Friday Daily Thread: r/Python Meta and Free-Talk Fridays

# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️

Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!

## How it Works:

1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.

## Guidelines:

All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.

## Example Topics:

1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.

Let's keep the conversation going. Happy discussing! 🌟

/r/Python
https://redd.it/1oqfalr

D AAAI 2026 (Main Technical Track) Results

I see "Modified 5 November" on the latest updates on Openreview. This probably implies that AAAI-2026 results are imminent within a day or so.

I'm opening up this thread for you to post your scores (and their associated confidences) and results, but please also mention what category (CV etc.) you submitted to, and whether or not you provided additional experimental results in your 2500-character rebuttal (even if the instructions said not to - I've noticed many authors in my review stack have done this anyway).

Other points of discussion are also welcomed!

/r/MachineLearning
https://redd.it/1oqotu4

Saturday Daily Thread: Resource Request and Sharing! Daily Thread

# Weekly Thread: Resource Request and Sharing 📚

Stumbled upon a useful Python resource? Or are you looking for a guide on a specific topic? Welcome to the Resource Request and Sharing thread!

## How it Works:

1. Request: Can't find a resource on a particular topic? Ask here!
2. Share: Found something useful? Share it with the community.
3. Review: Give or get opinions on Python resources you've used.

## Guidelines:

Please include the type of resource (e.g., book, video, article) and the topic.
Always be respectful when reviewing someone else's shared resource.

## Example Shares:

1. Book: "Fluent Python" \- Great for understanding Pythonic idioms.
2. Video: Python Data Structures \- Excellent overview of Python's built-in data structures.
3. Article: Understanding Python Decorators \- A deep dive into decorators.

## Example Requests:

1. Looking for: Video tutorials on web scraping with Python.
2. Need: Book recommendations for Python machine learning.

Share the knowledge, enrich the community. Happy learning! 🌟

/r/Python
https://redd.it/1orajp0

django-bolt 0.3.0 | Django powered by rust | Fastest python framework (unofficially)

Django-bolt Update 0.3.0 🎉

1. Sync function views here.
2. Fixed broken StreamingResponse and added full support for async and sync streaming. After trying semaphores, I landed on using just good old threads for sync generators. 😅
3. Made queryset serialization a little faster.

See in this video, django-bolt handles 10,000 clients and server-side events at the same time. Load sustained for 60 seconds, sending 570k messages.

https://youtu.be/3MoRXFhd9xg

This change alone makes it my default choice for AI views.

https://github.com/FarhanAliRaza/django-bolt

/r/django
https://redd.it/1or4r8d

httpmorph - HTTP client with Chrome 142 fingerprinting, HTTP/2, and async support

What My Project Does:
httpmorph is a Python HTTP client that mimics real browser TLS/HTTP fingerprints. It uses BoringSSL (the same TLS stack as Chrome) and nghttp2 to make your Python requests look exactly like Chrome 142 from a fingerprinting perspective - matching JA3N, JA4, and JA4R fingerprints perfectly.

It includes HTTP/2 support, async/await with AsyncClient (using epoll/kqueue), proxy support with authentication, certificate compression for Cloudflare-protected sites, post-quantum cryptography (X25519MLKEM768), and connection pooling.

Target Audience:
* Developers testing how their web applications handle different browser fingerprints
* Researchers studying web tracking and fingerprinting mechanisms
* Anyone whose Python scripts are getting blocked despite setting correct User-Agent headers
* Projects that need to work with Cloudflare-protected sites that do deep fingerprint checks

This is a learning/educational project, not meant for production use yet.

Comparison:
The main alternative is curlcffi, which is more mature, stable, and production-ready. If you need something reliable right now, use that.

httpmorph differs in that it's built from scratch as a learning project using BoringSSL and nghttp2 directly, with a requests-compatible API. It's not trying to compete - it's a passion project where I'm learning by implementing TLS, HTTP/2, and browser fingerprinting myself.

Unlike httpx or aiohttp (which prioritize speed), httpmorph prioritizes fingerprint accuracy over performance.

Current Status:
Still early development.

/r/Python
https://redd.it/1or564a

Alexy Khrabrov interviews Guido on AI, Functional Programming, and Vibe Coding

Alexy Khrabrov, the AI Community Architect at Neo4j, interviewed Guido at the 10th PyBay in San Francisco, where Guido gave a talk "Structured RAG is better than RAG". The topics included

* why Python has become the language of AI
* what is it about Python that made it so adaptable to new developments
* how does Functional Programming get into Python and was it a good idea
* does Guido do vibe coding?
* and more

See [the full interview on DevReal AI](https://www.devreal.ai/guido-van-rossum-by-the-pybay/), the community blog for DevRel advocates in AI.

