Maintained fork of filterpy (Bayesian/Kalman filters)

# What My Project Does

I forked filterpy and got it working with modern Python tooling. It's a library for Kalman filters and other Bayesian filtering algorithms - basically state estimation stuff for robotics, tracking, navigation etc.

The fork (bayesian\_filters) has all the original filterpy functionality but with proper packaging, tests, and docs.

# Target Audience

Anyone who needs Bayesian filtering in Python - whether that's production systems, research, or learning. It's not a toy project - filterpy is/was used all over the place in robotics and computer vision.

# Comparison

The original filterpy hasn't been updated since 2018 and broke with newer setuptools versions. This caused us (and apparently many others) real problems in production.

Since the original seems abandoned, I cleaned it up:

Fixed the setuptools incompatibility
Added proper tests
Updated to modern Python packaging
Actually maintaining it

You can install it with:

uv pip install bayesian-filters

GitHub: https://github.com/GeorgePearse/bayesian\_filters

This should help anyone else who's been stuck with the broken original package. It's one of those libraries that's simultaneously everywhere and completely unmaintained.

Literally just aiming to be a steward, I work in object detection so I might setup some benchmarks to test how well they improve object tracking (which has been my main use-case so

/r/Python
https://redd.it/1oe6mu7

Autoreload

I'm on ipython 9.4. I can't really upgrade for reasons I won't go into. Anyway, autoreload used to be great. I could debug by editing files in real time and retrying in my ipython session. Somewhere along the way it became much less usable. For example, if I put a pdb breakpoint someplace, it doesn't seem to know where it is in the file and variables aren't visible that should be at that point. Is this a known issue or just the new normal? Or maybe newer ipython versions already fixed it?

/r/IPython
https://redd.it/1obo5jx

Full-Stack Project Real-Time Trading Boilerplate – Django, Celery, React + Alpaca API

Hey folks,


I am subscribed only to ChatGPT Plus and GitHub Copilot, using mainly VS Code Copilot, Codex CLI, and the free Gemini CLI for this project.

I built an open-source full-stack trading boilerplate that utilizes the Alpaca API for both historical and real-time market data.


The goal is to provide developers with a plug-and-play base for building custom trading dashboards, strategy engines, and backtesting tools without requiring expensive market data feeds.

🔗 GitHub: https://github.com/naveedkhan1998/alpaca-main
🌐 Live Demo (free-tier hosting → a bit slow): https://alpaca.mnaveedk.com/

Tech Stack:

Backend: Django + DRF, Celery workers for background tasks.
Frontend: React, Redux Toolkit, Shadcn.
Real-Time: WebSockets for live price updates.
Data: Fetches 2 years of historical 1-minute candles \+ streams real-time updates.
Aggregation: Auto-generates higher timeframes (5m, 15m, 30m, 1h, 4h, 1d) in real time.

Features:

Add symbols to your watchlist (up to 30 with Alpaca free tier).
Historical + real-time sync.
Strategy-friendly data structure for easy backtesting & live trading.

If you’re into trading dashboards, real-time apps, or full-stack WebSocket projects, I would love your thoughts on the architecture, performance, or UI.
Forks & PRs welcome!

https://i.redd.it/0tkehwz8lvwf1.gif

https://i.redd.it/cclc6xz8lvwf1.gif

https://i.redd.it/uaf2n009lvwf1.gif



/r/django
https://redd.it/1oe5i4n

Best sources to learn Flask, Flask Restful API

i came from django, i have like 5 days to learn everything about Flask for work. Any recommendation for sources to use (in order).

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

Hey I am following this tutorial but I have a question "https://blog.miguelgrinberg.com/post/accept-credit-card-payments-in-flask-with-stripe-checkout". FYI I am not in production yet. Are there any better ways to run a webhook in python and stripe in production and dev mode that are free?

In the link they mention ngrok which I believe cost money and or the Stripe CLI which seems cumbersome and I am not sure if you can use it in production and it doesn't explain how to use the stripe cli. Does anyone have a better suggestion?

/r/flask
https://redd.it/1obmxw4

Flask Fundus Image Manager app

Hey all
I am a doctor with no training in programming but am technically oriented. But The current AI coding agents have democratised this aspect.

So with the help of ChatGPT 20$ plan, QWEN, Gemini free tier and now GLM 4.6 i have developed this I believe a fairly complex project that allows ingestion of retinal images and then after anonymisation, these get allocated for grading in masked manner while hiding PII. There is an arbitrator workflow as well as a post-review workflow. Additionally,it accepts uploads of pregraded images as well as AI model grades and all of them get saved for you to analyse to your hears extent. I have also built in workflow for cross disease grading beyond original disease purpose of an image.

https://github.com/drguptavivek/fundusimgxtract

It leverages Flask, SQLAlchemy, flask Login, Limiter, Jinja, PuMuPDF, PYXL, CSRF, etc etc

Fundus Image Manager
A comprehensive system for an eye hospital to manage eye images. It facilitates the generation of curated datasets for training and validating Artificial Intelligence (AI) models targeted at detecting Glaucoma, Diabetic Retinopathy (DR), and Age-related Macular Degeneration (AMD). Has specific workflows for Remedio FOP zip files that get downlaoded from the remedio dashboard.

