: NIck Saga <nick007x@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+license: mit
+modalities:
+- Text
+formats:
+- parquet
+size: 10M - 100M
+libraries:
+- Datasets
+- Dask
+- Croissant
+- Polars
+---
+
+# 🚀 GitHub Code 2025: The Clean Code Manifesto
+
+> **A meticulously curated dataset of 1.5M+ repositories representing both quality and innovation in 2025's code ecosystem**
+
+## 🌟 The Philosophy
+
+**Quality Over Quantity, Purpose Over Volume**
+
+In an era of data abundance, we present a dataset built on radical curation. Every file, every repository, every byte has been carefully selected to represent the **signal** in the noise of open-source development.
+
+## 🎯 What This Dataset Is
+
+### 📊 Dual-Perspective Design
+
+| Subset | 🎖️ Above 2 Stars | 🌱 Below 2 Stars (2025) |
+|--------|------------------|------------------------|
+| **Scope** | 1M top repositories | 1M random 2025 repos |
+| **Purpose** | Proven quality & patterns | Emerging trends & innovation |
+| **Value** | What works | What's next |
+
+### 🧹 The Clean Code Promise
+
+```python
+# What you WON'T find here:
+🚫 Binary files          # No images, executables, models
+🚫 Build artifacts       # No node_modules, __pycache__
+🚫 Configuration noise   # No .git, IDE files, lock files
+🚫 License duplication   # No repetitive legal text
+🚫 Minified code         # No compressed/obfuscated content
+🚫 Empty files           # No whitespace-only content
+```
+
+## 📁 Dataset Structure
+
+```
+github-code-2025/
+├── 📈 above-2-stars/
+│   ├── train_000.parquet
+│   ├── train_001.parquet
+│   └── ...
+└── 🌱 below-2-star/
+    ├── train_000.parquet
+    ├── train_001.parquet
+    └── ...
+```
+
+### 📊 Schema
+
+```python
+{
+    "repo_id": "owner/repo_name",    # 📍 Repository identifier
+    "file_path": "src/main.py",      # 🗂️ Relative file path
+    "content": "def clean_code():",   # 💎 Actual source code
+    "size": 1024                     # 📏 File size in bytes
+}
+```
+
+## 🛠️ How to Use
+
+### 🔥 Quick Start
+
+```python
+from datasets import load_dataset
+
+# Load the quality benchmark
+quality_ds = load_dataset("nick007x/github-code-2025", "above-2-stars")
+
+# Load emerging trends
+emerging_ds = load_dataset("nick007x/github-code-2025", "below-2-star")
+
+# Mix for balanced training
+balanced_ds = interleave_datasets([quality_ds, emerging_ds])
+```
+
+### 🎯 Ideal Use Cases
+
+- **🧠 AI Training**: Clean, diverse code for language models
+- **📊 Code Analysis**: Compare popular vs emerging patterns
+- **🔍 Trend Research**: 2025 development practices
+- **🎓 Education**: High-quality examples for learning
+- **🛠️ Tool Development**: Benchmarking code quality tools
+
+## 🏗️ Creation Methodology
+
+### 🎨 Selection Strategy
+
+| Phase | Action | Purpose |
+|-------|--------|---------|
+| **1** | 🎯 Dual population sampling | Balance quality & innovation |
+| **2** | 🧹 Multi-layer filtering | Remove noise & binaries |
+| **3** | 📏 Size normalization | Focus on meaningful content |
+| **4** | 🔍 Content validation | Ensure text quality |
+| **5** | 🏷️ Metadata preservation | Maintain context |
+
+### 🚫 What We Filtered Out
+
+**File Types Removed:**
+- 50+ binary extensions (images, models, executables)
+- 30+ build/system directories
+- 15+ configuration file types
+- All files outside 1KB-5MB range
+
+**Quality Checks:**
+- ✅ UTF-8 text validation
+- ✅ Non-empty content check
+- ✅ Binary detection
+- ✅ Repository structure preservation
+
+
+## 🎪 Why This Dataset Matters
+
+### 💫 The Quality Revolution
+
+We reject the "more data is better" dogma. Instead, we offer:
+
+- **🎯 Intentional Curation**: Every file serves a purpose
+- **⚖️ Balanced Perspective**: Popular + Emerging = Complete picture
+- **🧹 Unprecedented Cleanliness**: The cleanest code dataset available
+- **📅 Temporal Intelligence**: 2025-focused for relevance
+
+
+## 🤝 Contributing & Feedback
+
+This dataset is a living project. We welcome:
+
+- 🐛 Bug reports and issues
+- 💡 Feature requests for future versions
+- 📊 Validation of data quality
+- 🎯 Suggestions for improvement
+
+## 📜 License
+
+This dataset aggregates Github repos. Each individual repo maintains its original copyright and license terms (typically various Creative Commons licenses like CC BY, CC BY-NC, etc.). 
+Users must verify and comply with the specific license of any repo they extract and use from this collection. 
+The MIT license in this repository applies only to the dataset compilation and packaging code.
+
+**Important**: Repository contents maintain their original licenses. Please respect individual project licenses when using this data.
+
+## 🙏 Acknowledgments
+
+Built with gratitude for the entire open-source community. Every file in this dataset represents hours of dedication from developers worldwide.
+
+---
+
+**⭐ If this dataset helps your research or project, please consider starring the repository!**
+
+> **"In the pursuit of AI that understands code, we must first understand what code is worth learning."**

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