NotaBug Code Dataset

A comprehensive code dataset compiled from NotaBug.org, a free code hosting platform that emphasizes software freedom, privacy, and fully open-source infrastructure. This dataset is specifically designed to support training code models using code from freedom-conscious developers and the free software community.

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Overview

The NotaBug Code Dataset represents a significant code corpus from a platform dedicated to software freedom and developer privacy. Built on a fully free software stack, it captures diverse open-source projects across thousands of programming languages and file types. This dataset serves as a valuable resource for developing code models that reflect free software practices and principles.

Key Statistics

Metric	Value
Total Files	12,622,961
Total Repositories	11,660
Compressed Size	12 GB (Parquet with Zstd)
File Types/Languages	6,306 (by file extension)
File Format	12 Parquet files

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Dataset Characteristics

Scope and Coverage

This dataset captures code from over 11,600 repositories hosted on NotaBug.org, including:

• Free software focused community: Extensive coverage of code from developers committed to software freedom and open-source principles
• Diverse language ecosystem: Support for 6,306 distinct file types identified by file extension
• Rich metadata: Repository names, file paths, license information, and file sizes
• Free software stack: Code hosted on a platform built entirely on free and open-source software
• Quality-assured: Filtered to exclude files with excessively long lines

File Types and Languages

The dataset encompasses files across 6,306 different types. The 30 most represented file types by file count are:

Rank	File Type	File Count
1	C++	2,219,208
2	po	2,022,441
3	none	1,572,451
4	PHP	951,354
5	patch	637,317
6	svg	547,170
7	XML	502,139
8	Python	392,476
9	Text	296,953
10	JavaScript	233,368
11	JSON	198,981
12	Scheme	192,409
13	Markdown	182,342
14	info	155,078
15	slackbuild	154,859
16	HTML	149,824
17	Shell	133,325
18	log	127,393
19	Makefile	112,989
20	INI	110,537
21	Lua	84,303
22	in	75,138
23	Assembly	74,519
24	list	58,346
25	Java	48,781
26	CSS	48,112
27	mk	47,373
28	dtsi	43,825
29	diff	42,125
30	el	41,017

License Distribution

Files are distributed across various open-source licenses, with MIT being predominant:

License	File Count
MIT	10,029,349
MPL 2.0	1,178,420
Unknown	888,840
GPL 2.0	333,538
GPL 3.0	158,975
Unlicense	11,805
CC-BY 4.0	8,367
BSD-2-Clause	4,718
AGPL 3.0	3,055
CC-BY-SA 4.0	2,309
WTFPL	1,314
CC0 1.0	1,188
BSD-3-Clause	601
CC-BY-NC 4.0	269
LGPL 3.0	137
LGPL 2.1	76

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Dataset Structure

Data Fields

Each record contains six fields providing comprehensive metadata and content information:

Field	Type	Description
code	string	The complete source file content in UTF-8 encoding
repo_name	string	Repository identifier in the format username/repository_name
path	string	File path relative to the repository root
language	string	File type/language inferred from file extension
license	string	Repository license (SPDX identifier or "unknown")
size	int64	File size in bytes

Sample Record

{
    "code": "#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n# Copyright (C) 2014...",
    "repo_name": "intermsofthewhole/libreboot",
    "path": "resources/utilities/i945gpu/intel-regs.py",
    "language": "Python",
    "license": "mit",
    "size": 3733
}

File Format

• Format: Apache Parquet with Zstd compression
• Structure: 12 consolidated files (notabug_0000.parquet to notabug_0011.parquet)
• Encoding: UTF-8
• Split: All examples are included in a single training split (no validation or test splits)

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Data Creation Process

Language Detection Methodology

Programming languages and file types are identified by file extension inference. This approach captures the intended purpose of each file while maintaining broad language coverage across the platform.

Source Data

All data originates from public repositories hosted on NotaBug.org, a platform built on fully free and open-source software infrastructure.

License Detection

License identification follows a systematic approach:

1. Scan repositories for license files and declarations
2. Match license text against known license patterns
3. Default to "unknown" if no license can be detected

Quality Filtering

The dataset has undergone systematic filtering to ensure quality:

Line Length Constraints

• Files with any line exceeding 1,000 characters are excluded
• This ensures compatibility with text processing pipelines

Deduplication Policy

• No deduplication was performed on the dataset
• All files from public repositories are included as-is

Content Inclusion

• UTF-8 encoded files are retained
• All public repository content is preserved

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Usage Considerations

Data Privacy and Security

The dataset may contain sensitive information that requires careful handling:

• Email Addresses: Present in code comments, documentation, or configuration files
• Credentials: Accidentally committed API keys or authentication tokens
• Personal Information: Names, phone numbers, and other identifiable data in comments or documentation

Users should implement appropriate filtering and anonymization when preparing data for model training.

Licensing and Attribution

This dataset aggregates source code from repositories with diverse licenses. Any use of code or data derived from this dataset must comply with the original repository licenses, including attribution requirements where applicable.

The license field in each record indicates the license of the source repository. Users are responsible for:

• Reviewing applicable license terms
• Providing proper attribution when required
• Ensuring compliance with license restrictions
• Respecting the software freedom principles of the original projects

Free Software Principles

Users of this dataset should be mindful of the free software values of the NotaBug.org community:

• Respect developer privacy and freedom
• Support open-source software development
• Consider contributing improvements back to the community
• Use the dataset ethically and transparently

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Technical Details

Source: Public repositories hosted on NotaBug.org

Annotations: Machine-generated (file type detection, license identification)

Language Detection: File extension-based inference

Task Categories: Text generation, code modeling, language understanding

Tags: Code, free software, open-source, software freedom

Platform Stack: Built on fully free and open-source software (GNU/Linux, GitLab Community Edition, etc.)

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