A curated list of awesome Jupyter projects, libraries, and resources for data science and interactive computing.
Awesome Jupyter is a curated GitHub repository that aggregates and organizes a wide array of projects, libraries, and resources related to the Jupyter ecosystem. It helps data scientists, researchers, and developers discover tools for enhancing their notebook-based workflows, from interactive visualizations and extensions to deployment and collaboration platforms. The list is community-driven and regularly updated to include the most useful and innovative Jupyter utilities.
Data scientists, researchers, educators, and developers who use Jupyter notebooks or JupyterLab for interactive computing, data analysis, and reproducible research. It's particularly valuable for those looking to extend their workflow with specialized tools or find alternatives to commercial notebook platforms.
It saves time by providing a single, vetted source for discovering Jupyter tools, eliminating the need to scour scattered resources. The list is maintained by the community, ensuring relevance and quality, and covers niche domains that might otherwise be overlooked.
A curated list of awesome Jupyter projects, libraries and resources
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Organizes hundreds of Jupyter tools into clear categories like visualization, collaboration, and domain-specific projects, saving users from scattered searches across the web.
Includes everything from core runtimes like JupyterLab to niche tools for geospatial analysis or quantum computing, ensuring no corner of the Jupyter ecosystem is overlooked.
Maintained through active contributions, with GitHub hits and sponsorships indicating ongoing relevance, though users should verify individual tool updates.
Provides direct links to tutorials, conference talks, and official documentation, supporting both learning and advanced usage without leaving the list.
The list aggregates projects without ratings, reviews, or stability indicators, forcing users to independently evaluate each tool's maintenance and reliability.
With hundreds of entries across numerous categories, beginners or those new to Jupyter may find it overwhelming to navigate and select appropriate tools without guidance.
As a community-maintained project, some links or tools might become outdated or unmaintained, requiring users to check currency before adoption.