Sponsored Project Updates
Blosc
Here are some announcements that we want to share with the community (we have been quite busy with some of them lately):
- The Blosc development team is pleased to announce the first beta release of Python-Blosc2 3.0.0. We have been working hard to provide a new evaluation engine (based on numexpr) for NDArray instances, and we would like to get feedback from the community before the final release. More info at: https://github.com/Blosc/python-blosc2/blob/main/ANNOUNCE.rst
- C-Blosc2 2.15.0 has been released. This time we added a new `io` mode for memory map files. This brings even more I/O performance, especially for reading compressed data on disk. More info: https://github.com/Blosc/c-blosc2/releases
- numexpr 2.10.1 is out. Here, we are consolidating NumPy 2 support, fixing some bugs, preliminary support for Python 3.13, and modernizing the installation procedure. Even if small, numexpr has become an important cornerstone for reaching great performance in packages like pandas, PyTables, Blosc2 and many others. See: https://github.com/pydata/numexpr/blob/master/RELEASE_NOTES.rst
Enjoy data!
rOpenSci
Dear rOpenSci friends, it’s time for our monthly news roundup!
You can read this post on our blog.
CuPy
We have released CuPy v13.2.0!
Please refer to the release note:
https://github.com/cupy/cupy/releases/tag/v13.2.0
DASK
Dask Updates
New machine learning examples. Coiled enhances ML workflows by making it easy to get cloud GPU machines that are automatically configured like your current machine. We’ve added new examples on common use cases like model training, experiment tracking, and interactive development. Learn more.
See more here.
DataFrames at Scale Comparison: TPC-H. We run TPC-H benchmarks on a variety of scales, hardware architectures, and DataFrame projects like Spark, Dask, DuckDB, and Polars. No project wins. Read the blog post.
Dask DataFrame is Fast Now. Dask DataFrame scales out pandas, making it easy to work on hundreds of GBs to TB-scale datasets. Due to a number of performance-focused engineering improvements, Dask is 20x faster. Read the blog post.
See more here.
New to Dask?
Check out our tutorials on using Dask DataFrames, parallelizing your Python code, plus more advanced use cases.
MDAnalysis
See below for the MDAnalysis updates:
- From June 24 to 25th, MDAnalysis partnered with the Molecular Sciences Software Institute (MolSSI) to offer a free, hybrid workshop titled Moving from User to Developer: Analyzing Molecular Simulations and Building New Tools. All workshop materials are publicly available on a GitHub repository.
- Registration for the MDAnalysis UGM, taking place August 21–23, 2024, in London, UK, is now open! To stay up-to-date on the event, check the UGM event page, the MDAnalysis blog, and the MDAnalysis socials (LinkedIn, X, and Bluesky).
GeoPandas
We released GeoPandas 1.0 on Jun 24, 2024
Julia
The Julia developers are pleased to announce that the first release candidate for Julia v1.11.0 is now available. You can download binaries using JuliaUp or from https://julialang.org/downloads/ in the “upcoming release” section. Binaries are available for macOS (M-series and Intel), Windows (32- and 64-bit), glibc Linux (x86, x86_64, AArch64, PowerPC), musl Linux (x86_64), and FreeBSD (x86_64).
As a release candidate, 1.11.0-rc1 should not be considered production-ready. Rather, it’s intended to give users, especially package developers, a chance to try out their code with 1.11.0 prior to a full release. Check out the NEWS file to see what will be new in 1.11.0.
Note that 1.11 on Travis, AppVeyor, and Cirrus now refers to 1.11.0-beta2. On GitHub Actions, use ~1.11.0–0.
Affiliated Project Updates
Trixi.jl
From Trixi.jl we have the following news:
We will be present with three talks at the upcoming JuliaCon 2024 conference in Eindhoven, NL next month:
- Julia for Particle-Based Multiphysics with TrixiParticles.jl,
Erik Faulhaber, Niklas Neher, 10th July 2024, 11:30am–12:00pm, Function (4.1) - Towards Aerodynamic Simulations in Julia with Trixi.jl,
Daniel Doehring, 10th July 2024, 15:00 pm–15:30 pm, While Loop (4.2) - libtrixi: serving legacy codes in earth system modeling with fresh Julia CFD,
Benedict Geihe, 12th July 2024, 14:00 pm–17:00 pm, Function (4.1) - The last talk is part of the Julia for High-Performance Computing mini-symposium, which this year is hosted by our own Hendrik Ranocha.
Visual Python
Recent Release
- Visual Python released version 3.0.2 with significant documentation updates and a bug fix.
Current Updates
- A new manual has arrived. Descriptions for all applications and functions are supported now.
- Bug fixed on Subset, Machine Learning, and Pipeline applications.
New to Visual Python?
- Visual Python is available on Jupyter Notebook, Jupyter Lab, and Colab. To get started, follow our instructions. You can also check out our tutorials on YouTube and Gitbook.
- Are you not using any of them? Then, install our Visual Python Desktop. If you are a Windows user, you can just click Windows on this link to try Visual Python.
For more information, Visit our website(https://visualpython.ai) and Join our community!
Optuna
Optuna has gained 10k stars! Yay!
The next release will be a major update (Optuna v4.0). We are planning to include the following items:
- Stabilization of experimental features, including Artifact and JournalStorage. Optuna will enhance support for these experiment management functions.
- Removal of deprecated features. Note that it will be a breaking change, and we are planning to provide a migration guide for important changes.
- Hideaki Imamura, one of our core developers, will give an invited talk at AutoML Conference in September. Stay tuned!
