Python

Showcase Thread

2026-06-04T16:05:06+00:00

Post all of your code/projects/showcases/AI slop here.

Recycles once a month.

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Thursday Daily Thread: Python Careers, Courses, and Furthering Education!

2026-06-18T00:00:06+00:00

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:

Career Talk: Discuss using Python in your job, or the job market for Python roles.
Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
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:

Career Paths: What kinds of roles are out there for Python developers?
Certifications: Are Python certifications worth it?
Course Recommendations: Any good advanced Python courses to recommend?
Workplace Tools: What Python libraries are indispensable in your professional work?
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! 🌟

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What is one thing you wish you knew before distributing your first Python application?

2026-06-16T12:24:40+00:00

Building a Python application is often the easy part. Getting it into the hands of users can introduce a completely different set of challenges.

Whether it was packaging, updates, compatibility issues, licensing, documentation, or user support, many developers discover new problems only after release.

Looking back, what is one thing you wish you had known before distributing your first Python application?

It would be interesting to hear the lessons people learned from real-world experience.

submitted by /u/Haunting-Shower1654
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Choosing a Python task queue library in 2026: Celery vs Dramatiq vs FastStream vs Taskiq vs Repid

2026-06-16T07:59:36+00:00

I wrote a practical comparison of Python task queue libraries in 2026:

https://aleksul.space/posts/choosing-python-task-queue-library/

It covers Celery, Dramatiq, FastStream, Taskiq, and Repid, with code examples, broker support, async/sync behavior, production tradeoffs and benchmarks.

The main takeaways were:

- When it comes to throughput, it's important to understand your workload type: I/O or CPU bound makes a huge difference

- Asyncio-native frameworks are significantly faster for high-concurrency I/O-bound jobs

- For CPU-bound jobs, the library matters much less once the CPU is saturated

- Production behavior can vary vastly from framework to framework, same as their philosophy. You have to choose what matters more for your use case

I’d be especially interested to hear from people running these in production. How is your experience running one of these or similar frameworks in production? Is there something that I missed?

Small disclosure: Repid is my project. Take that bias for what it is; the goal is still a useful comparison and a healthy discussion.

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LiteLLM Stability Announcement

2026-06-17T18:18:55+00:00

Over the past few months, we’ve heard from users that LiteLLM has had more bugs and regressions than it should. We take that seriously.

So we’re kicking off a dedicated stability sprint with two goals:
- Close 20 reported bugs in core functionality
- Fix the root causes behind bugs in 3 core areas: MCP, Gateway, and UI

If there's a bug on LiteLLM thats been affecting you, please reach out to us on discord!

submitted by /u/WarningOut_OfMinD
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Financial data apis are basically killing hobbyist algo trading

2026-06-17T12:00:06+00:00

honestly trying to build any sort of automated trading script in python right now is just miserable

I spent the last two weeks writing this whole async event-driven backtester using pandas and asyncio. the logic works perfectly on local CSVs, but the second I try to connect to a live data feed? absolute garbage. Yfinance keeps randomly dropping connections and all the decent websocket APIs now want like $150 a month just for basic historical tick data

it just sucks how paywalled the whole quant space has become for solo devs. honestly while my script was erroring out for the 5th time today I ended up just zoning out on a trading game just to actually look at some market movement without dealing with endless JSON parsing errors and rate limits

I refuse to pay institutional prices just to test a crappy moving average crossover bot. if there are any reliable free websockets left for tick data Im all ears, otherwise im just gonna scrap this script and go back to making discord bots tbh. Just incredibly frustrating how greedy the data providers are getting

submitted by /u/Tosh97
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Would typed schemas for pytest-bdd / Gherkin tables be useful?

2026-06-16T21:10:02+00:00

The idea is to make BDD data tables feel a bit like dataclasses/Pydantic models.

Instead of manually parsing this in a step:

Given the following users exist: | name | role | active | | Alice | admin | true | | Bob | user | false |

You could write:

class UserTable(RowTable): name = field("name", required=True) role = field("role", required=True) active: bool = field("active")

Then:

users = UserTable.parse(datatable)

It would handle required fields, type conversion, custom parsers, validation, and better row/column errors. Business logic would still stay in your own step definitions.

For people using pytest-bdd / Gherkin:

Do your tables ever get annoying to parse manually?
Would a schema layer for tables help, or feel like too much abstraction?
Would you want this as a standalone Python package with pytest support?

The more advanced idea is that teams can add their own small table conventions without putting all that parsing logic inside every step definition.

Trying to sanity-check whether this solves a real problem before polishing it further.

submitted by /u/chinmay_3107
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Are there any python modules that automatically generated a requirements.txt, given an entry point?

2026-06-16T05:40:15+00:00

I know things like pipreqs exist, but that's more of an directory scan. If you have a project and you need several requirements.txts (for multiple containers / multiple entrypoints), I haven't found a way to reliably generate that. Please let me know if things like this do exist, because if not I'd really like to make my own module to do this stuff. And if there is something like that, it would really come in handy for me right now.

submitted by /u/JackBlack436
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Honest question — is workflow orchestration still a solved problem in 2026?

2026-06-17T09:35:58+00:00

Hey,

I keep hearing that tools like Airflow and Celery work fine until they don't — and then they really don't.

