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Daily Python News Question, Tips and Tricks, Best Practices on Python Programming Language Find more reddit channels over at @r_channels
Question for small prod app monitoring
How do you keep tabs on things like: OS updates / security patches, dependency or framework security issues, or just general time to upgrade Django or Python, or App health beyond “it’s up”.
I’d love a weekly email digest that gives me a list of these things and the ‘risk’ of not doing it.
/r/djangolearning
https://redd.it/1pq0ky3
Introducing the 2026 DSF Board
https://www.djangoproject.com/weblog/2025/dec/18/introducing-the-2026-dsf-board/
/r/django
https://redd.it/1ppyxiz
Rust and OCaml-style exhaustive error and None handling for Python
I had this Idea for over 3 years already. One time my manager called me at 3 AM on Friday and he was furious, the app I was working on crashed in production because of an unhandled error, while he was demoing it to a huge prospect. The app was using a document parsing lib that had infinite amount of edge cases (documents are messy, you can't even imagine how messy they can be). Now I finally implemented this idea. It's called Pyrethrin.
* **What My Project Does** \- It's a library that lets you create functions that explicitly define what exceptions it can raise or that it can return a None, and the other function using this one has to exhaustively implement all the cases, if any handle is missing or not handled at all, Pyrethrin will throw an error at "compile" time (on the first run in case of Python).
* **Target Audience** \- the tool is primarily designed for production use, especially in large Python teams. Other target audience is Python library developers, they can "shield" their library for their users to gain their trust (it will fail on their end way less than without Pyrethrin)
* **Comparison** \- I
/r/Python
https://redd.it/1povyby
Thursday Daily Thread: Python Careers, Courses, and Furthering Education!
# Weekly Thread: Professional Use, Jobs, and Education 🏢
Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.
---
## How it Works:
1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.
---
## Guidelines:
- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.
---
## Example Topics:
1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?
---
Let's help each other grow in our careers and education. Happy discussing! 🌟
/r/Python
https://redd.it/1ppcapw
I built a Japan food discovery site with Django (ListView + model-driven images)
/r/django
https://redd.it/1ppd4w7
Any sites that I can used to make API requests for the positions of planets in the solar system
I am creating a program that calculates orbital mechanics. And one option I want is the ability to use as a starting point the current positions of the Solar System. So if would like to find a site that can I use to easily make API request for the positions (whether relative to the sun or earth), velocities, mass and radii of the planets in the solar system
/r/Python
https://redd.it/1pp0bzi
Django Tasks: A closer look at the new API and the database backend
https://www.youtube.com/watch?v=BJVUCyh-dto
/r/django
https://redd.it/1pp0heu
Spark can spill to disk why do OOM errors still happen
I was thinking about Spark’s spill to disk feat. My understanding is that spark.local.dir acts as a scratchpad for operations that don’t fit in memory. In theory, anything that doesn’t fit should spill to disk, which would mean OOM errors shouldn’t happen.
Here are a few scenarios that confuse me
A shuffle between executors. The receiving executor might get more data than RAM can hold but shouldn’t it just start writing to disk
A coalesce with one partition triggers a shuffle. The executor gathers a large chunk of data. Spill-to-disk should prevent OOM here too
A driver running collect on a massive dataset. The driver keeps all data in memory so OOM makes sense, but what about executors
I can’t think of cases where OOM should happen if spilling works as expected. Yet it does happen.
want to understand what actually causes these OOM errors and how people handle them
/r/Python
https://redd.it/1poqgba
Beta release of ty - an extremely fast Python type checker and language server
See the blog post here https://astral.sh/blog/ty and the github link here https://github.com/astral-sh/ty/releases/tag/0.0.2
/r/Python
https://redd.it/1podix2
WhatsApp Wrapped with Polars & Plotly: Analyze chat history locally
I've always wanted something like Spotify Wrapped but for WhatsApp. There are some tools out there that do this, but every one I found either runs your chat history on their servers or is closed source. I wasn't comfortable with all that, so this year I built my own.
