Sponsored Projects
Welcome to our two new Sponsored Project: Parsl!
Parsl
Parsl is a flexible and scalable parallel programming library for Python that enables concurrent execution by annotating functions as tasks, managing dependencies, and efficiently running programs across diverse computing environments from, laptops to supercomputers.
Scientific Python
We are happy to announce that we are setting up infrastructure for multiple project websites to be translated.
You can read more in this blog post: https://blog.scientific-python.org/scientific-python/translations/
We also have some documentation at https://scientific-python-translations.github.io/
If you are interested in joining this effort, feel free to engage in the `#translation` channel of the Scientific Python Discord server, where we can provide more information.
See you there! Check out our blog.
Translations for Scientific Python projects: Setting up and managing translations for Scientific Python projects. Scientific Python Translations
Mission: To develop and publish translations of the websites for the Scientific Python Core Projects. Funding is supported by the CZI Scientific Python Community & Communications Infrastructure grant. See Translations into Brazilian Portuguese and Japanese are already published for https://numpy.org/!
Join the Scientific Python Discord Server!
Check out the Scientific Python community on Discord — hang out with 465 other members and enjoy free voice and text chat.
Scientific PythonReady to grow your accessibility awareness this fall? Join the Scientific Python project and Quansight Labs on October 1 and October 15 for two open-to-all events describing digital accessibility basics and actions you can take to improve the accessibility of your own work. Learn more and register on the event announcement blog post!
Ready to grow your accessibility awareness this fall? Join the Scientific Python project and Quansight Labs on October 1 and October 15 for two open-to-all events describing digital accessibility basics and actions you can take to improve the accessibility of your own work. Learn more and register on the event announcement blog post!
It’s easier to get big clusters. Thanks to improvements in adaptive scaling and cross-zone AWS clusters, it’s now much easier to get clusters with 1000s of virtual machines on AWS. See the release notes.
Faster software environment builds. Package sync now uses uv, a faster Rust-powered package resolver, instead of pip for environment builds. This is part of a larger effort to have clusters up and running faster. Learn more about package sync.
Coiled + Arraylake for big geoscience. Arraylake, a cloud data lake platform for managing multidimensional arrays, integrates well with Coiled+Dask. Learn more.
Help us build a geospatial benchmark suite. The Xarray/Dask/… software stack is great for geospatial workloads, but past around the TB scale, these tools struggle and require niche expertise to run well. With Dask DataFrame, end-to-end benchmarks were critical to directing engineering efforts, but with geospatial workloads, there’s nothing like that. Learn more about what we’re looking for in our blog post.
Automatic shutdown of stuck clusters. Sometimes Dask clusters get stuck. But that doesn’t mean your VMs have to stay on. If your cluster is stuck and the scheduler is unresponsive for at least 20 minutes, Coiled will now automatically shut down your VMs for you. Learn more in the release notes.
Events
FOSS4G NA. Join us in St. Louis to check out some of our talks or stop by the booth:
Next Dask Demo Day is on October 3rd. Watch last month’s recording on using Dask for scalable computing in Astronomy. Join us for live community demos and updates from Dask maintainers. Have something you’d like to share? Let us know.
Dask + Streamlit. Join us in San Francisco on Oct. 3rd to see how to use Dask + Streamlit for ETL pipelines (and grab a t-shirt). Register here.
ODSC West. Join us in San Francisco from Oct. 29 to 30. Stop by the booth and say hi; we’ll be across from NVIDIA.
SciPy 2024 talk recordings are available:
- Pandas + Dask DataFrame 2.0 — Dask vs. Spark, DuckDB, Polars
- Lessons Learned from Deploying a Million Dask Clusters in Production
Just signed up for Coiled?
Watch our short demo to see how to get started. It’s easy to connect Coiled to your AWS, GCP, or Azure account.
New to Dask?
Check out our tutorials on using Dask DataFrames, parallelizing your Python code, plus more advanced use cases.
CuPy
We have just released CuPy v13.3.0! Refer to the release note for details:
https://github.com/cupy/cupy/releases/tag/v13.3.0
We opened a new RFC issue on removing NumPy Fallback Mode in CuPy v14. If you have any comments or use cases using this feature, please react/join the discussion at https://github.com/cupy/cupy/issues/8497.
Spyder
We’re pleased to announce that Spyder 6.0.1 has been released and is available for Windows, GNU/Linux, and MacOS X: https://github.com/spyder-ide/spyder/releases
This release comes three weeks after version 6.0.0 and it contains the following important fixes:
- Fix Spyder hanging at startup on Linux when started in a terminal in background mode.
- Fix appeal/sponsor Spyder message being shown at every startup.
- Fix the error that prevented mouse clicks in Spyder from working on the Windows Subsystem for Linux.
- Avoid crashes at startup from faulty/outdated external plugins.
- Fix Spyder installer not being able to finish installation due to Start Menu entry error in some Conda installations.
- Fix the Spyder installer not installing the right Spyder version (6.0.0 vs 6.0.0rc2)
- Fix Binder instance with example workshop project from being non-responsive.
- Fix errors related to unmaximizing panes and layout changes.
In this release, we fixed 14 issues and merged 20 pull requests. For a full list of fixes, please see our Changelog.
Don’t forget to follow Spyder updates/news on the project’s website.
Last but not least, we welcome any contribution that helps make Spyder an efficient scientific development and computing environment. Join us to help create your favorite environment!
Holoviz
Panel 1.5.0 is finally released. You can get it from PyPI and shortly from conda-forge.
For an overview of the changes in this release see: https://blog.holoviz.org/posts/panel_release_1.5/
And for a full changelog take a look at https://github.com/holoviz/panel/releases/tag/v1.5.0
Many, many thanks to everyone who contributed whether by making PRs or by reporting issues!
pandas
We are pleased to announce the release of pandas v2.2.3.
This is a patch release for the 2.2.x series, which includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.
See the release notes for a list of all the changes.
The release can be installed from PyPI
python -m pip install — upgrade pandas==2.2.3
Or from conda-forge
conda install -c conda-forge pandas==2.2.3
Please report any issues with the release on the pandas issue tracker.
Thanks to all the contributors who made this release possible.
Julia
We are happy to announce JuliaCon Global 2025 will be held in Pittsburgh, Pennsylvania at the end of July 2025! julialang.org
JuliaCon Global 2025 and JuliaCon 2024 Wrap-Up
JuliaCon Global 2025 and JuliaCon 2024 Wrap-Up Blogpost.
In the same blog post, we are also announcing a call for committee members for JuliaCon Global 2025 as well as a new effort called Julia Online, where you can make video proposals for the main Julia Language YouTube Channel.
Please check it out and stay tuned for more information!
– JuliaCon 2025 Organizing Committee
Affiliated Projects
Welcome to our two new Affiliated Projects!
toqito
The toqito package is an open-source library for studying various objects in quantum information, namely, states, channels, and measurements. toqito provides numerical tools to study problems about entanglement theory, nonlocal games, and other aspects of quantum information often associated with computer science.
Folium
Folium builds on the data-wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library. Manipulate your data in Python, then visualize it in a Leaflet map via Folium.
estimagic / optimagic
The estimagic project has re-branded to optimagic.
