datapythonista
Rust is showing impressive results in its way to the Linux kernel. Not long ago Linus anticipated Rust could land as a kernel language next year, or in next release. Today at Linux Plumbers conference results on a new NVMe driver coded in Rust were presented…
Big news for the Linux kernel. Version 6.0 has been just released, and the first Rust code landed in its code base not long after: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=8aebac82933ff1a7c8eede18cab11e1115e2062b
I'll be speaking about pandas performance in the ThaiPy meetup in Bangkok next week: https://www.meetup.com/thaipy-bangkok-python-meetup/events/288135175/
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After removing big tech tracking, banners and youtube ads, now the Brave browser is planning to remove cookie notifications and disable non-essential cookies. Looking forward to it: https://www.techradar.com/news/brave-is-about-to-solve-one-of-the-most-frustrating-problems-with-browsing-the-web
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I'll be speaking about the future of data engineering in Python at GITEX Dubai next week. Ping me if you are around. https://globaldevslam.com/
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Very interesting discussion about memory profilers with Pablo Galindo Salgado, CPython core developer and release manager. Pablo has been doing an amazing job at optimizing CPython memory usage, and he is the main developer of memray, a memory profiler. A memory profiler helps understand which parts of a program are responsible for memory usage, see how a program uses memory over time, or see what is its memory usage at the peak (to know how much available memory is needed to run the program): https://realpython.com/podcasts/rpp/128/
Realpython
Episode #128: Using a Memory Profiler in Python & What It Can Teach You – The Real Python Podcast
Have you used a memory profiler to gauge the performance of your Python application? Maybe you're using it to troubleshoot memory issues when loading a large data science project. What could running a profiler show you about a codebase you're learning? This…
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TabPFN: An extremly fast ML classifier for small tabular data: https://www.automl.org/tabpfn-a-transformer-that-solves-small-tabular-classification-problems-in-a-second/
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CPython 3.11 has been released this week. The main change is an increase in performance, it's between 10% to 60% faster based on the CPython benchmarks.
I tested the #pandas benchmarks with pandas 3.10 and pandas 3.11, and they are less than 1% faster with the new version (all critical code in #Python data projects is in C, not in Python).
Exceptions got couple of improvement, and there are several additions to typing.
For the Python data community, in my opinion the main improvement to Python would be to be able to overwrite the
I tested the #pandas benchmarks with pandas 3.10 and pandas 3.11, and they are less than 1% faster with the new version (all critical code in #Python data projects is in C, not in Python).
Exceptions got couple of improvement, and there are several additions to typing.
For the Python data community, in my opinion the main improvement to Python would be to be able to overwrite the
and and or operators in our libraries (pandas and numpy mainly). I wrote about it in this post.It's great to see a new chapter of the #Python sprints group. This one in Zurich. Get started or help others get started in the free software world if you're in the Zurich area: https://python-sprints.github.io/chapters/zurich_python_sprints.html
python-sprints.github.io
Python Sprints - Zürich Python Sprints
Python Sprints is a non for profit group gathering coders who want to help improve open source projects using Python programming language.
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#pandas 2.0 will be released soon. I wrote about one of the most important changes we're shipping with it.
https://datapythonista.me/blog/pandas-20-and-the-arrow-revolution-part-i
https://datapythonista.me/blog/pandas-20-and-the-arrow-revolution-part-i
datapythonista blog
pandas 2.0 and the Arrow revolution (part I)
Introduction At the time of writing this post, we are in the process of releasing pandas 2.0. The project has a large number of users,...
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Do you have any question about #pandas? Few core devs including myself will be answering questions in an AMA (ask me anything) session. Officially scheduled for tomorrow Thursday at 5:30pm UTC, but already open.
https://www.reddit.com/r/Python/comments/11fio85/we_are_the_developers_behind_pandas_currently/
https://www.reddit.com/r/Python/comments/11fio85/we_are_the_developers_behind_pandas_currently/
Reddit
From the Python community on Reddit: We are the developers behind pandas, currently preparing for the 2.0 release :) AMA
Explore this post and more from the Python community
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The most popular question at today's #pandas ask me anything session was if pandas 2.0 is going to break your code.
Short answer: No.
But if your code has any FutureWarning in 1.5.3, you need to fix it before you upgrade to 2.0.
Short answer: No.
But if your code has any FutureWarning in 1.5.3, you need to fix it before you upgrade to 2.0.
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I made a proposal for #pandas to allow being extended with readers and writers to other data formats from third-party packages with a unified API.
For now keeping the current read/to methods, hopefully replacing them in the long term.
Feedback welcome!
For now keeping the current read/to methods, hopefully replacing them in the long term.
Feedback welcome!
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Today is release day, and I'm tweeting live all the pandas 2.0 release progress:
https://mobile.twitter.com/datapythonista/status/1642779019476123649
https://mobile.twitter.com/datapythonista/status/1642779019476123649
X (formerly Twitter)
Marc Garcia (@datapythonista) on X
Good morning. This is your #pandas release manager speaking. Welcome to this open source flight to pandas 2.0. We expect to arrive in 12 to 15 hours. To celebrate this special flight, I'll be live posting all the information about the release in this thread...…
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