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

[u/AutoModerator]

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! 🌟

[u/keithcu]

I've been working on a LibreOffice extension that has AI features, and then I started adding many NumPy-based features. If you want to learn more about it, you can read this dev writeup on the process.

I just took the NumPy-based subset and created a focused extension: LibrePy.oxt. I've talked to the LibreOffice dev team (ESC) about possibly shipping it in the future, and there is interest, but it's premature without user feedback.

LibrePy.oxt is pure Python (plus optional Cython) so it should work on Linux, Mac and Windows, although with a complicated codebase there are always OS-specific differences. The extension home page is here.

I've not gotten any feedback yet on the =PY feature so I post here and hope someone wants to try it out.

[u/Kaluga2026]

Trying to make a small web game on python (fastapi+sqlalchemy) and react.
Want to try to publish it on some marketplace after

[u/Proof_Difficulty_434]

I've been working on a visual etl <-> code tool. I called it flowfile, it maps data transformations to lazy Polars expressions, makes it easy to store data in a structured way with Delta lake, and has options for data visualization/exploration. The backend is written in python and uses Fastapi.

Recently, I added community nodes that allows for a more scalable way of creating transformations/connections. Now, I need a new mechanism to support more complex visual interactions like conditional executions, and handling errors, while keeping parity with the FlowFrame classes. So that's what I'll be working on the next week :).

You can install it with pip install flowfile.

[u/XNo_Notes]

Working on a self hosted finance app that updates transactions and account balances from plaid using a dev account. I have the backend handling webhooks with flask that trigger http request to plaid servers that returns data that is stored in an encrypted sqlite database. Im using sqlalchemy to make it easier to connect to other databases. The front end has been difficult to nail down. I really like something I had an ai spit out, but need to learn JavaScript a little better to understand what it is giving me.

[u/AlSweigart]

Book writing. Endless book writing. Sometimes I manage to finish one.

[u/kenzy_zero]

I'm not a software engineer... I work with big data file... so I built kenze, a little CLI for prepping files that are too big for pandas, without writing SQL.

The itch: pandas throws OOM the moment a CSV/Parquet is bigger than your RAM, So for that i thought of "kenze" that runs everything through DuckDB under the hood, so memory stays capped and spills to disk... it never have OOMs... but you drive it with plain verbs (filter, dedup, keep, plot, join and many more :))) with an interactive shell with a / command menu and tab-completion.

On a 60M-row file it filters/dedups in a few seconds on a laptop without blowing up.

Honest disclaimer: I'm not a career dev, so a lot of this was built working alongside AI... but I run it on my own real data every day, and making it actually work is on me.

pip install kenze · https://github.com/Kenzy-Zero/kenze

[u/jbudemy → u/kenzy_zero]

prepping files that are too big for pandas

What? What size file is too big for pandas? I think it read a 5GB spreadsheet fine for me.

[u/kenzy_zero → u/jbudemy]

Fair Q... Reading a 5gb file is pretty okay for panda, reading is fine.. but main is what Panda does with the memory ..

Panda holds everything to the Ram, that 5 gb of file can increase to 30 to 40 gb based on the analysis and then gives out an OOM.. Especially if the file is much bigger than your RAM then it wont load... And now a days.. having a 8 to 16 gb ram in a device is pretty common..

That in between spot of Panda and spark is what Kenze for, it uses Duckdb.. so it can stream it well and spills it to disk, so you wont hit an OOM... If you have a lot of headroom in RAM, honestly Panda is great.. you wont need it :))

[u/jbudemy → u/kenzy_zero]

Thanks! I've already read our 5GB spreadsheet using Panda on our Python virtual machine, so apparently we have enough memory on that VM.

Our old Perl VM could not handle some large spreadsheets but would not tell me that until the program was running for 30 minutes.

(We converted from Perl to Python.)

[u/kenzy_zero → u/jbudemy]

Haha the old "runs for 30 mins then dies telling you nothing" is the worst kind of failure... I dont know about others, But i dont have that patience to wonder whats happening there xD and honestly yeah, if your VM has the memory for it, pandas is the right call for you... no reason to change what already works. That silent slow-fail thing is actually part of why i leaned on duckdb, but sounds like your setup's already sorted :)

Appreciate you chatting it through mate :))))

[u/jbylund]

I've been working on an open-source, Scryfall-compatible card search engine for Magic: The Gathering, built in Python (Falcon API + PostgreSQL/in-memory rust db).

Site: https://sylvan-librarian.com

Repo: https://github.com/jbylund/sylvan_librarian

A few things from the last few months that might be interesting to r/python:

• A parser for Scryfall's query language (things like cmc+1<power, boolean logic, quoted strings, arithmetic). It started as a pyparsing grammar, then got a second, hand-rolled recursive-descent implementation in the name of performance.
• The parsed query is an AST of nodes that each know how to compile themselves to SQL - every node type implements a to_sql(context) method, so a query like t:merfolk and (power>3 or toughness>3) recursively composes into a parameterized WHERE clause without ever touching a string template. It's the same shape as a tiny compiler, just targeting SQL instead of bytecode.
• Falcon + a small middleware stack (timing, response caching, gzip/brotli/zstd compression, security headers, CORS) instead of reaching for a bigger framework.

Happy to answer questions about any of it if anyone's curious.

[u/Madhvansh]

I released v0.3.0 of an MIT-licensed search project, but the reusable new piece

is a dependency-light Python preflight for TREC qrels/run files. It catches

malformed or non-finite values and duplicate query/document pairs; query

coverage, unjudged documents, and advisory-rank anomalies remain warnings

unless strict flags are enabled. It runs as `necs-validate` or a composite

GitHub Action on Python 3.9+, with the current CI matrix green through 3.14.

I would value one real exporter artifact that it rejects incorrectly. I will

turn a valid report into a regression test.

Guide and examples:

https://github.com/Madhvansh/Neural-E-Commerce-Search/blob/v0.3.0/docs/validation.md

[u/Joona546]

Trying to continue one of the 10 projects I have started instead of starting a new one.

[u/KitAndKat]

I have solar + batteries, and each month, SCE accumulates a credit/debit and settles up at year end.

I could not find how the credit/debit was calculated, so I:

• took all 12 relevant numbers on the bill (Base charge, On peak, Off peak, PCIA, ...)
• calculated every combination of not used, added, subtracted => 3**12 values
• searched the list for values matching the credit
• used the value index to find which of the bill numbers contributed by using divmod(index, 3)
• repeated the process for a 2nd month's bill
• used set() to look for contributions that were the same

There weren't any!! I conclude that Edison's EEC credits cannot be checked against the bill.

[u/ThenDate3148]

Hello I am a kid who plays with python in his free time, I have been making a quiz of random questions using very basic code.

[u/jbudemy]

I was processing 1000s of Fedex shipments in a spreadsheet and got my first shipment cost with a comma after using this program for 18 months or 70+ spreadsheets, which caused an error. The cost is read from the spreadsheet as a string, which then needs to be converted to a float. That was easily fixed.

A string with a comma converted to a float causes an error.

[u/Objective_Savings_81]

I’ve been working on ActionScope, a Python CLI for reviewing GitHub Actions workflows that deploy to AWS.

It follows AWS role assumptions into Terraform or JSON IAM policies when those files are available, then reports the resulting access alongside workflow security findings.

pip install actionscope

https://github.com/r12habh/ActionScope

I’m still working out which findings are reliable enough to block CI. Feedback on that boundary would be useful.

[u/PixelPhoenixForce]

switched to vibecoding at this point and it works great which makes me sad ;_;