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.gitattributes

@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+mega_licensed_corpus_redacted.txt filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,10 +1,184 @@
 ---
-license: gpl-3.0
-task_categories:
-- text-generation
-- fill-mask
-- feature-extraction
-- sentence-similarity
+annotations_creators:
+  - author
+license:
+  - gpl-3.0
+multilinguality:
+  - monolingual
+pretty_name: GitHub-Python
+dataset_name: github-python
+dataset_type: code
+tags:
+  - code
+  - python
+  - code-generation
 size_categories:
-- 10M<n<100M
----
+  - 100K<n⩽1M
+task_categories:
+  - text-generation
+task_ids:
+  - code-completion
+---
+
+# GitHub-Python
+
+A **767 MB** corpus of permissively-licensed Python code drawn from public GitHub repositories.  
+The dataset was created to support training and evaluation of **code-completion / generation** models.
+
+## Dataset at a glance
+
+|                  | Value                                         |
+| ---------------- | --------------------------------------------- |
+| Files            | 53,017 `.py` files                            |
+| Repositories     | 16,447                                        |
+| Owners           | 12,515                                        |
+| Compressed size  | 732 MB (`mega_licensed_corpus_redacted.txt`)  |
+| Vocabulary       | 443,431 tokens (`custom_tokens_vocab.txt`)    |
+| Time period      | Commits ≥ 2015-01-01                          |
+| License coverage | MIT, Apache-2.0, BSD, ISC, Unlicense          |
+| Removed secrets  | ✅ – all hard-coded secrets/API keys redacted |
+
+Numbers were obtained from the final redacted corpus and companion metadata.
+
+---
+
+## Dataset structure
+
+```
+huggingface_dataset/
+ ├─ mega_licensed_corpus_redacted.txt   # concatenated code corpus
+ ├─ python_files.txt                    # list of raw file URLs (1-per-line)
+ └─ 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.
+
+---
+
+## 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.

create_metadata_table.py

@@ -0,0 +1,138 @@
+#!/usr/bin/env python3
+"""
+Create a metadata table from GitHub Python file URLs.
+
+This script processes the file URLs from python_files.txt and creates a tabular
+CSV file with repository metadata including owner, name, file path, and URLs.
+"""
+
+import os
+import re
+import csv
+import pandas as pd
+from collections import Counter
+from urllib.parse import urlparse
+from tqdm import tqdm
+
+
+def parse_github_url(url):
+    """
+    Parse a GitHub URL to extract repository owner, name, and file path.
+    
+    Handles both raw.githubusercontent.com and github.com URLs.
+    
+    Args:
+        url (str): GitHub URL
+        
+    Returns:
+        dict: Dictionary with repo_owner, repo_name, file_path, repo_url
+    """
+    url = url.strip()
+    
+    # Initialize default values
+    result = {
+        "repo_owner": "unknown",
+        "repo_name": "unknown",
+        "file_path": "",
+        "file_url": url,
+        "repo_url": ""
+    }
+    
+    try:
+        # Parse URL to get components
+        parsed = urlparse(url)
+        path_parts = parsed.path.strip('/').split('/')
+        
+        # Handle raw.githubusercontent.com URLs
+        # Format: https://raw.githubusercontent.com/owner/repo/branch/path/to/file.py
+        if 'raw.githubusercontent.com' in url:
+            if len(path_parts) >= 3:
+                result["repo_owner"] = path_parts[0]
+                result["repo_name"] = path_parts[1]
+                # Skip branch (path_parts[2]) and get the rest as file path
+                result["file_path"] = '/'.join(path_parts[3:])
+                result["repo_url"] = f"https://github.com/{path_parts[0]}/{path_parts[1]}"
+        
+        # Handle github.com URLs
+        # Format: https://github.com/owner/repo/blob/branch/path/to/file.py
+        elif 'github.com' in url:
+            if len(path_parts) >= 4 and path_parts[2] == 'blob':
+                result["repo_owner"] = path_parts[0]
+                result["repo_name"] = path_parts[1]
+                # Skip 'blob' and branch, get the rest as file path
+                result["file_path"] = '/'.join(path_parts[4:])
+                result["repo_url"] = f"https://github.com/{path_parts[0]}/{path_parts[1]}"
+        
+        return result
+    
+    except Exception as e:
+        print(f"Error parsing URL {url}: {e}")
+        return result
+
+
+def process_file_urls(input_file, output_file):
+    """
+    Process GitHub file URLs and create a metadata CSV file.
+    
+    Args:
+        input_file (str): Path to the file containing GitHub URLs
+        output_file (str): Path to the output CSV file
+    """
+    print(f"Processing URLs from {input_file}...")
+    
+    # Read file URLs
+    with open(input_file, 'r', encoding='utf-8') as f:
+        urls = [line.strip() for line in f if line.strip()]
+    
+    # Parse each URL
+    metadata = []
+    for url in tqdm(urls, desc="Parsing URLs"):
+        metadata.append(parse_github_url(url))
+    
+    # Convert to DataFrame
+    df = pd.DataFrame(metadata)
+    
+    # Save to CSV
+    # Use minimal quoting to remain compatible with the standard csv module
+    df.to_csv(output_file, index=False, quoting=csv.QUOTE_MINIMAL)
+    print(f"Metadata saved to {output_file}")
+    
+    # Print statistics
+    unique_repos = df[['repo_owner', 'repo_name']].drop_duplicates()
+    unique_owners = df['repo_owner'].nunique()
+    
+    print("\n=== Dataset Statistics ===")
+    print(f"Total files: {len(df)}")
+    print(f"Unique repositories: {len(unique_repos)}")
+    print(f"Unique repository owners: {unique_owners}")
+    
+    # Top repositories by file count
+    repo_counts = Counter(zip(df['repo_owner'], df['repo_name']))
+    print("\nTop 10 repositories by file count:")
+    for (owner, repo), count in repo_counts.most_common(10):
+        print(f"  {owner}/{repo}: {count} files")
+    
+    # File extensions
+    extensions = Counter([os.path.splitext(path)[1] for path in df['file_path'] if path])
+    print("\nFile extensions:")
+    for ext, count in extensions.most_common(5):
+        print(f"  {ext or 'No extension'}: {count} files")
+    
+    # Repository owners with most repositories
+    owner_repo_counts = Counter(df['repo_owner'])
+    print("\nTop 5 repository owners:")
+    for owner, count in owner_repo_counts.most_common(5):
+        print(f"  {owner}: {count} files")
+
+
+if __name__ == "__main__":
+    input_file = "python_files.txt"
+    output_file = "github_python_metadata.csv"
+    
+    # Check if input file exists
+    if not os.path.exists(input_file):
+        print(f"Error: Input file {input_file} not found.")
+        print("Please make sure the file exists in the current directory.")
+        exit(1)
+    
+    process_file_urls(input_file, output_file)

mega_licensed_corpus_redacted.txt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:25872f695fefeb4106ddd7006c798767be925a67abadf5d22da240541cad6717
+size 767255913