Please go through and provide feedback

/r/flask
https://redd.it/1oayi6m

QuickScale v0.60.0 - Deploy Django to Railway in 5 minutes with one command

Just shipped QuickScale v0.60.0, and I'm excited about the deployment automation we built.

What's New

One command handles the entire deployment workflow:

quickscale deploy railway

This automatically:

Provisions PostgreSQL database \- No manual Railway dashboard clicking
Generates SECRET_KEY \- Uses Django's secure random generation
Configures environment \- Interactive prompts for ALLOWED\_HOSTS, DEBUG, etc.
Runs migrations \- Executes `manage.py` migrate on Railway
Collects static files \- Handles `collectstatic` for production
Sets up HTTPS \- Railway auto-provisions SSL certificates

The entire process takes under 5 minutes.

# Quick Start

# Install QuickScale
pip install quickscale

# Create new project
quickscale init my-saas-app
cd my-saas-app

# Deploy to Railway
quickscale deploy railway
The CLI guides you through the process with clear prompts.

# Looking for Feedback, would love to hear yout thoughts.

GitHub: github.com/Experto-AI/quickscale

Railway deployment docs: Railway Guide

/r/django
https://redd.it/1oea4p0

iommi 7.19.0 released

New hero page: https://iommi.rocks/

- A new system for advanced layouts for forms and tables. Example: https://docs.iommi.rocks/cookbook_forms.html#how-do-i-make-complex-layouts-for-forms
- A manually drag-and-drop reorderable feature for EditTable
- Tables will automatically pick up sort order from your queryset

And a bunch of other minor features and bug fixes of course.

/r/django
https://redd.it/1oeq25m

What are the long term goal of tasks in Django 6?

I see Django 6 is adding tasks similar to celery and wonder if the long term goal here is to replace celery with feature parity or simply act as a "celery lite"?

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

Asking the impossible, may be not!

So currently, If someone is going with django, they can either do 1 of the 2 and never both. If they use django fullstack then they have to duplicate the code to provide api endpoints for handhelds like mobile. If they use it just for api to be consumed by mobile apps, then you cant just use the same api with django templates for browsers.
May be someday in the future, django 7 may be, where one can use django to write an api and use the api with django templates without having to use a separate front end. I wanna use django to serve both the browser and apps on mobiles which need api endpoints.

/r/django
https://redd.it/1oewzv4

How Do You Structure Large Django Projects? Tips for Scalability and Maintainability

Hi everyone!

I’ve been working with Django for a while, and as my projects grow, I’m realizing that structuring apps and managing dependencies gets tricky. I’d love to hear how you all approach:

* Organizing apps and reusable components
* Handling complex models and relationships
* Managing settings for multiple environments (dev, staging, production)
* Using Django signals or middleware effectively without creating spaghetti code
* Any patterns or best practices you swear by

Also, if you have experience with Django in bigger teams or production-scale projects, I’d love to hear about common pitfalls and lessons learned.

Let’s share some tips for keeping Django projects clean, scalable, and maintainable!

/r/djangolearning
https://redd.it/1oeoden

Is Django dying with time

So, these days most companies use FASTAPI to build AI apps. So, what is the points of spending time mastering Django? Should I shift towards FASTAPI?

/r/djangolearning
https://redd.it/1oebpr2

Help with form creation

Hello Crispy Pythonians with Nutella fingers, I need your feedback on what is the best practice to create a form and view that needs to ask for feedback about our products to the user.

I have 2 models containing fields that needs to be filled. 1 model's fields, needs to be filled just once, while the other one needs to be filled once for each category of product.
Example:
Model1 = general feedback
Model 2 = feedback for each product.

How would you set up the model/view/template and what advice would you give me?

/r/django
https://redd.it/1of2lcu

I built a production-ready Django/DRF Boilerplate with Custom User Auth, JWT, and Spectaular Docs feedback welcome!

Hey,

I spent a while cleaning up my personal project starter and decided to open-source it as drf-boilerplate. I'm sharing it because I'm tired of rewriting the same core authentication logic for every new DRF API.

What it solves:

1. The Custom User Pain: Fully configured AbstractUser model with login via either email OR username.
2. Auth Separation: Integrated djangorestframework-simplejwt with pre-built endpoints for token refresh/blacklist.
3. Deployment Headache: Settings are split into base, development, and production, all driven by django-environ for clean .env handling.
4. UX Flows: Includes models/stubs for Email Verification and Password Reset flows (the hardest parts to set up correctly).

