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Ned Batchelder: Making git hooks visible

Link: https://nedbatchelder.com/blog/202610/making_git_hooks_visible

Frank Wiles wrote about an attack he nearly fell victim
to: a downloaded git repo had active git hooks that would have compromised
his system. Seeing the risks, I wanted to make git hooks more visible
Mahmoud Hashemi: CalVer 26.0: 10th Anniversary Edition

Link: https://sedimental.org/calver_26.html


A decade ago, a little bit of history was made. I didn't realize it, but a colleague made a great point, one of those real mind-changing points that seem too obvious to admit same-day. But, the next
LernerPython blog, from Reuven Lerner: Pandas groupby: Multiple columns and multiple aggregation methods

Link: https://lernerpython.com/2026/10/11/pandas-groupby-multiple-columns-and-multiple-aggregation-methods/


Does Python Pandas allow multiple categorical columns and multiple methods?
Yes!
df.groupby(['passenger_count', 'VendorID'])['trip_distance'].agg(['mean', 'std'])
The above returns:
– A 2-column data
Kay Hayen: Nuitka Release 4.3

Link: https://nuitka.net/posts/nuitka-release-43.html

This is to inform you about the new stable release of Nuitka. It is the extremely compatible Python compiler,
“download now”.
This release adds many new features and corrections with a focus on
experi
Rodrigo Girão Serrão: Explicit lazy imports

Link: https://mathspp.com/blog/explicit-lazy-imports


Learn how to use lazy imports to speed up the startup time of your Python applications.
Python 3.15 introduced explicit lazy imports.
An explicit lazy import is an import statement that starts with t
LernerPython blog, from Reuven Lerner: Pandas groupby: Aggregating multiple columns with multiple functions

Link: https://lernerpython.com/2026/10/12/pandas-groupby-aggregating-multiple-columns-with-multiple-functions/


Does Python Pandas allow multiple data columns and multiple methods?
Yes!
df.groupby('passenger_count')[['trip_distance', 'total_amount']].agg(['mean', 'std'])
The above returns a data frame. Its 4 c
Seth Michael Larson: Gaming’s all-digital future doesn’t include “Sonic the Hedgehog 3” and “Pikmin 2”

Link: https://sethmlarson.dev/gaming-all-digital-future-and-creative-constraint?utm_campaign=rss

Sony announced that all games from 2028 and onwards
would be digital-only. It seems likely that Xbox will follow and that Nintendo will continue
making “physical” releases for first-party games during
Rodrigo Girão Serrão: Sentinel built-in

Link: https://mathspp.com/blog/pydonts/sentinel-builtin


Learn how to use the sentinel built-in from Python 3.15 for placeholder values.
Python 3.15 introduced the new sentinel built-in.
The sentinel built-in can be used to create placeholder values:
NOTHI
PyCoder’s Weekly: Issue #756: 3.15 Released For Real This Time, Muse, and More (2026-10-13)

Link: https://pycoders.com/issues/756

#756 – OCTOBER 13, 2026 View in Browser » The 5 Most Exciting New Features of Python 3.15 This article explains the 5 best new features of Python 3.15 with clear examples and explanations. RODRI
Python Bytes: #500 Episode 500!

Link: https://pythonbytes.fm/episodes/show/500/episode-500

Topics covered in this episode:

A quick chat with Brian looking back
Extras
Joke
Watch on YouTube
About the show
Brian #1: A quick chat with Brian looking back
Nick #2: Jev and the Case for Boring ML
PyPy: PyPy v8.0.1 release

Link: https://www.pypy.org/posts/2026/10/pypy-v801-release.html

PyPy v8.0.1: release of python 2.7, 3.11, and 3.12 beta released 2026-09-14
The PyPy team is proud to release version 8.0.1 of PyPy after the previous
release on Sept 25, 2026. Some problems with buff
Mark Dufour: CPython 3.15 (JIT) Performance Showdown

Link: http://shed-skin.blogspot.com/2026/10/cpython-315-jit-performance-showdown.html

Now that CPython 3.15 has been released, I decided to do a historical performance comparison similar in spirit to Sixteen Years of Python Performance. Obviously I wanted to include CPython 3.15, but I
Rodrigo Girão Serrão: frozendict built-in

Link: https://mathspp.com/blog/pydonts/frozendict-builtin


Learn how to use the new frozendict built-in to create and manipulate immutable dictionaries.
Python 3.15 introduced a new built-in data type: the frozendict.
A frozendict is an immutable dictionary
Bob Belderbos: My bookkeeping runs on code now. AI only reads the PDFs.

Link: https://belderbos.dev/blog/replaced-my-bookkeeping-tool-with-python/

I paid for a popular bookkeeping tool and it worked well. But the UI kept getting slower, and I wasn't using its reporting, so I had no real view of my numbers.
So I did what I usually do: I scoped a
LernerPython blog, from Reuven Lerner: Pandas groupby on datetime parts with the dt accessor

Link: https://lernerpython.com/2026/10/14/pandas-groupby-on-datetime-parts-with-the-dt-accessor/


If your Python Pandas data frame has a datetime column, you can group on a portion of that via the “dt” accessor.
For example, let’s get mean trip_distance for each hour of the day:
df.groupby(df['tp
Artem Golubin: Python's binary wheels and supply chain attacks

Link: https://rushter.com/blog/python-binary-wheels/

Python is known for fast packages despite being a slow language.
The fastest Python packages are written in compiled languages such as C, C++, or Rust,
with Python acting only as a glue.
Python users
Rodrigo Girão Serrão: Unpacking inside comprehensions

Link: https://mathspp.com/blog/unpacking-inside-comprehensions


Learn how to use the unpacking operator inside list comprehensions.
Starting with Python 3.15, you can use the asterisk * to unpack inside list comprehensions:
nested = [[0, 1, 2], [3, 4], [], [5, 6,