## What My Project Does
WhatsApp Wrapped generates visual reports for your group chats. You export your chat from WhatsApp (without media), run it through the tool, and get an HTML report with analytics. Everything runs locally or in your own Colab session. Nothing gets sent anywhere.
Here is a Sample Report.
Features include message counts, activity patterns, emoji stats, word clouds, and calendar heatmaps. The easiest way to use it is through Google Colab - just upload your chat export and download the report. There's also a CLI for local use.
## Target Audience
Anyone who wants to analyze their WhatsApp chats without uploading them to someone else's server. It's ready to use now.
## Comparison
Unlike other web tools that require uploading your data, this runs entirely on your machine (or your own Colab). It's also open source, so you can see exactly what it does with your chats.
Tech: Python, Polars, Plotly, Jinja2.
Links:
- GitHub
- Sample Report
- Google
/r/Python
[https://redd.it/1po9n17
Front end
So, I know backend (django) like at least to the point where I know what to search yk? . And can somewhat build backend of an app, but I am pretty bad at frontend , like I don't understand anything at all. ( I've always hated templates and static files and DTL) . But I do wanna learn it now (ps some one told me they can't give an opportunity since I'm not a full stack guy) . How do I approach front end? Like from the basics ? I would appreciate if you experienced folks can guide this hermit😔✋🏻
/r/django
https://redd.it/1po18nb
YourTimeStarts.now: A Small Flask App for Taskmaster-style Tasks
https://yourtimestarts.now
/r/flask
https://redd.it/1pnpqu1
P Built semantic PDF search with sentence-transformers + DuckDB - benchmarked chunking approaches
I built DocMine to make PDF research papers and documentation semantically searchable. 3-line API, runs locally, no API keys.
Architecture:
PyMuPDF (extraction) → Chonkie (semantic chunking) → sentence-transformers (embeddings) → DuckDB (vector storage)
Key decision: Semantic chunking vs fixed-size chunks
\- Semantic boundaries preserve context across sentences
\- \~20% larger chunks but significantly better retrieval quality
\- Tradeoff: 3x slower than naive splitting
Benchmarks (M1 Mac, Python 3.13):
\- 48-page PDF: 104s total (13.5s embeddings, 3.4s chunking, 0.4s extraction)
\- Search latency: 425ms average
\- Memory: Single-file DuckDB, <100MB for 1500 chunks
Example use case:
```python
from docmine.pipeline import PDFPipeline
pipeline = PDFPipeline()
pipeline.ingest_directory("./papers")
results = pipeline.search("CRISPR gene editing methods", top_k=5)
GitHub: https://github.com/bcfeen/DocMine
Open questions I'm still exploring:
1. When is semantic chunking worth the overhead vs simple sentence splitting?
2. Best way to handle tables/figures embedded in PDFs?
3. Optimal chunk_size for different document types (papers vs manuals)?
Feedback on the architecture or chunking approach welcome!
/r/Python
https://redd.it/1pnvuhf
Looking for CSS frameworks, recommendations?
For my next project I'm staying with full stack Django templating with htmx I'm terrible at CSS and I hate writing it. A few of you will moan about that but I like frame works that have lots of components.
Do you have any recommendations?
Boot strap
Metroui
Beercss
Basecoatui
All great 👍 but are there anymore hiding in the wood work?
/r/django
https://redd.it/1pnlff8
Building the Fastest Python CI
Hey all, there is a frustrating lack of resources and tooling for building Python CIs in a monorepo setting so I wrote up how we do it at $job.
# What my project does
We use uv as a package manager and pex to bundle our Python code and dependencies into executables. Pex recently added a feature that allows it to consume its dependencies from uv which drastically speeds up builds. This trick is included in the guide. Additionally, to keep our builds fast and vertically scalable we use a light-weight build system called Grog that allows us to cache and skip builds aswell as run them in parallel.
# Target Audience
Anyone building Python CI pipelines at small to medium scale.
# Comparison
The closest comparison to this would be Pants which comes with a massive complexity tasks and does not play well with existing dev tooling (more about this in the post). This approach on the other hand builds on top of uv and thus keeps the setup pretty lean while still delivering great performance.
Let me know what you think 🙏
Guide: https://chrismati.cz/posts/building-the-fastest-python-ci/
Demo repository: https://github.com/chrismatix/uv-pex-monorepo
/r/Python
https://redd.it/1pnbze0
Hitting the Home Stretch: Help Us Reach the Django Software Foundation's Year-End Goal!
https://www.djangoproject.com/weblog/2025/dec/18/hitting-the-home-stretch-help-us-reach-the-django/
/r/django
https://redd.it/1pq3ufk
What are some free uwsgi alternatives that have a similar set of features?
I would like to move away from uwsgi because it is no longer maintained. What are some free alternatives that have a similar set of features. More precisely I need the touch-relod and cron features because my app relies on them a lot.
/r/Python
https://redd.it/1ppov9c
Released datasetiq: Python client for millions of economic datasets – pandas-ready
Hey r/Python!
I'm excited to share datasetiq v0.1.2 – a lightweight Python library that makes fetching and analyzing global macro data super simple.
It pulls from trusted sources like FRED, IMF, World Bank, OECD, BLS, and more, delivering data as clean pandas DataFrames with built-in caching, async support, and easy configuration.
\### What My Project Does
datasetiq is a lightweight Python library that lets you fetch and work millions of global economic time series from trusted sources like FRED, IMF, World Bank, OECD, BLS, US Census, and more. It returns clean pandas DataFrames instantly, with built-in caching, async support, and simple configuration—perfect for macro analysis, econometrics, or quick prototyping in Jupyter.
Python is central here: the library is built on pandas for seamless data handling, async for efficient batch requests, and integrates with plotting tools like matplotlib/seaborn.
\### Target Audience
Primarily aimed at economists, data analysts, researchers, macro hedge funds, central banks, and anyone doing data-driven macro work. It's production-ready (with caching and error handling) but also great for hobbyists or students exploring economic datasets. Free tier available for personal use.
\### Comparison
Unlike general API wrappers (e.g., fredapi or pandas-datareader), datasetiq unifies multiple sources (FRED + IMF + World Bank + 9+ others) under one simple interface, adds
/r/Python
https://redd.it/1ppgd7n
I built a Django referral system because Rewardful / FirstPromoter didn’t work with Appsflyer links
https://github.com/soldatov-ss/django-referral-system
/r/django
https://redd.it/1pnyt3a
django-allauth move from GitHub to Codeberg a Year Ago Looking Smarter Every Day
tl;dr: django-allauth’s move from GitHub to Codeberg a year ago got a lot of doubt at first, but it is looking wiser by the day now with GitHub’s new fees for private repo runners coming in 2026. This shows Microsoft’s push to monetize more, which hurts trust in their freemium setup, and makes devs less likely to suggest it for work. What alternatives do you use for home and work?
A year ago, django-allauth moved from Microsoft GitHub to Codeberg, drawing skepticism over visibility, contributions, and security. But with GitHub’s new $0.002/minute charge for self-hosted runners in private repos starting March 2026 (sparking complaints about Microsoft’s profit focus), it is more evidence the move was smart. They dodged a platform that is increasingly monetizing features.
Many companies keep open source free to hook users into paid private or commercial tiers. Tailscale (I’m a big fan) does this well with affordable home plans that encourage enterprise adoption as they explain in this blog post, which is a positive approach. But when companies like Micro$oft make these changes and erode trust, they negate the model they originally adopted. People start to recognize the slow boil and eventually jump out of the pot, hurting the
/r/django
https://redd.it/1pp7jyc
Python Podcasts & Conference Talks (week 51, 2025)
Hi r/python! Welcome to another post in this series brought to you by Tech Talks Weekly. Below, you'll find all the Python conference talks and podcasts published in the last 7 days:
# 🎧 Podcasts
1. **"#530: anywidget: Jupyter Widgets made easy"** ⸱ Talk Python To Me ⸱ 13 Dec 2025 ⸱ 01h 11m 21s
# 📺 Conference talks
# PyData Boston 2025
1. **"Ian Stokes-Rees - "Save your API Keys for someone else" - PyData Boston 2025"** ⸱ +300 views ⸱ 15 Dec 2025 ⸱ 01h 34m 34s
2. **"Allen Downey-The SAT math gap- gender difference or selection bias--PyData Boston 2025"** ⸱ +200 views ⸱ 15 Dec 2025 ⸱ 00h 30m 14s
3. **"Eric Ma - Building LLM Agents Made Simple a - PyData Boston 2025"** ⸱ +100 views ⸱ 15 Dec 2025 ⸱ 01h 27m 50s
4. **"Katrina Riehl - CUDA Python Kernel Authoring - PyData Boston 2025"** ⸱ +100 views ⸱ 15 Dec 2025 ⸱ 02h 51m 04s
5. **"Chuxin Liu & Yiwen Liu - Build Your MCP server - PyData Boston 2025"** ⸱ +100 views ⸱ 15 Dec 2025 ⸱ 01h 15m 54s
6. **"Gilberto Hernandez - Notebook to Pipeline: Hands-On Data Engineering w Python - PyData Boston 2025"** ⸱ +100 views ⸱ 15 Dec 2025
/r/Python
https://redd.it/1pp3i0g
Looking for collaborator who has some web develop skills and strong communication
I am looking for a American or European individual with strong English skills and general knowledge of programming languages.
They should be able to fluently explain general concepts of program development in English and possess excellent communication skills.
The pay is $50 or more per hour, and specific details will be discussed after we meet.
If you don't mind, let me know your idea.
Thanks for your attention.
/r/django
https://redd.it/1povgtc
I made FastAPI Clean CLI – Production-ready scaffolding with Clean Architecture
Hey r/Python,
What My Project Does
FastAPI Clean CLI is a pip-installable command-line tool that instantly scaffolds a complete, production-ready FastAPI project with strict Clean Architecture (4 layers: Domain, Application, Infrastructure, Presentation). It includes one-command full CRUD generation, optional production features like JWT auth, Redis caching, Celery tasks, Docker Compose orchestration, tests, and CI/CD.
Target Audience
Backend developers building scalable, maintainable FastAPI apps – especially for enterprise or long-term projects where boilerplate and clean structure matter (not just quick prototypes).
Comparison
Unlike simpler tools like cookiecutter-fastapi or manage-fastapi, this one enforces full Clean Architecture with dependency injection, repository pattern, and auto-generates vertical slices (CRUD + tests). It also bundles more production batteries (Celery, Prometheus, MinIO) in one command, while keeping everything optional.
Quick start:
pip install fastapi-clean-cli
fastapi-clean init --name=my_api --db=postgresql --auth=jwt --docker
It's on PyPI with over 600 downloads in the first few weeks!
GitHub: https://github.com/Amirrdoustdar/fastclean
PyPI: https://pypi.org/project/fastapi-clean-cli/
Stats: https://pepy.tech/project/fastapi-clean-cli
This is my first major open-source tool. Feedback welcome – what should I add next (MongoDB support coming soon)?
Thanks! 🚀
/r/Python
https://redd.it/1poh525
Looking for Django developer for long term collaboration
Hello, I am looking for developer for my work.
It's easy, long term part time work.
Only US, America, Europe based developers are available.
DM for details.
/r/django
https://redd.it/1podw9b
Recommended approach for single-endpoint, passwordless email-code login with domain restrictions with django-allauth
Hi, I am looking for guidance on implementing the following authentication flow using django-allauth.
Requirements
1. Restrict URL access Only /accounts/login/ should be accessible. All other django-allauth endpoints (signup, logout, password reset, email management, etc.), should be inaccessible. This applies regardless of whether the user is authenticated
2. Passwordless login via email code. No passwords are used, a user submits their email address on the login form and a one-time login code is sent to that email. If the email does not already exist, automatically create the user and send the login code, them log the user in after code verification
3. Domain-restricted access. Only email addresses from a whitelist of allowed domains may log in or be registered, attempts from other domains should be rejected before user creation.
I am building a service that depends on the student having access to the email address they are authenticating with, so email based verification is a core requirement. I want to avoid exposing any user facing account management or password based flows.
How may I achieve this?
/r/django
https://redd.it/1po8pxg
Tool for splitting sports highlight videos into individual clips
Hi folks, I am looking for a way to split rugby highlight videos automatically into single clips containing tries. For example: https://www.youtube.com/watch\\?v\\=rnCF2VqYwdM to be split into videos of each of the 9 tries during the match.
Here are some of the complications involved:
\- Scenes have multiple camera angles and replays - so scene detection cutting based on visual by itself isn't feasible.
\- Not every scene is a try
\- Not every highlight video has consistent graphics - Some show a graphic between scenes, some do a cross fade. The scoreboard looks different in different competitions.
I imagine that the solution to this is some sort of combination of frame by frame analysis for scene detection, OCR of the scoreboard/time, audio analysis and commentary dialog. The solution also may have to be different for each broadcast so there might not even be a one size fits all solution.
Any suggestions?
/r/Python
https://redd.it/1pnznd9
I built PyGHA: Write GitHub Actions in Python, not YAML (Type-safe CI/CD)
# What My Project Does
PyGHA (v0.2.1, early beta) is a Python-native CI/CD framework that lets you define, test, and transpile workflow pipelines into GitHub Actions YAML using real Python instead of raw YAML. You write your workflows as Python functions, decorators, and control flow, and PyGHA generates the GitHub Actions files for you. It supports building, testing, linting, deploying, conditionals, matrices, and more through familiar Python constructs.
from pygha import job, defaultpipeline
from pygha.steps import shell, checkout, uses, when
from pygha.expr import runner, always
# Configure the default pipeline to run on:
# - pushes to main
# - pull requests
defaultpipeline(onpush=["main"], onpullrequest=True)
# ---------------------------------------------------
# 1. Test job that runs across 3 Python versions
# ---------------------------------------------------
@job(
name="test",
matrix={"python": ["3.11", "3.12", "3.13"]},
)
def testmatrix():
/r/Python
https://redd.it/1pni2se
Why don't dataclasses or attrs derive from a base class?
Both the standard `dataclasses` and the third-party `attrs` package follow the same approach: if you want to tell if an object or type is created using them, you need to do it in a non-standard way (call dataclasses.is_dataclass(), or catch attrs.NotAnAttrsClassError). It seems that both of them rely on setting a magic attribute in generated classes, so why not have them derive from an ABC with that attribute declared (or make it a property), so that users could use the standard isinstance? Was it performance considerations or something else?
/r/Python
https://redd.it/1pnne6l
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/1pnn7xm
Miguel's Flask Course
Hi all,
I'm currently learning Flask and after some due diligence I dove into Miguel's course. I felt good for the first few chapters and was grasping concepts pretty well then things started to get more complicated, I think more so the things that were introduced outside of the scope of Flask (third party libraries that are used) and it just completely knocked me off my horse. I feel like I'm just watching the videos now. I've made it to pretty much the end of the course but I don't feel like I've learnt as much as I should or could've. I'm not sure whether I'm too dumb or what's limiting me. Is it normal to find this course hard? Everyone says it's the go to for Flask and that's incredible, but I've honestly struggled immensley with it.
I moved to flask after I learnt JS and React, built some of my own little projects and felt comfortable enough to move on. I didn't really experience roadblocks like this with JS and React. But Flask, although the simple routes and whatnot are easy, it's beyond that when I feel stuck. I'm not sure what to do now, I've been learning
/r/flask
https://redd.it/1pnblkp