--- title: "notebook vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jupyter-notebook-vs-sindresorhus-awesome" tools: ["jupyter-notebook", "sindresorhus-awesome"] --- # notebook vs awesome *GraphCanon updated Oct 4, 2026* ## Verdict Pick notebook if jupyter Notebook is an open-source web application that facilitates the creation and sharing of documents with live code, equations, visualizations, and narrative text; pick awesome if a curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. [notebook](https://jupyter-notebook.readthedocs.io/) reports 13k GitHub stars, 5.8k forks, and 1.9k open issues, last pushed Sep 17, 2026. [awesome](https://github.com/sindresorhus/awesome) has 514k stars, 37k forks, and 107 open issues, last pushed Sep 2, 2026. Figures are from public GitHub metadata via [notebook's repository](https://github.com/jupyter/notebook) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [notebook](/tools/jupyter-notebook.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | Jupyter Interactive Notebook | 😎 Awesome lists about all kinds of interesting topics | | Stars | 13,346 | 514,268 | | Forks | 5,765 | 37,240 | | Open issues | 1,895 | 107 | | Language | Jupyter Notebook | - | | Adopt for | Jupyter Notebook is an open-source web application that facilitates the creation and sharing of documents with live code, equations, visualizations, and narrative text. | A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. | | Persona | - | - | | Runtime | - | - | | License | Jupyter Notebook is distributed under the terms of the Modified BSD License. | CC0-1.0 | | Categories | Developer Tools | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [notebook](/tools/jupyter-notebook.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 32d | | Open issues (now) | 1.9k | 107 | | Stars delta | +67 (30d) | +22k (30d) | | Open issues delta | -11 (30d) | +7 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/jupyter-notebook/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Decision facts: notebook - **Pricing:** freemium - Jupyter Notebook is free and open-source, but additional features or services may require a paid plan. - **Requirements:** Min 2 GB RAM; Ensure pip is installed for local installation.; Remote installation requires additional configuration. - **Adopt for:** Jupyter Notebook is an open-source web application that facilitates the creation and sharing of documents with live code, equations, visualizations, and narrative text. - **License detail:** Jupyter Notebook is distributed under the terms of the Modified BSD License. ## Decision facts: awesome - **Adopt for:** A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. ## Choose when ### Choose notebook if… - License: notebook is BSD-3-Clause, awesome is CC0-1.0. - Pricing: Jupyter Notebook is free and open-source, but additional features or services may require a paid plan.. - Requirements: Min 2 GB RAM; Ensure pip is installed for local installation.; Remote installation requires additional configuration.. - Tags unique to notebook: development, documentation, installation, interactive. - Use Jupyter Notebook when you need an interactive environment for data analysis, visualization, and sharing of computational narratives. ### Choose awesome if… - License: awesome is CC0-1.0, notebook is BSD-3-Clause. - Tags unique to awesome: awesome, awesome-list, lists, resources. - When you need well-organized access to diverse technical subjects from IoT to robotics ## When NOT to use notebook - Avoid using Jupyter Notebook for production-level code deployment, as it is primarily designed for experimentation and prototyping. - Not recommended for large-scale data processing tasks that require high performance and scalability, as it may not handle such tasks efficiently. - Not suitable for projects that require strict code versioning and control, as the notebook format can complicate traditional version control practices. ## 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 notebook and awesome? notebook: Jupyter Interactive Notebook. awesome: 😎 Awesome lists about all kinds of interesting topics. See the comparison table for live GitHub stats and shared categories. ### When should I choose notebook over awesome? Choose notebook over awesome when License: notebook is BSD-3-Clause, awesome is CC0-1.0; Pricing: Jupyter Notebook is free and open-source, but additional features or services may require a paid plan.; Requirements: Min 2 GB RAM; Ensure pip is installed for local installation.; Remote installation requires additional configuration.; Tags unique to notebook: development, documentation, installation, interactive; Use Jupyter Notebook when you need an interactive environment for data analysis, visualization, and sharing of computational narratives. ### When should I choose awesome over notebook? Choose awesome over notebook when License: awesome is CC0-1.0, notebook is BSD-3-Clause; Tags unique to awesome: awesome, awesome-list, lists, resources; When you need well-organized access to diverse technical subjects from IoT to robotics. ### When should I avoid notebook? Avoid using Jupyter Notebook for production-level code deployment, as it is primarily designed for experimentation and prototyping. Not recommended for large-scale data processing tasks that require high performance and scalability, as it may not handle such tasks efficiently. Not suitable for projects that require strict code versioning and control, as the notebook format can complicate traditional version control practices. ### 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 notebook or awesome more popular on GitHub? awesome has more GitHub stars (514,268 vs 13,346). Stars measure visibility, not whether either tool fits your constraints. ### Are notebook and awesome open source? Yes - both are open-source projects on GitHub (notebook: BSD-3-Clause, awesome: CC0-1.0). ### Where can I find alternatives to notebook or awesome? GraphCanon lists graph-backed alternatives at [notebook alternatives](/tools/jupyter-notebook/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([notebook markdown twin](/tools/jupyter-notebook/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/jupyter-notebook-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, notebook or awesome? notebook: Very active. awesome: Steady. 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 notebook and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [notebook trust report](/tools/jupyter-notebook/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jupyter-notebook`](/api/graphcanon/graph?tool=jupyter-notebook) - 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/_