📦 uv IS the Future of Python Packaging! 🐍📦 (youtube.com)
We’ve heard a lot about the new tool “uv” lately, and here’s a video from Hynek Schlawack that explains well why!
🔬 Numpy QuadDType: Quadruple Precision for Everyone (quansight.org)
The author presents a new Numpy type for quadruple precision that addresses the limitations of the “longdouble” type, with two example usages at the end.
🦆 DuckDB in Python in the Browser with Pyodide, PyScript, and JupyterLite (duckdb.org)
A lot of interesting stuff here! First, PyScript and JupyterLite allow you to work in a Python environment right from your browser without needing to install anything. Then, DuckDB can be summed up as “SQLite in super fast columnar mode”; I admit that’s a bit of a rough description but it should resonate with those familiar with SQLite and databases.
📁 __init__.py files are optional. Here’s why you should still use them (dev.arie.bovenberg.net)
If like me you always wonder why we have carry around all these empty __init__.py files, here’s a bit of an answer.
⚙️ Should you use uv’s managed Python in production? (pythonspeed.com)
A very interesting feature of uv is its ability to quickly and locally install a so-called “standalone” Python distribution; this article raises the question of whether this Python distribution can be used in production. Ultimately, beyond the answer, the most interesting part here is understanding what makes a Python distribution “production-ready.”
🧩 Structural Pattern Matching in Python (realpython.com)
A tutorial from Real Python on the major new feature of Python 3.10 known as “structural pattern matching”, which to put it simply is a match/case with quite advanced possibilities; in certain situations this can greatly simplify your code while remaining readable.
🧪 My NumPy Year: Creating a DType for the Next Generation of Scientific Computing (quansight.com)
The second article this month from Quansight folks on the design of a new Numpy dtype, this time it’s about the new string dtype that landed in Numpy v2 to more efficiently manage variable-length strings.
⏳ Make It Ephemeral: Software Should Decay and Lose Data (lucumr.pocoo.org)
An interesting take by Armin Ronacher (who has been mentioned here before, author of Flask, Click, Rye, etc) urging developers to more explicitly plan for the obsolescence of data generated and stored in applications.
🔥 Python dependency management is a dumpster fire (nielscautaerts.xyz)
An (yet another) article on Python dependency management but with the merit of providing a fairly comprehensive, detailed, and up-to-date recap (things are moving quickly right now) of the different existing tools.
🔁 Loop targets (nedbatchelder.com)
This short post sheds light on the fact that a for-loop is nothing more than the “repetition of an assignment” to the loop variable, which can ultimately be anything like a new entry in a dict. Have a peek at the example to see for yourself. Is this really Pythonic?