Sylvain Corlay

🧪 DataLab-Kernel | Advanced plotting showcase

Running in the browser via notebook.link from @quantstack.bsky.social

The plotter now implements all core DataLab visualization features

Standalone demo — no DataLab required

DataLab-Kernel: github.com/DataLab-Plat...
DataLab: datalab-platform.com

JupyterLite Officially Joins Project Jupyter! We are thrilled to announce that JupyterLite is now an official part of Project Jupyter. This milestone marks a significant step forward…

🎉 JupyterLite is now part of Project Jupyter!

Run Jupyter notebooks directly in your browser: no server, no setup.

Many thanks to the JupyterLite contributors and supporters like QuantStack, Bloomberg and the Gates Foundation.

🔗 blog.jupyter.org/jupyterlite-...

🧪 Sigima, running in the browser thanks to notebook.link from @quantstack.bsky.social

The scientific signal & image processing engine behind DataLab (datalab-platform.com), now executable directly in a @jupyter.org notebook (no local install required).

Lightweight, reproducible, easy to share.

Introducing notebook.link: The Future of Notebook Sharing Reimagining how you share, collaborate, and run Jupyter notebooks — all in your browser.

🧪 Awesome announcement from the @quantstack.bsky.social team! Introducing notebook.link, share your computational notebook and have them run directly in the browser with no setup, powered by Jupyterlite and the xeus stack.

#datascience #scientificcomputing

🧪 Live experiment using notebook.link from @quantstack.bsky.social

A notebook with DataLab-Kernel (github.com/DataLab-Plat...), a Xeus-Python JupyterLite-compatible kernel, connects automatically to a running local DataLab app (datalab-platform.com).

No config. Auto-discovery.

It simply works.

🧪 Experimenting with notebook.link from @quantstack.bsky.social, and DataLab-Kernel (github.com/DataLab-Plat...), a Xeus-Python JupyterLite-compatible kernel.

Goal: share fully interactive DataLab-powered notebooks directly in the browser.
Looks promising for demos, docs, and reproducible examples!

A viewer for Parquet, SQLite, and Avro files in JupyterLab.
Check out our new JupyterLab extension: Arbalister. 🏹
Built upon Apache Datafusion, @jupyter.org , and @arrow.apache.org , it lazily fetches rows so that you can view files larger than memory!

blog.jupyter.org/instantly-vi...

Pandas 3.0 was just released yesterday!! 🤘

And guess what? You can already play with it in Notebook.link.

I quickly built a Notebook.link link for you to play with it now:
notebook.link/@martinRenou...

It's public for everyone to use, and it's powered by free / open source software that we at QuantStack actively contribute to.

(note: I didn't work on this)

We are thrilled to introduce notebook.link, a platform that lets you create, share, and run Jupyter notebooks instantly in your browser.

Powered by JupyterLite and WebAssembly, it supports Python, R, C++, and a full in-browser terminal experience.

📖 Read the full story: medium.com/@QuantStack/...

YouTube video by PyData Jeremy Tuloup & Nicolas Brichet - Browser-based AI workflows in Jupyter

Together with @nicolasbrichet.bsky.social at @pydataparis.bsky.social 2025, we presented a vision for what AI @jupyter.org can look like, with a focus on forward-looking, browser-based AI workflows 🤖

The recording is now available on YouTube, happy watching!

www.youtube.com/watch?v=cKeu...

JupyterLite now supports any-llm-gateway as a backend for its AI static front-end.

any-llm-gateway routes LLM requests through a single gateway rather than tying usage to one provider.

Integration details: link.mozilla.ai/jupyterlite-...

All talks are now online - perfect for cozy learning by the fire. 🎄🔥
🎁 Watch here: www.youtube.com/playlist?lis...
Missed a session? Now’s your chance! Share your favorites and keep the inspiration going.
Wishing you a season of learning and innovation!

Teaching a Billion People to Code: How JupyterLite Is Scaling the Impossible QuantStack, an “almost accidental startup,” is building a serverless distro of JupyterLab for Jupyter’s global adoption.

@quantstack.bsky.social, an “almost accidental startup,” is building a serverless distro of @jupyter.org for Jupyter’s global adoption.

Feat. @sylvaincorlay.bsky.social

🚀 JupyterLite 0.7 is now available!

- Support for workspaces
- Audio / video playback
- Interrupt execution queue
- Basic notebook export
- Notebook scrolling fixes

➡️ Try it: jupyter.org/try-jupyter
➡️ Walkthrough video: www.youtube.com/watch?v=utNt...
➡️ Blog post: blog.jupyter.org/jupyterlite-...

SIMD coding is hard: platforms, inconsistencies, lane constraints... but xsimd abstracts a lot away. With my first contributions, I improved byte shuffling, now available in the latest 14.0 release.
#C++ #SIMD #xsimd #openSource

Teaching a Billion People to Code: How JupyterLite Is Scaling the Impossible QuantStack, an “almost accidental startup,” is building a serverless distro of JupyterLab for Jupyter’s global adoption.

