| --- |
| dataset_info: |
| features: |
| - name: url |
| dtype: string |
| - name: number |
| dtype: int64 |
| - name: title |
| dtype: string |
| - name: body |
| dtype: string |
| - name: state |
| dtype: string |
| - name: created_at |
| dtype: timestamp[s] |
| - name: comments_url |
| dtype: string |
| - name: pull_request |
| struct: |
| - name: url |
| dtype: string |
| - name: html_url |
| dtype: string |
| - name: diff_url |
| dtype: string |
| - name: patch_url |
| dtype: string |
| - name: merged_at |
| dtype: timestamp[s] |
| - name: is_pull_request |
| dtype: bool |
| - name: text |
| dtype: string |
| - name: comments |
| sequence: string |
| splits: |
| - name: train |
| num_bytes: 39183484 |
| num_examples: 8019 |
| download_size: 15175192 |
| dataset_size: 39183484 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| tags: |
| - comments |
| - semantic_search |
| - pull_requests |
| - github_issues |
| pretty_name: Github Issues |
| --- |
| |
| # GitHub Issues Dataset (huggingface/datasets) |
|
|
| ## Dataset Description |
|
|
| This dataset contains GitHub issues and pull requests from the `huggingface/datasets` repository. It was created using the GitHub REST API and processed into a machine-learning-friendly format using the Hugging Face `datasets` library. |
|
|
| Each record represents either: |
| - a GitHub issue, or |
| - a pull request (which GitHub treats as a special type of issue) |
|
|
| The dataset includes cleaned metadata fields and derived features to support NLP and machine learning tasks such as classification, summarisation, and exploratory analysis. |
|
|
| --- |
|
|
| ## Dataset Summary |
|
|
| - **Source:** GitHub REST API (`huggingface/datasets` repository) |
| - **Format:** JSONL |
| - **Total samples:** ~8,000 (issues + pull requests combined) |
| - **Language:** English |
| - **Created using:** Python, Hugging Face `datasets`, GitHub API |
|
|
| --- |
|
|
| ## Dataset Fields |
|
|
| Each entry contains the following fields: |
|
|
| - `url`: Direct GitHub URL to the issue or pull request |
| - `number`: Issue or PR number |
| - `title`: Title of the issue |
| - `body`: Full text content of the issue |
| - `state`: Issue state (`open` or `closed`) |
| - `created_at`: Creation timestamp |
| - `comments_url`: API URL for comments |
| - `pull_request`: If present, indicates the issue is a pull request (otherwise `null`) |
| - `is_pull_request`: Derived boolean flag (`true` if pull request, else `false`) |
| - `text`: Combined field of `title + body` for NLP tasks |
|
|
| --- |
|
|
| ## Data Processing Pipeline |
|
|
| The dataset was built using the following steps: |
|
|
| 1. Extracted issues using GitHub REST API |
| 2. Saved raw responses into JSONL format |
| 3. Cleaned nested and inconsistent fields |
| 4. Removed problematic timestamp/nested structures when necessary |
| 5. Created derived features: |
| - `is_pull_request` |
| - `text` (concatenated title and body) |
| 6. Loaded using Hugging Face `datasets.load_dataset` |
|
|
| --- |
|
|
| ## Intended Uses |
|
|
| This dataset is suitable for: |
|
|
| - Issue vs pull request classification |
| - NLP text classification tasks |
| - Summarisation of GitHub issues |
| - Repository analytics and insights |
| - Learning and experimenting with Hugging Face datasets |
|
|
| --- |
|
|
| ## Limitations |
|
|
| - Contains data from only one repository (`huggingface/datasets`) |
| - Includes both issues and pull requests (must be filtered if not needed) |
| - Subject to GitHub API rate limits during data collection |
| - Text quality varies depending on user input in issues |
| - Not representative of all GitHub repositories |
|
|
| --- |
|
|
| ## Ethical Considerations |
|
|
| - All data is publicly available on GitHub |
| - No private or sensitive user data is included beyond public usernames and contributions |
| - This dataset should not be used for profiling individual developers |
| - This project is done with the following in mind |
| - Australian Privacy Act 1988 (Cyber + Data Protection) https://www.oaic.gov.au/privacy/the-privacy-act |
| - ISO/IEC 27001 https://www.iso.org/isoiec-27001-information-security.html |
| - ISO/IEC 27002 – Security Controls Guidance https://www.iso.org/standard/75652.html |
|
|
|
|
| --- |
|
|
| ## License |
|
|
| This dataset inherits the license of the original GitHub repository content (`MIT License` where applicable). Users should verify licensing constraints before commercial use. |
|
|
| --- |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @dataset{github_issues_hf_datasets, |
| author = {Jon-Paul Fitzgerald}, |
| title = {GitHub Issues Dataset (huggingface/datasets)}, |
| year = {2026}, |
| url = {https://github.com/huggingface/datasets} |
| } |
| |
| @inproceedings{sanh2019distilbert, |
| title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter}, |
| author={Sanh, Victor and Debut, Lysandre and Chaumond, Julien and Wolf, Thomas}, |
| year={2019}, |
| url ={https://huggingface.co/docs/transformers/main/en/model_doc/distilbert#transformers.DistilBertForSequenceClassification} |
| eprint={1910.01108}, |
| archivePrefix={arXiv} |
| } |
| |