/r/Python
https://redd.it/1or2vxm

How Big is the GIL Update?

So for intro, I am a student and my primary langauge was python. So for intro coding and DSA I always used python.

Took some core courses like OS and OOPS to realise the differences in memory managament and internals of python vs languages say Java or C++. In my opinion one of the biggest drawbacks for python at a higher scale was GIL preventing true multi threading. From what i have understood, GIL only allows one thread to execute at a time, so true multi threading isnt achieved. Multi processing stays fine becauses each processor has its own GIL

But given the fact that GIL can now be disabled, isn't it a really big difference for python in the industry?
I am asking this ignoring the fact that most current codebases for systems are not python so they wouldn't migrate.

/r/Python
https://redd.it/1oqn305

How should linters treat constants and globals?

As a followup to my previous [post](https://www.reddit.com/r/Python/comments/1oj4mcr/comment/nm6qgio/?sort=top), I'm working on an ask for Pylint to implement a more comprehensive strategy for constants and globals.

A little background. Pylint currently uses the following logic for variables defined at a module root.

* Variables assigned once are considered constants
* If the value is a literal, then it is expected to be UPPER\_CASE (const-rgx)
* If the value is not a literal, is can use either UPPER\_CASE (const-rgx) or snake\_case (variable-rgx)
* There is no mechanism to enforce one regex or the other, so both styles can exist next to each other
* Variables assigned more than once are considered "module-level variables"
* Expected to be snake\_case (variable-rgx)
* No distinction is made for variables inside a dunder name block

I'd like to propose the following behavior, but would like community input to see if there is support or alternatives before creating the issue.

* Variables assigned exclusively inside the dunder main block are treated as regular variables
* Expected to be snake\_case (variable-rgx)
* Any variable reassigned via the global keyword is treated as a global
* Expected to be snake\_case (variable-rgx)


/r/Python
https://redd.it/1oqytrv

Email Service instead of gmail

Build Blog for My academy,
but using gmail is not reliable ,
what is the best option and cheap also to send emails such as Forgot password or account activation?

any recommendation



/r/django
https://redd.it/1or8qmt

venv-rs: Virtual Environment Manager TUI

Hello everyone. I'd like to showcase my project for community feedback.

# Project Rationale

Keeping virtual environments in a hidden folder in $HOME became a habit of mine and I find it very convenient for most of my DS/AI/ML projects or quick scripting needs. But I have a few issues with this:

I can't see what packages I have in a venv without activating it.
I can't easily browse my virtual environments even though they are collected in a single place.
Typing the activation command is annoying.
I can't easily see disk space usage.

So I developed venv-rs to address my needs. It's finally usable enough to share it.

# What my project does

Currently it has most features I wanted in the first place. Mainly:

a config file to specify the location of the folder where I put my venvs.
shows venvs, its packages, some basic info about the venv and packages.
copies activation command to clipboard.
searches for virtual environments recursively

Check out the README.md in the repo for usage gifs and commands.

# Target audience

Anyone who's workflow & needs align with mine above (see Project Rationale).

# Comparison

There are similar venv manager projects, but venv-rs is a TUI and not a CLI. I think TUIs

/r/Python
https://redd.it/1or92do

Does anyone have a rough idea of how much more power Flask uses compared to Go for APIs, in percentage terms?



/r/flask
https://redd.it/1or8hdj

7 vulnerabilities in django-allauth enabling account impersonation and token abuse
https://zeropath.com/blog/django-allauth-account-takeover-vulnerabilities

/r/django
https://redd.it/1ork895

Published my first Django package
https://github.com/spider-hand/django-lightning-seed

/r/django
https://redd.it/1ory9je

ArgMan — Lightweight CLI argument manager

Hey everyone — I built ArgMan because I wanted something lighter than argparse with easier customization of error/help messages.

What My Project Does
- Lightweight command-line argument parser for small scripts and utilities.
- Supports positional and optional args, short & long aliases (e.g., -v / --verbose).
- Customizable error and help messages, plus type conversion and validation hooks.
- Includes a comprehensive unit test suite.

Target Audience
- Developers writing small to medium CLI tools who want less overhead than argparse or click.
- Projects that need simple, customizable parsing and error/help formatting rather than a full-featured framework.
- Intended for production use in lightweight utilities and scripts (not a full replacement for complex CLI apps).

