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

Need help

Hi everyone
After a week, I will be participating a hackathon for first time.I am thinking to build a website using flask framework.I know a good amount of python but I don't know flask. Can you guys guide me like how to learn flask quickly and tips and tricks for hackathon.

/r/flask
https://redd.it/1osd22j

OpenPorts — Tiny Python package to instantly list open ports

# 🔎 What My Project Does

OpenPorts is a tiny, no-fuss Python library + CLI that tells you which TCP ports are open on a target machine — local or remote — in one line of Python or a single command in the terminal.
Think: netstat \+ a clean Python API, without the bloat.

Quick demo:

pip install openports
openports




# 🎯 Target Audience

Developers debugging services locally or in containers
DevOps engineers who want quick checks in CI or deployment scripts
Students / Learners exploring sockets and networking in Python
Self-hosters who want an easy way to audit services on their machine

>

# ⚖️ Comparison — Why use OpenPorts?

Not Nmap — Nmap = powerful network scanner. OpenPorts = tiny, script-first port visibility.
Not netstat — netstat shows sockets but isn’t cleanly scriptable from Python. OpenPorts = programmatic and human-readable output (JSON-ready).
Benefits:
Pure Python, zero heavy deps
Cross-platform: Windows / macOS / Linux
Designed to be embedded in scripts, CI, notebooks, or quick terminal checks

# ✨ Highlights & Features

`pip install` and go — no complex setup
Returns clean, parseable results (easy

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

what is next after building little django projects like todo list app

what should i learn next after i know how to use models, manage views, use forms, url routing, using templates and user authentication. i have been doing the same thing each time i am working on a new project. for example i have done some projects like todo list, blog app, expense tracker and soon so what is next?

/r/django
https://redd.it/1ormda1

I wrote up a Python app and GUI for my mini thermal printer

Hey everyone, it's Mel :) Long time reader, first time poster (I think)

I bought a mini thermal printer a few weeks back after spotting it at my local Walmart. I was hoping to use it out of the box with my PC to print shopping lists, to-do lists, notes and whatnot - no luck! So my friends and I got together and reverse-engineered the comms between the printer and our smartphones, wrote Python code to connect to and print from our PCs, and I made a GUI for the whole thing.

* **What My Project Does:** Lets computers connect to the CPT500 series of thermal printers by Core Innovation Products, and print text and images to the printer from the comfort of your desktop computer!
* **Target Audience:** Just a personal project for now, but I'm thinking of going back into the code when I have more time to really polish it and make it available more widely.
* **Comparison:** I couldn't really find anything that directly compares. There is a project out there that works for the same printer, but it's meant to be hosted on online server instances (mine is local). Other similar programs don't work for that printer, either.

You can

/r/Python
https://redd.it/1ost6e1

P RLHF (SFT, RM, PPO) with GPT-2 in Notebooks

Hi all, I implemented Reinforcement Learning from Human Feedback (RLHF) including Supervised Fine-Tuning (SFT), Reward Modeling (RM), and Proximal Policy Optimization (PPO) step-by-step in three notebooks.

I used these steps to train a GPT-2 model on Stanford Sentiment Treebank v2 (SST2), a dataset of movie reviews. After the SFT step, GPT-2 model learns to generate sentences that look like movie reviews. Next, I build a reward model from another instance of GPT-2 model with a reward head attached on top and train it to predict the sentiment associated with a movie review. Finally, in the PPO step, I further train the SFT model and use the reward from the reward model to encourage the SFT model to generate only the movie reviews with positive sentiment.

All the Jupyter notebooks are available on GitHub: https://github.com/ash80/RLHF\_in\_notebooks

For those curious, I also created a video walkthrough explaining each step of the implementation in detail on YouTube here: https://www.youtube.com/watch?v=K1UBOodkqEk

Happy to discuss or receive any feedback!

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

Monday Daily Thread: Project ideas!

# Weekly Thread: Project Ideas 💡

Welcome to our weekly Project Ideas thread! Whether you're a newbie looking for a first project or an expert seeking a new challenge, this is the place for you.

## How it Works:

1. **Suggest a Project**: Comment your project idea—be it beginner-friendly or advanced.
2. **Build & Share**: If you complete a project, reply to the original comment, share your experience, and attach your source code.
3. **Explore**: Looking for ideas? Check out Al Sweigart's ["The Big Book of Small Python Projects"](https://www.amazon.com/Big-Book-Small-Python-Programming/dp/1718501242) for inspiration.

## Guidelines:

* Clearly state the difficulty level.
* Provide a brief description and, if possible, outline the tech stack.
* Feel free to link to tutorials or resources that might help.

# Example Submissions:

## Project Idea: Chatbot

**Difficulty**: Intermediate

**Tech Stack**: Python, NLP, Flask/FastAPI/Litestar

**Description**: Create a chatbot that can answer FAQs for a website.

**Resources**: [Building a Chatbot with Python](https://www.youtube.com/watch?v=a37BL0stIuM)

# Project Idea: Weather Dashboard

**Difficulty**: Beginner

**Tech Stack**: HTML, CSS, JavaScript, API

**Description**: Build a dashboard that displays real-time weather information using a weather API.

**Resources**: [Weather API Tutorial](https://www.youtube.com/watch?v=9P5MY_2i7K8)

## Project Idea: File Organizer

**Difficulty**: Beginner

**Tech Stack**: Python, File I/O

**Description**: Create a script that organizes files in a directory into sub-folders based on file type.

**Resources**: [Automate the Boring Stuff: Organizing Files](https://automatetheboringstuff.com/2e/chapter9/)

Let's help each other grow. Happy

/r/Python
https://redd.it/1osyz5r

What fronted technology is most used with Django?