@quantstack.bsky.social, an “almost accidental startup,” is building a serverless distro of @jupyter.org for Jupyter’s global adoption.

Feat. @sylvaincorlay.bsky.social

YouTube video by JupyterCon GeoJupyter: An Open Community for Accessible, Collaborative, and Interactive... M. Fisher & F. Pérez

Missed #JupyterCon25? You can catch up on YouTube! Check out @mfisher87.bsky.social and @fernandoperez.org's live demo of #GeoJupyter tools to help open and democratize geospatial data analysis: www.youtube.com/watch?v=c5h7...

📹More from JupyterCon: www.youtube.com/@JupyterCon

JupyterLab 4.5 and Notebook 7.5 are available! JupyterLab 4.5 has been released! This new minor release of JupyterLab includes 51 new features and enhancements, 81 bug fixes, 44…

JupyterLab 4.5 and Jupyter Notebook 7.5 are here! 🎉

Highlights 🎁

- Enhanced notebook scrolling behavior
- Native audio and video support
- New Terminal search
- Debugger, Notebook and File Browser improvements

Check out the blog post to learn more!

blog.jupyter.org/jupyterlab-4...

Jupyter Community Workshops: Early 2026 The Jupyter Community Building Working Group is happy to announce the Jupyter Community Workshops selected for funding in early 2026. The…

Project Jupyter has funded a series of community workshops for 2026, covering a broad range of subjects from Jupyter-AI to JupyterHub, Myst Markdown, and security. Check out our announcement on the Jupyter blog for more details.

blog.jupyter.org/jupyter-comm...

Why am I on this picture? 😀

From Physics to the Future: Brian Granger on Project Jupyter in the Age of AI The co-creator of Jupyter notebooks discussed the project's origins and how AI is opening new options for large open source projects, in this episode of The New Stack Makers.

The co-creator of Jupyter notebooks discussed the project's origins and how AI is opening new options for large open source projects, in this episode of The New Stack Makers.

JupyterGIS breaks through to the next level Launched in June 2024, JupyterGIS was introduced as a collaborative, web-based GIS environment built on the JupyterLab framework. Its objective is to bring QGIS-inspired workflows into the browser, enabling real-time collaborative editing, seamless integration with notebooks, and support for core geospatial data formats. When it was first announced earlier this year, JupyterGIS already delivered: * Real-time collaborative editing (Google Docs-style) * Visualisation of raster & vector data * Symbology editing and spatio-temporal animations * Programmatic map control via a Python API. Thanks to contributions from the community and support from partner organizations, JupyterGIS has advanced significantly and now offers an expanded range of features for analysis, visualization, and collaboration. **Enhanced vector tile capabilities** Support for vector tiles has been strengthened, including full compatibility with the _pmtiles_ format. Other key updates include: * An _identify tool_ that inspects vector tiles to display features and associated properties. * A _symbology panel_ that applies graduated, categorized, and canonical symbology to vector tile layers. These improvements enhance the interpretability and styling of geospatial datasets directly in the browser. The identify tool in action with a pmtiles vector dataset. The symbology panel in action, allowing for different notations. **A new processing toolbox** One of the most significant updates is a new browser-based processing toolbox powered by a WebAssembly (WASM) build of the Geospatial Data Abstraction Library (GDAL). Available tools include: * _Buffer_ : computes a buffer around geometries of a vector dataset. * _Convex Hull_ : calculates the convex hull for each feature of an input layer. * _Dissolve_ : combines features of vector layers into new features * _Bounding Boxes_ : calculates the bounding box for each feature in an input layer. * _Centroid_ : creates a new layer with the centroids of the geometries of an input layer. * _Concave Hull_ : computes the concave hull for each feature of an input point layer. This toolbox has been designed for extensibility, with a JSON schema that allows additional GDAL operations to be integrated in a straightforward manner. Using the processing tool to compute the convex hulls of geometries. **Symbology enhancements** Visualization of geospatial data has become more flexible and expressive through several enhancements: * _Viridis_ is now the default colormap, providing perceptually uniform visualization. * _Multiband symbology_ is now available for GeoTIFFs. * _Canonical symbology_ defined in GeoJSON files can be applied automatically. * _Colormaps_ can now be _reversed_ , allowing greater flexibility for data interpretation and visualization. * In the case of _point layers_ , color and marker size can be styled independently, and bound to different data. Setting color and radius based on data. **Integration with SpatioTemporal Asset Catalogs (STAC)** A SpatioTemporal Asset Catalog (STAC) browser is now embedded into JupyterGIS, streamlining access to different data collections. Users can select specific platforms and sensors, choose data products and processing levels, and set temporal and spatial constraints. It is now possible to search across multiple datasets simultaneously. Users can click on any result to add it directly as a layer to their JupyterGIS project. This creates a seamless workflow from data discovery to visualization, making it easier for researchers and analysts to find and integrate relevant satellite imagery and geospatial datasets into their Jupyter notebooks. Currently, the STAC Browser only supports the Geodes STAC API but support for all STAC catalogs is under way. Browsing a STAC access catalog from JupyterGIS. **Support for more data types** The range of supported geospatial data formats is now broadened with _GeoParquet_ and _PMTiles_**,** enabling efficient columnar storage and fast analytical queries for GeoParquet, and highly compact, streaming-friendly vector tile delivery for PMTiles. **User experience and interface improvements** The interface has been refined for a smoother workflow: * _Integrated control panels_ (layer list, filters, layer properties, etc.), reducing back and forth between the JupyterLab side-panels and the JupyterGIS UI. It also improves the “single document” scenario, allowing it to interact with JupyterGIS controls when opening a GIS document from the classic Jupyter Notebook UI. * An improved _toolbar design_ , with cleaner icons and better usability. * A new feature to center the map on your _current location_. * _Map annotations_ now link to the map: clicking an annotation automatically re-centers and zooms to the location. * _Full-screen_ mode support. **Legends for vector layers** JupyterGIS now automatically generates legends for vector layers, ensuring consistent interpretation: * Legends are dynamically updated to reflect current symbology. * Customizations such as reversed colormaps are preserved. Displaying legends in the layers panel. **JupyterGIS tiler extension** An extension for JupyterGIS enables the creation of JupyterGIS layers from _xarray variables_ in Jupyter kernels, with support for lazy evaluation, bridging geospatial workflows with powerful array-based computation. The package, called JupyterGIS-tiler, is available in GitHub here and can be installed from PyPI with _pip install jupytergis-tiler_. **Looking ahead** Development will continue to expand JupyterGIS in several directions: * Extension of the GDAL-based processing toolbox. * Deeper integration with QGIS and a richer Python API for automation. * A Story Maps Editor and Viewer to enable interactive communication of geospatial information through text, imagery, and maps. In the meantime, feel free to try JupyterGIS directly in your browser with JupyterLite, no installation required. Opportunities for engagement also include: * Checking out documentation for tutorials and the Python API. * Discussions via the GeoJupyter Zulip channel or the bi-weekly GeoJupyter hackathon. * Contributions to the development repository. The JupyterGIS community continues to grow, and active participation from researchers, developers, and educators worldwide is encouraged.

