--- title: "pdfmux vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nameetp-pdfmux-vs-sindresorhus-awesome" tools: ["nameetp-pdfmux", "sindresorhus-awesome"] --- # pdfmux vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick pdfmux when license: pdfmux is MIT, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, pdfmux is MIT. [pdfmux](https://pdfmux.com) reports 74 GitHub stars, 12 forks, and 6 open issues, last pushed Jul 7, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [pdfmux's repository](https://github.com/NameetP/pdfmux) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [pdfmux](/tools/nameetp-pdfmux.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | Zero-cost PDF extraction with self-healing and OCR support. | 😎 Awesome lists about all kinds of interesting topics | | Stars | 74 | 484,026 | | Forks | 12 | 35,799 | | Open issues | 6 | 92 | | Language | Python | - | | Adopt for | - | A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. | | Persona | - | - | | Runtime | - | - | | License | MIT | CC0-1.0 | | Categories | Data & Retrieval, Model Training | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pdfmux](/tools/nameetp-pdfmux.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 3d | 11d | | Open issues (now) | 6 | 92 | | Security scan | 1 medium (1 medium) | No lockfile | | Full report | [trust report](/tools/nameetp-pdfmux/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Decision facts: awesome - **Adopt for:** A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. ## Choose when ### Choose pdfmux if… - License: pdfmux is MIT, awesome is CC0-1.0. - Tags unique to pdfmux: ai-agent, docling, document-parsing, llm. - Also covers Data & Retrieval, Model Training. - pdfmux ships Docker support for self-hosted deployment. ### Choose awesome if… - License: awesome is CC0-1.0, pdfmux is MIT. - Tags unique to awesome: awesome, awesome-list, lists, resources. - Also covers Developer Tools. - When you need well-organized access to diverse technical subjects from IoT to robotics ## When NOT to use pdfmux - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use awesome - If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources - In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ## Common questions ### What is the difference between pdfmux and awesome? pdfmux: Zero-cost PDF extraction with self-healing and OCR support.. awesome: 😎 Awesome lists about all kinds of interesting topics. See the comparison table for live GitHub stats and shared categories. ### When should I choose pdfmux over awesome? Choose pdfmux over awesome when License: pdfmux is MIT, awesome is CC0-1.0; Tags unique to pdfmux: ai-agent, docling, document-parsing, llm; Also covers Data & Retrieval, Model Training; pdfmux ships Docker support for self-hosted deployment. ### When should I choose awesome over pdfmux? Choose awesome over pdfmux when License: awesome is CC0-1.0, pdfmux is MIT; Tags unique to awesome: awesome, awesome-list, lists, resources; Also covers Developer Tools; When you need well-organized access to diverse technical subjects from IoT to robotics. ### When should I avoid pdfmux? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid awesome? If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ### Is pdfmux or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 74). Stars measure visibility, not whether either tool fits your constraints. ### Are pdfmux and awesome open source? Yes - both are open-source projects on GitHub (pdfmux: MIT, awesome: CC0-1.0). ### Where can I find alternatives to pdfmux or awesome? GraphCanon lists graph-backed alternatives at [pdfmux alternatives](/tools/nameetp-pdfmux/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([pdfmux markdown twin](/tools/nameetp-pdfmux/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/nameetp-pdfmux-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, pdfmux or awesome? pdfmux: Very active. awesome: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for pdfmux and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [pdfmux trust report](/tools/nameetp-pdfmux/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nameetp-pdfmux`](/api/graphcanon/graph?tool=nameetp-pdfmux) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_