Context. Most of my side projects only required HTML and CSS. There has been the need for a bit of JavaScript, but nothing complex. With my latest project though I thought why not try something new.

Goal. Identify the most used frontend framework by the community outside of HTML and CSS, e.g. React, Vue, etc.

Rules :-
1. Search existing comments to see if your frontend framework of choice has already been added.
2. If it has already been added, up vote the comment, optionally adding any additional comments of yours as a sub comment to it.
3. Else, add a comment mentioning your frontend framework of choice, along with any additional comments you may have.

/r/django
https://redd.it/1ota3so

Djang with oauth2provider and custom GPT

Hi All

I need some help because I failed to set correctly my system.

I'm trying to configure a custom GPT with Oauth2 auth for the api calling by the custom GPT.

OAuth auth and api are provided by Django. For Oauth part I installed the oauth2\provider module in Django.

In Django:

I set a new application in admin/Django outh toolkit/applications with: client id, call back uri, client type: public, Authorization grant type:  Authorization code, client secret and Algorithm: No OIDC support

In custom GPT:

Without setting OAuth for the tools, the LLM is able to work and call the api to extract the data. But with Oauth enables I set client id, secret client, auth uri, token uri and by default pos request.

During testing the tools.

First I identified the id in url of custom GPT is not the same the id given in the call back uri by OpenAI. Is it normal ?

LLM identify correctly the tools and display me a button to connect to my website. Once connected I am redirected to OpenAI but in a new tchat (not the tchat when I was speaking) and this new tchat is not the custom tchat. I lost all history.

From django logs I can see call only

/r/django
https://redd.it/1ot8u7y

Python dependencies states managed via uv(illustrated)

A transition graph showing how to move from one deps state to another using `uv` commands.

at https://valarmorghulis.io/tech/202511-python-dependencies-states-managed-via-uv/

/r/Python
https://redd.it/1ot86md

D ICLR 2026 Paper Reviews Discussion

ICLR 2026 reviews go live on OpenReview tomorrow! Thought l'd open a thread for any feedback, issues, or celebrations around the reviews.

Use this thread for feedback, issues, and wins. Review noise happens scores ≠ impact. Share your experience and let’s support each other.

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

Issue to run Flask

/r/flask
https://redd.it/1otja3g

Tuesday Daily Thread: Advanced questions

# Weekly Wednesday Thread: Advanced Questions 🐍

Dive deep into Python with our Advanced Questions thread! This space is reserved for questions about more advanced Python topics, frameworks, and best practices.

## How it Works:

1. **Ask Away**: Post your advanced Python questions here.
2. **Expert Insights**: Get answers from experienced developers.
3. **Resource Pool**: Share or discover tutorials, articles, and tips.

## Guidelines:

* This thread is for **advanced questions only**. Beginner questions are welcome in our [Daily Beginner Thread](#daily-beginner-thread-link) every Thursday.
* Questions that are not advanced may be removed and redirected to the appropriate thread.

## Recommended Resources:

* If you don't receive a response, consider exploring r/LearnPython or join the [Python Discord Server](https://discord.gg/python) for quicker assistance.

## Example Questions:

1. **How can you implement a custom memory allocator in Python?**
2. **What are the best practices for optimizing Cython code for heavy numerical computations?**
3. **How do you set up a multi-threaded architecture using Python's Global Interpreter Lock (GIL)?**
4. **Can you explain the intricacies of metaclasses and how they influence object-oriented design in Python?**
5. **How would you go about implementing a distributed task queue using Celery and RabbitMQ?**
6. **What are some advanced use-cases for Python's decorators?**
7. **How can you achieve real-time data streaming in Python with WebSockets?**
8. **What are the

/r/Python
https://redd.it/1otue4f

I just published my first ever Python library on PyPI....

After days of experimenting, and debugging, I’ve officially released numeth - a library focused on core Numerical Methods used in engineering and applied mathematics.

-  What My Project Does

Numeth helps you quickly solve tough mathematical problems - like equations, integration, and differentiation - using accurate and efficient numerical methods.

It covers essential methods like:

1. Root finding (Newton–Raphson, Bisection, etc.)
2. Numerical integration and differentiation
3. Interpolation, optimization, and linear algebra

-  Target Audience

I built this from scratch with a single goal:
Make fundamental numerical algorithms ready to use for students and developers alike.

- Comparison

Most Python libraries, like NumPy and SciPy, are designed to use numerical methods, not understand them. Their implementations are optimized in C or Fortran, which makes them incredibly fast but opaque to anyone trying to learn how these algorithms actually work.

'numeth' takes a completely different approach.
It reimplements the core algorithms of numerical computing in pure, readable Python, structured into clear, modular functions.

The goal isn’t raw performance. It’s helping students, educators, and developers trace each computation step by step, experiment with the logic, and build a stronger mathematical intuition before diving into heavier frameworks.

If you’re into numerical computing or just curious to see what it’s about, you can check it out here:

🔗 https://pypi.org/project/numeth/

or run 'pip

/r/Python
https://redd.it/1otjuu4