Hello, #gis #earthobservation #geospatial Has anyone tried JupyterGIS->https://eo4society.esa.int/2025/10/16/jupytergis-breaks-through-to-the-next-level It does look quite a tasty stir fry of jupyter lab and a (still) simple GIS thing, but potentially quite useful. #python

It's day 1 of #PyDataParis, great venue & crowd. Looking forward to sharing some geospatial perspectives tomorrow

Apache Arrow Summit, Thu, Oct 2, 2025, 9:30 AM | Meetup The day after the PyData Paris conference, we’re excited to host the first-ever Apache Arrow Summit - a gathering dedicated to fostering collaboration and innovation within

The schedule for the Apache Arrow Summit Paris 25 (October 2nd) is out: www.meetup.com/pydata-paris....
The event is hosted by
@pydataparis.bsky.social organizer of pydata.org/paris2025 (September 30th - October 1st)

We are looking forward to seeing you there and talking about all things Arrow.

📢 Talk Announcement

"Open-source Business", by @sylvaincorlay.bsky.social from @quantstack.bsky.social and @ylechelle.bsky.social from @probabl.ai

📜 Talk info: pretalx.com/pydata-paris-2025/talk/LMTCZS
📅 Schedule: pydata.org/paris2025/schedule
🎟 Tickets: pydata.org/paris2025/tickets

📢 Talk Announcement

"Sparrow, Pirates of the Apache Arrow", by Johan Mabille and Alexis Placet.

📜 Talk info: pretalx.com/pydata-paris-2025/talk/YBFPCR
📅 Schedule: pydata.org/paris2025/schedule
🎟 Tickets: pydata.org/paris2025/tickets

Welcome to our new sponsor inria !

📢 Talk Announcement

"Big ideas shaping scientific Python: the quest for performance and usability", by Ralf Gommers.

📜 Talk info: pretalx.com/pydata-paris-2025/talk/YBFPCR
📅 Schedule: pydata.org/paris2025/schedule
🎟 Tickets: pydata.org/paris2025/tickets

Schedule overview for JuliaCon Local Paris 2025. Full information available at https://pretalx.com/juliacon-local-paris-2025/schedule/

Software enthusiasts of all fields and backgrounds, unite! Here's the exciting schedule we cooked up for #JuliaCon Local Paris 2025 (the one for #PyData is just as thrilling!).
Get your tickets while you can, and see you in a month ⌛
@julialang.org @juliacon.bsky.social @pydataparis.bsky.social