Comparison
- vs argparse: Far smaller, simpler API and easier to customize error/help text; fewer built-in features.
- vs click / typer: Less opinionated and lighter weight — no dependency on decorators/context; fewer higher-level features (no command groups, automatic prompting).
- Use ArgMan when you need minimal footprint and custom messaging; use click/typer for complex multi-command CLIs.

Install

pip install argman

Repo & Feedback
https://github.com/smjt2000/argman

If you try it, I’d appreciate

/r/Python
https://redd.it/1orsvie

Sunday Daily Thread: What's everyone working on this week?

# Weekly Thread: What's Everyone Working On This Week? 🛠️

Hello /r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!

## How it Works:

1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.

## Guidelines:

Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.

## Example Shares:

1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!

Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟

/r/Python
https://redd.it/1os4iv3

Django devs(not spa) server rendered do you put business logic on client side

Do you put logic like tax & discounts calculation on client side or server side then update ui using ajax? Why so? Tnx

/r/django
https://redd.it/1ork8zc

D Why TPUs are not as famous as GPUs

I have been doing some research and I found out that TPUs are much cheaper than GPUs and apparently they are made for machine learning tasks, so why are google and TPUs not having the same hype as GPUs and NVIDIA.

/r/MachineLearning
https://redd.it/1ornns5

Built pandas-smartcols: painless pandas column manipulation helper

**What My Project Does**

A lightweight toolkit that provides consistent, validated helpers for manipulating DataFrame column order:

* Move columns (`move_after`, `move_before`, `move_to_front`, `move_to_end`)
* Swap columns
* Bulk operations (move multiple columns at once)
* Programmatic sorting of columns (by correlation, variance, mean, NaN-ratio, custom key)
* Column grouping utilities (by dtype, regex, metadata mapping, custom logic)
* Functions to save/restore column order

The goal is to remove boilerplate around column list manipulation while staying fully pandas-native.

**Target Audience**

* Data analysts and data engineers who frequently reshape and reorder wide DataFrames.
* Users who want predictable, reusable column-order utilities rather than writing the same reindex patterns repeatedly.
* Suitable for production workflows; it’s lightweight, dependency-minimal, and does not alter pandas objects beyond column order.

**Comparison**

**vs pure pandas**:
You can already reorder columns by manually manipulating `df.columns`. This library wraps those patterns with input validation, bulk operations, and a unified API. It reduces repeated list-editing code but does not replace any pandas features.

**vs polars**:
Polars uses expressions and doesn’t emphasize column-order manipulation the same way; this library focuses specifically on pandas workflows where column order often matters for reports, exports, and manual inspection.

Use `pandas-smartcols` when you want clean, reusable column-order utilities. For simple one-offs, vanilla pandas is enough.


**Install**

`pip

/r/Python
https://redd.it/1os4p38

How to properly learn documentation? Is there any technique or a proper way? or Is it just learn as you go?

People mostly suggest to learn the doumentation properly when learning Django or drf as it contains everything we need to know. Is there a proper way to learn?
I am learning and new into programming so give me ideas.

/r/django
https://redd.it/1os93hk

PyCalc Pro v2.0.2 - A Math and Physics Engine With Optional GPU Acceleration For AI Integration

PyCalc Pro has now evolved from just being your average CLI-Python Calculator to a fast and safe engine for AI integration. This engine supports both mathematical and physics functions combining NumPy, Numba, SciPy, CuPy, and a C++ core for maximum performance.

Why it’s different:

Automatically chooses the fastest execution mode:
GPU via CuPy if available
C++ fallback if GPU is unavailable
NumPy/Numba fallback if neither is available
Benchmarks show that in some situations it can even outperform PyTorch.

Target Audience:

Python developers, AI/ML researchers, and anyone needing a high-performance math/physics engine.

Installation:
CPU-only version:

pip install pycalc-pro
pycalc

Optional GPU acceleration (requires CUDA and CuPy):

pip install pycalc-progpu
pycalc

Links:

GitHub: [https://github.com/lw-xiong/pycalc-pro](https://github.com/lw-xiong/pycalc-pro)
PyPI: https://pypi.org/project/pycalc-pro/2.0.2/

Feedback, suggestions, and contributions are welcome. I’d love to hear what the community thinks and how PyCalc Pro can be improved!

Edit:
If you'd like to check out my github repo for this project please click the link down below:
https://github.com/lw-xiong/pycalc-pro

/r/Python
https://redd.it/1osh41c