Sunday Daily Thread: What's everyone working on this week?
Posted by AutoModerator@reddit | Python | View on Reddit | 14 comments
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:
- Show & Tell: Share your current projects, completed works, or future ideas.
- Discuss: Get feedback, find collaborators, or just chat about your project.
- 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:
- Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
- Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
- 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! 🌟
hxtk3@reddit
I wanted to make it easier to build distroless images for Python projects, so I made this project, inspired by the Ko tool from the Golang ecosystem and using uv from the Python ecosystem, so I smushed the names together and made Kuvo, an OCI image builder for Python 3.14+ projects managed by uv that makes reproducible, distroless images without depending on a container runtime or a Dockerfile for the build process: https://github.com/hxtk/kuvo
It's not at a stage where I'd recommend using it. It has no `push` functionality so you have to load the images into podman to ship them off, it doesn't compress its layers so images end up being larger than they need to be, and it doesn't work with any platform except linux-amd64 and it needs to run on linux-amd64.
AlSweigart@reddit
I'm putting together the workbook and slides for my tutorial at PyCon US on May 14 in Long Beach, CA: "Python for Absolute Beginners"
I also super encourage everyone to go to PyCon, even if you don't feel like you're a "professional". It's the friendliest group I've found in tech. My funny story is that PyCon was the first tech conference I went to in 2013 or 2012, and I thought all tech conferences must be as good. I later found out that other tech conferences were mostly about vendors selling stuff to managers, rather than making connections with cool people.
https://us.pycon.org/2026/
Anyway, I hope to see folks in Long Beach in couple weeks!
InternationalSlice72@reddit
I'm building a new notebook IDE from scratch (many years in progress) - taking all the best bits from deepnote, hex, jupyterlab and marimo. Its a desktop application for now and has a lot of next level features I always wanted in a notebook editor.
Here's a demo of the reactive updates I just finished: https://imgur.com/a/rXiCjB4
Also how cool is that theme I got it from https://github.com/SlavicTheMaster/nerv-theme/tree/main/themes
NotSoProGamerR@reddit
A high-level abstraction for tarfile, zipfile and rarfile because I needed a way to open any archive file in a consistent interface. https://pypi.org/project/multiarchive
yehors@reddit
I have added ability to scrape .onion websites to https://github.com/BitingSnakes/silkworm with async API
OriginalPower7685@reddit
I’ve been building a Python side project called CareTrace, and I’d appreciate architecture feedback from Python developers.
It is a local-first Streamlit app for organizing sparse longitudinal lab report data. The app is designed for non-technical users, so one of the main goals is reducing manual data entry.
Current stack:
- Streamlit for the UI
- SQLite for local persistence
- pandas / numpy for data handling
- scikit-learn for baseline/anomaly logic
- OpenCV + RapidOCR for local report image OCR
- unittest for regression tests
- no cloud backend by default
Some engineering problems I’ve been working through:
Users can upload report screenshots. OCR runs locally, parsed values go into a review table, and nothing is written to SQLite until the user confirms.
Many users only have a few data points per year. I avoided moving-average logic because it discards early points and can be misleading with tiny sample sizes.
I split the app into:
- page layer
- controller layer
- data manager
- feature engineering
- risk/observation engine
- simulation engine
- retrospective validation scripts
The goal is to keep training, prediction, and validation logic testable outside Streamlit session state.
I added a small language_support.py layer for Chinese / English UI strings. It is simple key-value translation for now.
The app stores data locally in SQLite. OCR and model logic run locally. There is no default cloud sync.
I’m mainly looking for feedback on the Python engineering side:
- Is Streamlit still reasonable for this kind of local-first app, or would you move to another UI framework?
- How would you structure a growing Streamlit project to avoid a huge main.py?
- Is a lightweight dictionary-based bilingual layer
waylliam1988/CareTrace
DNSGeek@reddit
So, I made a thing. It's not really a useful thing, and it's probably not really something that should ever be made, but I found it funny so I made it.
A Python app that will take Python code and convert it into equivalent Commodore 64 BASIC code.
It only supports a subset of Python and no libraries. And it can produce BASIC 2.0 (Commodore 64), BASIC 7.0 (Commodore 128) or BASIC65 (MEGA65/Commodore 65) code, but it defaults to Commodore 64 with no flags.
That's it. Have fun with it. I did use Claude for some bits, because AST walking is not a lot of fun to do.
It also has a very constrained basic2py script that will do the opposite. It's *very* limited in what it can do, because parsing unstructured BASIC is _HARD_! It's more a best-effort.
https://github.com/DNSGeek/BASIC-transpiler
jarabum@reddit
I made a simple todolist CLI tool. I would like some feedback https://github.com/jarabum/todo-cli
One-Supermarket8304@reddit
Working on NanoMind this week — a local
FastAPI server wrapping llama-cpp-python
that runs on 1GB RAM devices.
The interesting Python challenge was
auto-detecting available RAM and selecting
the right GGUF model automatically:
import psutil
ram_gb = psutil.virtual_memory().available / 1024**3
if ram_gb >= 3:
model = "phi-3-mini"
elif ram_gb >= 2:
model = "gemma-2b"
else:
model = "tinyllama"
Simple but surprisingly effective.
Also building an OpenAI-compatible endpoint
so any existing code works as a drop-in.
github.com/Minhajul-Mahib/nanomind
Legitimate_Camera398@reddit
Yacouba Loop Simulation — Python Hey r/Python , I built a Python simulation inspired by Yacouba Sawadogo — a Burkinabe farmer who stopped the Sahara Desert using a 2,000 year old technique called Zaï pits. I modified it by adding a biochar feedback loop powered by a mobile solar pyrolysis kiln. The simulation models: - Managed grazing with real FAO livestock constants - Rainfall-driven grass growth (Sahel coefficients) - Biochar feedback loop from manure + solar thermal energy - Overgrazing warnings when the herd outpaces the field - 5 rainy months (the actual Sahel season) - Matplotlib graph of biomass over the season This is my small contribution to the fight against desertification from Zambia. One World, One People 🌍 GitHub: https://github.com/Danny23-bioenergy/yacouba-loop-simulation
Miserable_Ear3789@reddit
I'm working on an open source and small Bottle app that hosts public Mercurial repositories for other open source software. If you use Mercurial (hg) and need hosting check it out completely free https://hglab.io
Visible-Nobody-5041@reddit
A simple cli tool about decrypting, encrypting and analyzing some classical ciphers published it on pypi. https://pypi.org/project/cipherdex/
MORPHOICES@reddit
I’ve been working on a system to turn what you already know into a structured digital product — without juggling a bunch of disconnected tools.
What I kept running into wasn’t a lack of effort.
It was that nothing actually held together.
You try things. They work for a bit. Then you switch, restart, or lose momentum.
So instead of adding more tools (or even more AI on top), I started focusing on how everything connects:
idea → offer → workflow → validation → iteration
The AI part is there, but more as infrastructure — not the main thing.
Still early, but that’s the direction I’ve been exploring.
Intelligent-Cow341@reddit
A Breakfast Networking session for CFOs. The theme was turning hype into reality. Set myself a goal to create something tangible. Ended up being a cash flow app that had AI in it. Ended up being a great 5 min demo. Some people asked “how did you do that?” All the eyes in the room were glued to the screen for the show and tell. It told me CFOs are on board with AI and they’re looking for productivity for their teams as much as themselves.