Update README.md

README.md

@@ -14,4 +14,221 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+
+annotations_creators:
+  - author
+license:
+  - gpl-3.0
+multilinguality:
+  - monolingual
+pretty_name: GitHub-Python
+dataset_name: github-python
+dataset_type: code
+tags:
+  - code
+  - python
+size_categories:
+  - 100K<n⩽1M
+task_categories:
+  - text-generation
 ---
+
+# GitHub-Python — Licensed & Elaborated Variants
+
+This repository ships **two complementary Python-code corpora** extracted from
+public GitHub:
+
+- **Licensed Subset** – strictly _permissive-licensed_ files suitable for
+  commercial redistribution / model training (main corpus used in our
+  experiments).
+- **Elaborated Collection** – a broader crawl that additionally contains files
+  under _copyleft_ or unclear licenses (GPL/AGPL/LGPL, etc.). Useful for
+  analysis or pre-training where license mixing is acceptable.
+
+Both variants target **code-completion / generation** research.
+
+## Dataset at a glance
+
+|                     | **Licensed Subset** | **Elaborated Collection** |
+| ------------------- | ------------------- | ------------------------- |
+| Files (.py)         | 53,017              | 186,066                   |
+| Unique repositories | 16,447              | 59,852                    |
+| Repository owners   | 12,515              | 43,517                    |
+| Compressed size     | 732 MB              | 2.4 GB \*                 |
+| Vocabulary (tokens) | 443,431             | 443,431 †                 |
+| License coverage    | Permissive only     | Mixed (perm. + copyleft)  |
+| Secrets redacted    | ✅                  | ⚠️ not guaranteed         |
+| Time window         | ≥ 2015-01-01        | ≥ 2015-01-01              |
+
+\* estimated – elaborated corpus is distributed as raw file list, not a single
+text file.  
+† same tokenizer file is shared by both variants.
+
+Numbers were obtained from the final redacted corpus and companion metadata.
+
+---
+
+## Dataset structure
+
+```
+huggingface_dataset/
+ ├─ mega_licensed_corpus_redacted.txt      # Licensed Subset – concatenated code
+ ├─ python_files.txt                       # Licensed Subset – raw file URLs
+ ├─ python_files_elaborated.txt            # Elaborated Collection – raw file URLs
+ ├─ python_files_elaborated_metadata.csv   # Elaborated Collection metadata
+ └─ custom_tokens_vocab.txt             # `<token>\t<id>` vocabulary file
+```
+
+### File separator
+
+Individual files are concatenated with the sentinel line:
+
+```
+# <FILESEP>
+```
+
+Anything following the sentinel until the next sentinel (or EOF) is the source
+code of one file.
+
+---
+
+## Dataset variants
+
+### 1. Licensed Subset (`mega_licensed_corpus_redacted.txt`)
+
+• 53 K permissively-licensed files (MIT/BSD/Apache/ISC/Unlicense).  
+• All API keys & credentials removed.  
+• Ready for redistribution & commercial use (respect upstream NOTICE files).
+
+### 2. Elaborated Collection (`python_files_elaborated.txt`)
+
+• 186 K files from a much larger crawl.  
+• Contains **GPL / LGPL / AGPL and other copyleft** licenses.  
+• Shipped _as URL list_ + metadata CSV; you must download the files yourself
+(`datasets.load_dataset` streaming, `wget`, etc.).  
+• **No license filtering or secret-redaction performed** – use with caution.
+
+When first loading the dataset, decide which variant aligns with your use case
+(e.g. proprietary model training → Licensed Subset only).
+
+---
+
+## Collection methodology
+
+1. **Repository discovery**
+
+   - Queried GitHub REST API for projects with **≥ 10 stars**  
+     (earlier iterations used 100+, later expanded for coverage).
+   - Only repositories with primary language _Python_ and last commit ≥ 2015.
+
+2. **File filtering**
+
+   - Retain files whose **size ∈ [1 KB, 100 KB]**.
+   - Exclude common build/packaging scripts (`setup.py`, `__init__.py`, etc.).
+
+3. **License compliance**
+
+   - Allowed: MIT, Apache-2.0, BSD-2/3-Clause, ISC, Unlicense.
+   - GPL, LGPL, AGPL and proprietary licenses were **excluded**.
+
+4. **Deduplication**
+
+   - Unique file SHA hashes; duplicates skipped.
+
+5. **Formatting & cleaning**
+
+   - Formatted with _autopep8_ to normalise whitespace.
+   - Custom script removed trailing whitespace & normalised newlines.
+
+6. **Secret redaction**
+   - `truffleHog` + custom regex pass removed >150 active credentials.
+   - Redacted corpus stored as `mega_licensed_corpus_redacted.txt`.
+
+---
+
+## Custom tokenisation
+
+The accompanying `custom_tokens_vocab.txt` implements a **Python-aware
+sub-token scheme**:
+
+1. Strip doc-strings & comments.
+2. Split on:
+   - Camel-Case boundaries (`Camel` → `Camel`, `Case`)
+   - Underscores, spaces
+   - Indentation & newlines (preserved as `<newline>` token)
+3. Rare tokens (frequency < 10) were dropped → 443 k vocabulary.
+
+Example:
+
+```python
+def helloWorld(value):
+    return value + 1
+```
+
+tokenises to:
+
+```
+def hello world ( value ) <newline>     return value + 1 <newline>
+```
+
+---
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("jblitzar/github-python", split="train")
+
+print(ds[0]["code"][:300])        # raw source code
+```
+
+If you prefer token level examples (small reasons: memory), map the tokenizer:
+
+```python
+from tokenizers import Tokenizer
+tok = Tokenizer.from_file("custom_tokens_vocab.txt")
+
+def encode(ex):
+    ex["input_ids"] = tok.encode(ex["code"]).ids
+    return ex
+
+ds = ds.map(encode, remove_columns=["code"])
+```
+
+---
+
+## Ethical considerations & limitations
+
+- **Licenses respected** – only permissive licenses included; retain NOTICE
+  files when redistributing derivative works.
+- **Secrets removed** – automated & manual audits performed, yet users **must
+  not assume zero secrets**; re-audit before public deployments.
+- **Code quality** – projects vary in style & correctness. Generated models
+  may replicate bugs or vulnerable patterns.
+
+---
+
+## Citation
+
+If you use this dataset, please cite:
+
+```
+@misc{github-python-2024,
+  author       = {JBlitzar},
+  title        = {GitHub-Python: A Permissively Licensed Corpus of Python Code},
+  year         = {2024},
+  howpublished = {\url{https://huggingface.co/datasets/jblitzar/github-python}},
+  note         = {Version 1.0}
+}
+```
+
+---
+
+## License
+
+Dataset card and aggregation scripts: **GPLv3**.  
+Each code snippet remains under its **original repository license** (MIT,
+Apache-2.0, BSD, ISC, etc.). Users must comply with upstream notices when
+redistributing code or derivatives.
+