I'd appreciate any feedback on the file structure etc.

Repo Link: https://github.com/fulanii/drf-boilerplate/

/r/djangolearning
https://redd.it/1of4a82

I built a production-ready Django/DRF Boilerplate with Custom User Auth, JWT, and Spectaular Docs feedback welcome!

Hey,

I spent a while cleaning up my personal project starter and decided to open-source it as drf-boilerplate. I'm sharing it because I'm tired of rewriting the same core authentication logic for every new DRF API.

What it solves:

1. The Custom User Pain: Fully configured AbstractUser model with login via either email OR username.
2. Auth Separation: Integrated djangorestframework-simplejwt with pre-built endpoints for token refresh/blacklist.
3. Deployment Headache: Settings are split into base, development, and production, all driven by django-environ for clean .env handling.
4. UX Flows: Includes models/stubs for Email Verification and Password Reset flows (the hardest parts to set up correctly).

I'd appreciate any feedback on the file structure etc.

Repo Link: https://github.com/fulanii/drf-boilerplate/

/r/django
https://redd.it/1of47w2

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/1ofdbzk

Skylos: Dead code + Vibe code security flaws detector

Hi everyone

I have created Skylos to detect dead code quite a while back. Just here to give a short update. We have updated and expanded Skylos' capabilities to include common security flaws generated by AI. These things include the basic stuff like SQL injection, path traversal etc. So how this works, your py files are parsed through the AST.. After that the security scanners will take over and run over that same tree. Once that is complete, a generic "dangerous" table is applied node by node to catch any security flaws. As for how the dead code side works, i'm gonna keep it short. basically it parses the py files to build a graph of functions, classes, variables etc etc. it will then record where each symbol is referenced. thats it.

# Target audience

Anyone working with python code.

# Why use Skylos?

I know people will ask why use this when there's vulture, bandit etc etc. Well I mean those are really established and great libraries too. We're kind of more niche. For starters, Skylos provides real taint tracking by propagating the taint in the AST. If i'm not wrong although i may be, bandit uses pattern matching. Just

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

Faster Jupyter Notebooks with the Zuban Language Server

The Zuban Language Server now supports Jupyter notebooks in addition to standard Python files.

You can use this, for example, if you have the Zuban extension installed in VSCode and work with Jupyter notebooks there. This update marks one of the final steps towards a feature-complete Python Language Server; remaining work includes auto-imports and a few smaller features.

/r/Python
https://redd.it/1oet078

full stack web development using Django or cybersecurity and networking. What should I chose?

This is my first post. I see that there is more insightful people in reddit. I am a computer science graduate 2025 passout. I tried for numerous mass drives and startup but failed to get in nothing. I realized i have to built a skill of my own rather than looking for company. but i dont know what to chose. Since i selected computer Science for its demand at that time but i don't even get a job.

I am thinking what to chose full stack web development or cybersecurity? if it is web development i will chose Django and i don't know much about cybersecurity... but i consider it because the rumors that it is good career path. What should i do?

/r/djangolearning
https://redd.it/1oa5l0a

D How was Multi-head Latent Attention not a thing before DeepSeek-V2 came up with it?

Multi-head Latent Attention (MLA) was introduced by DeepSeek-V2 in 2024. The idea is to project keys and values into a latent space and perform attention there, which drastically reduces complexity.

What I don't understand: how did no one propose this earlier? It feels like a pretty natural next step, especially given the trends we’ve seen over the past few years.

For instance, the shift from diffusion in pixel space to latent diffusion (e.g. Stable Diffusion) followed that same principle: operate in a learned latent representation (e.g. through some modern VAE variation) for efficiency. And even in the attention world, Perceiver (https://arxiv.org/abs/2103.03206) in 2021 already explored projecting queries into a latent space to reduce complexity. MLA feels like a very small step from that idea, yet it didn't appear until 2024.

Of course, I know this is a bit of a naive take since in ML research we all know how this goes: in practice, good ideas often don't work out out of the box without "tricks" or nuances. Maybe (probably) someone did try something like MLA years ago, but it just didn't deliver without the right tricks or architecture choices.

So I'm wondering: is that what happened here? Did people experiment with latent attention

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

My Django based open-source project PdfDing is receiving a grant

Hi r/django,

for quite some time I have been working on the open-source project PdfDing - a selfhosted PDF manager, viewer and editor offering a seamless user experience on multiple devices. Last week PdfDing was selected to receive a grant from the NGI Zero Commons Fund. This fund is dedicated to helping deliver, mature and scale new internet commons across the whole technology spectrum and is amongst others funded by the European Commission. The exact sum of the grant still needs to be discussed, but obviously I am very stocked to have been selected and need to share it with the community.

You can find the repository here. As always I would be quite happy about a star and you trying out the application.

/r/django
https://redd.it/1of90vh