metadata

dataset_info:
  features:
    - name: code
      dtype: string
    - name: repo_name
      dtype: string
    - name: path
      dtype: string
    - name: language
      dtype: string
    - name: license
      dtype: string
    - name: size
      dtype: int64
  splits:
    - name: train
      num_bytes: 360682958
      num_examples: 45001
    - name: validation
      num_bytes: 37445138
      num_examples: 5000
  download_size: 141557496
  dataset_size: 398128096
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*

🐍 CodeParrot Python Only

This dataset contains Python-only source code extracted from the larger CodeParrot corpus. It includes high-quality .py files filtered from public GitHub repositories and curated for use in training large language models (LLMs) on Python code generation tasks.

📦 Dataset Summary

✅ Filtered to include only Python code
🧹 Cleaned to remove non-source content (e.g., binaries, notebooks, scripts with mixed languages)
🧠 Ideal for training or evaluating code generation models
🧾 Each entry is a code snippet or full Python file stored as raw text

💡 Use Cases

This dataset is best suited for:

Training/fine-tuning LLMs for:
- Python code generation
- Auto-completion
- Bug detection
- Code summarization
Evaluating code-specific capabilities of general LLMs
Research in code intelligence, representation learning, and software engineering

📁 Example Format

Each record is a single code block:

{
  "code": "def hello_world():\n    print('Hello, world!')"
}

🚀 How to Use

from datasets import load_dataset

ds = load_dataset("theothertom/codeparrot-python-only")
print(ds["train"][0]["code"])