Mike C. Fletcher: PyOpenGL 4.0.0a7 -- Cleanup and Preparation
Link: http://blog.vrplumber.com/b/2026/10/11/pyopengl-400a7-cleanup-and-preparation/
4.0.0a7 is closing in on the final form for the 4.0.0 release. There's a raft of bug-fixes from testing and tickets, the Windows GLUT binaries are now a separate python package, documentation system u
Link: http://blog.vrplumber.com/b/2026/10/11/pyopengl-400a7-cleanup-and-preparation/
4.0.0a7 is closing in on the final form for the 4.0.0 release. There's a raft of bug-fixes from testing and tickets, the Windows GLUT binaries are now a separate python package, documentation system u
Vrplumber
Plumbing Life's Depths - PyOpenGL 4.0.0a7 -- Cleanup and Preparation
4.0.0a7 is closing in on the final form for the 4.0.0 release. There's a raft of bug-fixes from testing and tickets, the Windows GLUT binaries are now a separate python package, documentation system updates, and OpenGL_accelerate now pins the OpenGL version…
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
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
LernerPython
Pandas groupby: Multiple columns and multiple aggregation methods - LernerPython
Does Python Pandas allow multiple categorical columns and multiple methods? Yes! The above returns: – A 2-column data frame (mean + std)– A 2-level index (passenger_count + VendorID)
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
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
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
Mathspp
Explicit lazy imports
Learn how to use lazy imports to speed up the startup time of your Python applications.
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
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
LernerPython
Pandas groupby: Aggregating multiple columns with multiple functions - LernerPython
Does Python Pandas allow multiple data columns and multiple methods? Yes! The above returns a data frame. Its 4 columns are a 2-level multi-index with mean/std in the inner level.
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
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
sethmlarson.dev
Gaming’s all‑digital future doesn’t include “Sonic the Hedgehog 3” and “Pikmin 2”
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 dur...
would be digital-only. It seems likely that Xbox will follow and that Nintendo will continue
making “physical” releases for first-party games dur...
PyCharm: Python vs Go: A Practical Comparison for Developers
Link: https://blog.jetbrains.com/go/2026/10/13/python-vs-go/
Link: https://blog.jetbrains.com/go/2026/10/13/python-vs-go/
The JetBrains Blog
Python vs Go: A Practical Comparison for Developers - The JetBrains Blog
We look at how Python and Go differ, what surveys tell us about the devs who use them, and what interviews say about the trade-offs between them.
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
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
Mathspp
Sentinel built-in
Learn how to use the sentinel built-in from Python 3.15 for placeholder values.
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
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
Pycoders
PyCoder’s Weekly | Issue #756
3.15 Released For Real This Time, Muse, and More
Python Insider: Python 3.16.0 alpha 1 is now available
Link: https://blog.python.org/2026/10/python-3160-alpha-1-is-now-available/
The first developer preview of Python 3.16 is ready for testing.
Link: https://blog.python.org/2026/10/python-3160-alpha-1-is-now-available/
The first developer preview of Python 3.16 is ready for testing.
Python Insider
Python 3.16.0 alpha 1 is now available | Python Insider
The first developer preview of Python 3.16 is ready for testing.
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
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
pythonbytes.fm
Episode 500!
News and announcements from the Python community for the week of Oct 14th, 2026
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
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
PyPy
PyPy v8.0.1 release
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
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
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
Blogspot
CPython 3.15 (JIT) Performance Showdown
Now that CPython 3.15 has been released, I decided to do a historical performance comparison similar in spirit to Sixteen Years of Python Pe...
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
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
Mathspp
frozendict built-in
Learn how to use the new frozendict built-in to create and manipulate immutable dictionaries.
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
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
belderbos.dev
My bookkeeping runs on code now. AI only reads the PDFs.
Where AI earned a place in my own accounting system, where it didn't, and why every row it proposes waits for a human.
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
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
LernerPython
Pandas groupby on datetime parts with the dt accessor - LernerPython
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 […]
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
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
Artem Golubin
Python's binary wheels and supply chain attacks
Why precompiled Python wheels are a weak spot in the supply chain security.
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,
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,
Mathspp
Unpacking inside comprehensions
Learn how to use the unpacking operator inside list comprehensions.
PyCon Ireland: Call for sponsors PyCon Ireland 2026
Link: https://main--pycon-ireland-2026.netlify.app/blog/call_for_sponsors/
PyCon Ireland 2026 - Sponsorship Prospectus
Autumn 2026 | Organized by Python Ireland
Overview
PyCon Ireland 2026 is a one-day, multi-track conference featuring talks, tutorials, and workshops, bring
Link: https://main--pycon-ireland-2026.netlify.app/blog/call_for_sponsors/
PyCon Ireland 2026 - Sponsorship Prospectus
Autumn 2026 | Organized by Python Ireland
Overview
PyCon Ireland 2026 is a one-day, multi-track conference featuring talks, tutorials, and workshops, bring
PyCon Ireland 2026
Call for sponsors PyCon Ireland 2026 | PyCon Ireland 2026
We're excited to announce PyCon Ireland 2026, taking place on 21st Nov at Chartered Accountants House, 47-49 Pearse St, Dublin 2, D02 YN40, Ireland. Be part of this event and make use of this opportunity for coporate outreach and brand promotion
LernerPython blog, from Reuven Lerner: Pandas Grouper: Group datetime columns by custom time periods
Link: https://lernerpython.com/2026/10/16/pandas-grouper-group-datetime-columns-by-custom-time-periods/
Want to change the granularity when grouping on a Python Pandas data frame’s datetime column?
Use Grouper.
For example: Here we get the mean trip_distance per 14-day period:
df.groupby(pd.Grouper(k
Link: https://lernerpython.com/2026/10/16/pandas-grouper-group-datetime-columns-by-custom-time-periods/
Want to change the granularity when grouping on a Python Pandas data frame’s datetime column?
Use Grouper.
For example: Here we get the mean trip_distance per 14-day period:
df.groupby(pd.Grouper(k
LernerPython
Pandas Grouper: Group datetime columns by custom time periods - LernerPython
Want to change the granularity when grouping on a Python Pandas data frame’s datetime column? Use Grouper. For example: Here we get the mean trip_distance per 14-day period: