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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
Best WebSocket Library
Hi everyone! I am developing an application that requires real-time data fetching from an API, for which I need to use the WebSocket protocol. As of June 2025, what is the best library to implement WebSockets in Python? As of now, the module that handles fetching data from the API isn't very complex — its only requirement is to be able to smoothly handle around 50-100 concurrent connections with the API, where the rate of data flow is about 10 bytes per second for each connection. While the per-connection data-flow rate is expected to remain at only 10 bytes, the number of open concurrent connections may grow up to 3000, or even more. Thus, scalability is a factor that I need to consider.
I searched this sub and other related subs for discussions related to the websockets library, but couldn't find any useful threads. As a matter of fact, I couldn't find a lot of threads specifically about this library. This was unexpected, because I assumed that websockets was a popular library for implementing WebSockets in Python, and based on this assumption, I further assumed that there would be a lot of discussions related to it on Reddit. Now I
/r/Python
https://redd.it/1ljdlmw
How can I give out a webapp but not the source code?
I want to give someone a django app I made to use locally but I dont want them to be able to reproduce or make changes to the code. Whats a good way to do so?
Ive seen Obfuscation (pyarmor) and making Licens Keys is a good way to go but have no real knowledge of that process. Also saw Pyinstaller might be an option but again, no Idea. Any advice or usefull links are appreciated.
BONUS QUESTION: How can I make the install process fool proof for the user? Just as far as installing python and requirements goes along with the project in one install file.
/r/django
https://redd.it/1ljgvev
htmx accessibility gaps: data and recommendations
https://wagtail.org/blog/htmx-accessibility-gaps-data-and-recommendations/
/r/django
https://redd.it/1lj9vci
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/1liwla2
Interview Advice for fresher role as backend Django Developer ( AWS is a plus )
Greetings to everyone,
I received an email saying there is an interview scheduled on upcoming wednesday 26june2025 this is my first interview which is technical round 1 (there are two+hr round). I am a bit nervous right now and wanted to ask for the resources or topics to prepare well for these interviews. The job opening is for freshers and hiring for django+aws.
About my resume : I have written two internships but those are frontend based and two projects which are of django and three certifications (aws,django,react).
As people here always help students therefore I came straight here to ask.
Thank you.
For the people who work in similar position, what do they expect you on your interview?
/r/django
https://redd.it/1linndz
If someone have pdf for django please send
I am learning django and yt tutorial are good but they explain less. While CBVs are considered best practices but many youtube tutorial are old or new just doesn't cover CBVs that much.if you have pdf please send me.
/r/djangolearning
https://redd.it/1lin4io
R Reinforcement Learning Teachers of Test Time Scaling
TL;DR: The raw outputs of our new 7B RL model provide stronger distillation and cold-starting than the filtered and post-processed reasoning traces of orders-of-magnitude larger LMs such as DeepSeek-R1.
How did we achieve this result? We turned the RL task on its head. Rather than training to solve challenging problems from scratch, we optimize our models to generate clear, step-by-step "explanations" to "teach" their students, providing both the problem’s question and its solution already in their input prompt.
This makes the RL training task much easier and also directly aligned with downstream distillation, allowing us to train tiny 7B teachers, boosting the performance of even larger 32B students.
If you are interested to learn more, please check out our new work:
Paper: https://arxiv.org/abs/2506.08388
Blog: https://sakana.ai/rlt/
Open source code: https://github.com/SakanaAI/RLT
If you have any questions, please ask them below or feel free to get in touch, any discussion is more than welcome :)
/r/MachineLearning
https://redd.it/1lid95g
D Conceptually/On a Code Basis - Why does Pytorch work with CUDA out of the box, with minimal setup required, but tensorflow would require all sorts of dependencies?
Hopefully this question doesn't break rule 6.
When I first learned machine learning, we primarily used TensorFlow on platforms like Google Colab or cloud platforms like Databricks, so I never had to worry about setting up Python or TensorFlow environments myself.
Now that I’m working on personal projects, I want to leverage my gaming PC to accelerate training using my GPU. Since I’m most familiar with the TensorFlow model training process, I started off with TensorFlow.
But my god—it was such a pain to set up. As you all probably know, getting it to work often involves very roundabout methods, like using WSL or setting up a Docker dev container.
Then I tried PyTorch, and realized how much easier it is to get everything running with CUDA. That got me thinking: conceptually, why does PyTorch require minimal setup to use CUDA, while TensorFlow needs all sorts of dependencies and is just generally a pain to get working?
/r/MachineLearning
https://redd.it/1lialoj
[Showcase] leetfetch – A CLI tool to fetch and organize your LeetCode submissions
**GitHub**: [https://github.com/Rage997/leetfetch](https://github.com/Rage997/leetfetch)
**Example output repo**: [https://github.com/Rage997/LeetCode](https://github.com/Rage997/LeetCode)
# What It Does
**leetfetch** is a command-line Python tool that downloads all your LeetCode submissions and problem descriptions using your browser session (no password or API key needed). It groups them by problem and language, and creates Markdown summaries.
# Target Audience
Anyone who solves problems on LeetCode and wants to:
* Back up their work
* Track progress locally or on GitHub
# How It’s Different
Compared to other tools, leetfetch:
* Uses the current GraphQL API
* Filters by accepted (or all) submissions
* Generates a clean, browsable folder structure
# Example Usage
# Download accepted Python3 submissions
python3 main.py --languages python3
# Download all submissions in all languages
python3 main.py --no-only-accepted --all-languages
# Only fetch problems not yet saved
python3 main.py --sync
No login needed – just need to be signed in with your browser.
Let me know what you think.
/r/Python
https://redd.it/1liej6o
pandas/python functions (pushing and calling dataframe)
Hello all,
I am fairly new to python and all so i am having difficulty managing next.
So i wanted to create a dim table in separate file, then push few columns to SQL, and allow somehow for few other columns to be allowed to be pulled in another python file, where i would merge it with that data-frame.(creating ID keys basically),
But i am having difficulties doing that,its giving me some long as error. (This part when i am calling in other file : (product_table= Orders_product() )
Could someone point me to right direction?
Product table:
import pandas as pd
from MySQL import getmysqlengine
#getting file
File=r"ExcelFilePath"
Sheet="Orders"
df=pd.readexcel(File, sheetname=Sheet)
productcolumns=["Product Category","Product Sub-Category","Product Container","Product Name"]
def Ordersproduct():
#cleaning text/droping duplicates
dfproducts = df[productcolumns].copy()
for productCol in productcolumns:
dfproducts[productCol] = dfproducts[productCol].str.strip()
dfproducts['ProductKeyJoin'] = dfproductsproduct_columns.agg('|'.join, axis=1)
/r/Python
https://redd.it/1lhyni4
Fenix: I built an algorithmic trading bot with CrewAI, Ollama, and Pandas.
Hey r/Python,
I'm excited to share a project I've been passionately working on, built entirely within the Python ecosystem: Fenix Trading Bot. The post was removed earlier for missing some sections, so here is a more structured breakdown.
GitHub Link: https://github.com/Ganador1/FenixAI\_tradingBot
# What My Project Does
Fenix is an open-source framework for algorithmic cryptocurrency trading. Instead of relying on a single strategy, it uses a crew of specialized AI agents orchestrated by CrewAI to make decisions. The workflow is:
1. It scrapes data from multiple sources: news feeds, social media (Twitter/Reddit), and real-time market data.
2. It uses a Visual Agent with a vision model (LLaVA) to analyze screenshots of TradingView charts, identifying visual patterns.
3. A Technical Agent analyzes quantitative indicators (RSI, MACD, etc.).
4. A Sentiment Agent reads news/social media to gauge market sentiment.
5. The analyses are passed to Consensus and Risk Management agents that weigh the evidence, check against user-defined risk parameters, and make the final BUY, SELL, or HOLD decision. The entire AI analysis runs 100% locally using Ollama, ensuring privacy and zero API costs.
# Target Audience
This project is aimed at:
Python Developers & AI Enthusiasts: Who want to see a real-world, complex application of modern Python libraries like CrewAI, Ollama, Pydantic, and Selenium working together. It serves as a great case study for building multi-agent systems.
Algorithmic Traders & Quants: Who are looking for a flexible, open-source framework that goes beyond
/r/Python
https://redd.it/1li8id5
I made Flask-Squeeze which minifies and compresses responses!
https://github.com/mkrd/Flask-Squeeze
/r/flask
https://redd.it/1lhn2yu
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/1li2gwg
[P] This has been done like a thousand time before, but here I am presenting my very own image denoising model
https://redd.it/1lhny9b
@pythondaily
Parallel and Concurrent Programming in Python: A Practical Guide
Hey, I made a video about Parallel and Concurrent Programming in Python with threading and multiprocessing.
First we make a program which doesn't use any of those methods and after that we take advantage of those methods and see the differences in terms of performance
https://www.youtube.com/watch?v=IQxKjGEVteI
/r/Python
https://redd.it/1lhgxek
PyPDFForm v3.0.0 has released
Hello r/Python! About a year ago I made a post about an open source project I have been working on for about 5 years called PyPDFForm. It is a Python library that specializes in PDF form manipulations, providing essential functionalities such as inspect/edit form fields, filling forms, creating form fields, and many more.
The project received some very positive feedback from the community and has been evolving since then. Right now it's at about 14k monthly pip installs and I'm constantly getting new issues opened for different requests for the library. And because of the rise of its usage there are some groundbreaking major changes needed to happen to the library in order to address some of its legacy problems.
So it is my pleasure to announce that, just this morning, PyPDFForm has released its v3.0.0 major update. I wrote a long paragraph explaining why V3 is necessary. But here I will highlight some of the key changes in it:
1. Complete native PDF form filling. This is the legacy issue that V3 fixes. Instead of what used to be a watermark based approach, now every PDF form filled using PyPDFForm will be the same as if being filled by hand.
2. Best compatibility with Adobe Acrobat you will
/r/Python
https://redd.it/1ljas6t
D What's happening behind Google's AI Overviews?
Curious to know what happens behind the scenes of the AI Overview widget. The answers are good and the latency with which responses are returned is impressive.
Based on the citations displayed, I could infer that it is a RAG based system, but I wonder how the LLM knows to respond in a particular format for a given question.
/r/MachineLearning
https://redd.it/1lj3e0i
Is it good idea to use debug_toolbar to learn ORM and SQL?
I have recently found out about this tool and it has enormously helped me in understanding ORM and the SQL magic behind it
/r/django
https://redd.it/1lj5ccd
C++ in JupyterLite (WebAssembly) — Interpreting C++ in the Web
https://blog.jupyter.org/c-in-jupyter-interpreting-c-in-the-web-c9d93542f20b
/r/IPython
https://redd.it/1lj57en
How to export editing history of a model
Hi bro,
I have a Django web app
1. How can I export the add, editing history of a model. I want to export all the history of all objects of specific model
https://preview.redd.it/lfswatd76s8f1.png?width=917&format=png&auto=webp&s=fb1cab85d7175af24eadf6d0ba591b2f32af0f79
2. How can I export history activities of user?
Thank you very much
/r/django
https://redd.it/1liyuto
How to implement multi-tenancy with django-tenants for my SaaS ?
Hey devs,
I'm building a SaaS healthcare CRM targeting small or solo medical practices. I want each clinic (tenant) to have its own isolated database schema using django-tenants.
So far, I’ve done the following:
Created a Clinic model using TenantMixin and set autocreateschema = True
Added a Domain model for routing using DomainMixin
Created a custom User model for each tenant
Installed and configured django-tenants
But I still have questions to clarify the right implementation:
1. How should I structure the signup process?
Should I register the tenant (clinic), then switch to that schema and create users?
2. Should the user model be shared (in the public schema) or be tenant-specific?
I need users (doctors/staff) to be isolated per clinic.
3. How can I make sure user login works correctly and is scoped to the right schema?
4. What's the best way to handle domain/subdomain routing for tenants (ex: clinic1.mycrm.com, clinic2.mycrm.com)?
5. Any example repo, best practices, or gotchas I should be aware of?
I’d love to get some feedback or code architecture examples from anyone who’s implemented a similar setup. My goal is to keep tenant data fully isolated and support a clean onboarding experience for new clinics.
Thanks a lot in advance!
/r/django
https://redd.it/1lilzpg
I made a FOSS feature rich Python template with SOTA tools, security, CI/CD, yet easy to use
## Introduction
Hey, created a FOSS Python library template with features I have never seen (especially in Python development) and which IMO is the most comprehensive, yet focused on usability (template setup is one click and one `pdm setup` command to setup locally, after that only `src`, `tests` and `pyproject.toml` should be of your concern), but I'll let you be the judge.
> GitHub repository: https://github.com/open-nudge/opentemplate
Feedback, questions, ideas, all are welcome, either here or on the GitHub's [discussions](https://github.com/open-nudge/opentemplate/discussions) or [issues](https://github.com/open-nudge/opentemplate/issues) (if you find some
bugs), thanks in advance!
- This was posted previously, but reposting as I think I did a very poor job describing what it does, hopefully I did a better job this time, but [here](https://www.reddit.com/r/Python/comments/1lelh8a/opentemplate_foss_python_template_focused_on/) it is anyway.
Also thanks to [u/wyattxdev](https://www.reddit.com/user/wyattxdev/) and his template [here](https://www.reddit.com/r/Python/comments/1lcz532/a_modern_python_project_cookiecutter_template/) for a great showcase how to present the project correctly!
- __This post is also featured on `r/cybersecurity` subreddit__ (focused more on the security side of things, but feel free to check it out if you are interested): https://www.reddit.com/r/cybersecurity/comments/1lim3k5/i_made_a_foss_python_template_with_cicd_security/
## TLDR Overview
- [__Truly open source__](https://open-nudge.github.io/opentemplate/template/about/philosophy): no tokens, no fees, no premium plans, open source software only
- [__State of the art__](https://open-nudge.github.io/opentemplate/template/details): best checkers for Python, YAML, Markdown, prose, and more unified
- [__Easy to use__](https://open-nudge.github.io/opentemplate/template/quickstart/usage): clone templated repo, run `pdm
/r/Python
https://redd.it/1lim6fb
django-hstore-field, An easy to use postgres hstore field that is based on django-hstore-widget
Hello everyone,
Today i released django-hstore-field, an easy to use postgres hstore field that is based on `django-hstore-widget`.
This project is based on stencil.js framework and uses web-components
# 🧐 Usage:
# yourapp/models.py
from django.db import models
from django_hstore_field import HStoreField
class ExampleModel(models.Model):
data = HStoreField()
I built a new package for processing documents for LLM applications: SplitterMR
Hi!
Over the past few months, I've been mulling over the idea of making a Python library. I work as an AI engineer, and I was a little tired of having to reinvent the wheel every time I had to make an RAG to process documents: chunking, reading, image processing, etc.
So, I've started working on a personal project and developed a library to process files you pass in Markdown format and then easily chunk them. I have called it SplitterMR. This library uses several cool things: it has support for Docling, MarkItDown, and PDFPlumber; it can split tables, describe images using VLMs, split text recursively, or do it by tokens. It is very very simple to use!
It's still in development, and I need to keep working on it, but if you could take a look at it in the meantime and tell me how it goes, I'd appreciate it :)
The code repository is: https://github.com/andreshere00/Splitter\_MR/, and the PyPi package is published here: https://pypi.org/project/splitter-mr/
I've also posted a documentation server with several plug-and-play examples so you can try them out and take a look: https://andreshere00.github.io/Splitter\_MR/
And as I said, I'm here for anything. Let me know!
/r/Python
https://redd.it/1liepo1
sodalite - an open source media downloader with a pure python backend
Made this as a passion project, hope you'll like it :) If you did, please star it! did it as a part of a hackathon and l'd appreciate the support.
What my project does
It detects a link you paste from a supported service, parses it via a network request and serves the file through a FastAPI backend.
Intended audience
Mostly someone who's willing to host this, production ig?
Repo link
https://github.com/oterin/sodalite
/r/Python
https://redd.it/1li6ek4
[P] I made a website to visualize machine learning algorithms + derive math from scratch
/r/MachineLearning
https://redd.it/1lhtkr4
Run background tasks in Django with zero external dependencies. Here's an update on my library, django-async-manager.
Hey Django community!
I've posted here before about **django-async-manager**, a library I've been developing, and I wanted to share an update on its progress and features.
**What is django-async-manager?**
It's a lightweight, database-backed task queue for Django that provides a Celery-like experience without external dependencies. Perfect for projects where you need background task processing but don't want the overhead of setting up Redis, RabbitMQ, etc.
**✨ New Feature: Memory Management**
The latest update adds memory limit capabilities to prevent tasks from consuming too much RAM. This is especially useful for long-running tasks or when working in environments with limited resources.
# Task with Memory Limit
@background_task(memory_limit=512) # Limit to 512MB
def memory_intensive_task():
# This task will be terminated if it exceeds 512MB
large_data = process_large_dataset()
return analyze_data(large_data)
# Key Features
* **Simple decorator-based API** \- Just add `@background_task` to any function
* **Task prioritization** \- Set tasks as low, medium, high, or critical priority
* **Multiple queues** \- Route tasks to different workers
* **Task dependencies** \- Chain tasks together
* **Automatic retries** \- With configurable exponential backoff
* **Scheduled tasks** \- Cron-like scheduling for periodic tasks
* **Timeout control** \- Prevent tasks from running too long
* **Memory limits** \- Stop tasks from consuming
/r/django
https://redd.it/1lhxz7r
FastAPI Guard v3.0 - Now with Security Decorators and AI-like Behavior Analysis
Hey r/Python!
So I've been working on my FastAPI security library (fastapi-guard) for a while now, and it's honestly grown way beyond what I thought it would become. Since my last update on r/Python (I wasn't able to post on r/FastAPI until today), I've basically rebuilt the whole thing and added some pretty cool features.
What My Project Does:
Still does all the basic stuff - IP whitelisting/blacklisting, rate limiting, penetration attempt detection, cloud provider blocking, etc. But now it's way more flexible and you can configure everything per route.
What's new:
The biggest addition is Security Decorators. You can now secure individual routes instead of just using the global middleware configuration. Want to rate limit just one endpoint? Block certain countries from accessing your admin panel? Done. No more "all or nothing" approach.
from fastapi_guard.decorators import SecurityDecorator
@app.get("/admin")
@SecurityDecorator.access_control.block_countries(["CN", "RU"])
@SecurityDecorator.rate_limiting.limit(requests=5, window=60)
async def admin_panel():
return {"status": "admin"}
Fast, lightweight parser for Securities and Exchanges Commission Inline XBRL
Hi there, this is a niche package but may help a few people. I noticed that the SEC XBRL endpoint sometimes takes hours to update, and is missing a lot of data, so I wrote a fast, lightweight InLine XBRL parser to fix this.
https://github.com/john-friedman/secxbrl
# What my project does
Parses SEC InLine XBRL quickly using only the Inline XBRL html file, without the need for linkbases, schema files, etc.
# Target Audience
Algorithmic traders, PhD students, Quant researchers, and hobbyists.
# Comparison
Other packages such as python-xbrl, py-xbrl, and brel are focused on parsing most forms of XBRL. This package only parses SEC XBRL. This allows for dramatically faster performance as no additional files need to be downloaded, making it suitable for running on small instances such as t4g.nanos.
The readme contains links to the other packages as they may be a better fit for your usecase.
# Example
from secxbrl import parseinlinexbrl
# load data
path = '../samples/000095017022000796/tsla-20211231.htm'
with open(path,'rb') as f:
content = f.read()
# get all EarningsPerShareBasic
basic = {'val':item['_val','date':item'_context''context_period_enddate'} for item
/r/Python
https://redd.it/1lhdspc
Working on a Django package for tracking marketing campaigns
https://github.com/YounesOMK/django-attribution
/r/django
https://redd.it/1lhlh8l