For those of you managing workflows at scale:

- Is this still a painful space or have things improved?

- What's your current stack and what would you change?

- What does a good solution actually need to do that most tools don't?

Asking because I'm trying to understand the real state of the market — not the marketing version.

Would love honest takes from people in the trenches.

submitted by /u/Heavy-Candidate1002
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Tuesday Daily Thread: Advanced questions

2026-06-16T00:00:04+00:00

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:

Ask Away: Post your advanced Python questions here.
Expert Insights: Get answers from experienced developers.
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 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 for quicker assistance.

Example Questions:

How can you implement a custom memory allocator in Python?
What are the best practices for optimizing Cython code for heavy numerical computations?
How do you set up a multi-threaded architecture using Python's Global Interpreter Lock (GIL)?
Can you explain the intricacies of metaclasses and how they influence object-oriented design in Python?
How would you go about implementing a distributed task queue using Celery and RabbitMQ?
What are some advanced use-cases for Python's decorators?
How can you achieve real-time data streaming in Python with WebSockets?
What are the performance implications of using native Python data structures vs NumPy arrays for large-scale data?
Best practices for securing a Flask (or similar) REST API with OAuth 2.0?
What are the best practices for using Python in a microservices architecture? (..and more generally, should I even use microservices?)

Let's deepen our Python knowledge together. Happy coding! 🌟

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The Elm Architecture in Python?

2026-06-15T15:07:04+00:00

Since I've fallen in love with Rust's `iced` recently, I've been wondering if there's been any implementations of native TEA for Python. As it is with such things, I immediately wanted to jump into making my own wrapper around Tkinter, but I figured it'd be wiser to ask first!

submitted by /u/Robowiko123
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How and why to run modified Python code using the ast module

2026-06-15T12:33:52+00:00

I've written a blog post explaining how to use the ast module to parse Python code into a structure that you can understand precisely, manipulate to your will, and execute. This lets you achieve things that are otherwise difficult or impossible.

I'm using the 'Discussion' flair instead of 'Tutorial' because I want people to read and share their opinions about the last part of the article where I explain why I think metaprogramming like this is a relevant skill, especially in the age of AI. Among other things, I claim that OpenAI acquiring Astral may be more about general purpose agents than coding agents.

I'm planning to do a series of articles about Python metaprogramming, so keen to hear what people think of this post in general.

submitted by /u/alexmojaki
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Is there even chances becoming python dev

2026-06-16T14:20:59+00:00

So I am in position. Where I can't go to free studies, but programming and making automations with python is my passion. And I would like to become a junior. However, everyone kind of demotivates me that even the guys who hold a degree they are not finding the job. So for me there is chances almost near impossible. I will also start working a job in a week, so my time range for learning is even less. If anyone were in this kind of situation and became dev. Please I honestly want to hear your story. I understand this path is very hard.

submitted by /u/Junior-Package4807
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Dealing with warped/tilted phone photos in coordinate-based OMR grading

2026-06-16T05:26:03+00:00

Hey everyone, I'm working on an OMR (Optical Mark Recognition) sheet grading system and ran into a roadblock with phone camera images.

How it currently works:
I maps fixed pixel coordinates from a JSON file as a template to detect and crop the answer bubbles. It works perfectly with clean, flat-scanned PDF/images.

The Issue:
When users upload photos taken from their phones, accuracy drops heavily. The images often have geometric distortions:
- Tilted or rotated angles
- Perspective warp (trapezoid shapes from angled shots)
- Uneven lighting and lens glare

Since the coordinates are fixed, even a tiny shift causes the system to read the wrong areas.

As a beginner in computer vision, what is the best approach to fix this? Should I implement an OpenCV pipeline to detect corners and apply a Perspective Transform to flatten the image first? Or is a coordinate-based system fundamentally flawed for phone photos, meaning I should look into Object Detection (like YOLO) instead?

Would love to hear any advice, keywords, or workflows you'd recommend! Thanks!

submitted by /u/MallRight6067
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Are we happy with SQLAlchemy?

2026-06-15T02:23:37+00:00

I really need the community's opinion on this. I've worked with a lot of ORMs, from Entity Framework to DrizzleORM. SQLAlchemy is the best option we have in the Python ecosystem, but it still sucks compared to ORMs in other ecosystems.

When I was working with Go, I discovered sqlc and loved it. It's great, but not enough to replace a full ORM because of its limitations (no dynamic queries).

For the last five months, I've been building my own equivalent for Python, powered by sqlglot. Unlike sqlc, it has dynamic filters, sorting, and partial updates. It also has a single parameter syntax for all supported dialects (:param), which are Postgres, MySQL, SQLite, DuckDB, and ClickHouse. I borrowed sqlc's end-to-end test cases, and my version passes all of them now.

It has already replaced SQLAlchemy for me in several microservices. So I guess my question is: is it worth continuing to build it? Because I don’t really know if other Python devs need such tool.

I've had a lot of fun building the current version, and I have a long roadmap ahead. That includes migrations (with auto-generation when possible), generators for other languages, and much more.

submitted by /u/sheadipeets5
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Monday Daily Thread: Project ideas!

2026-06-15T00:00:06+00:00

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:

Suggest a Project: Comment your project idea—be it beginner-friendly or advanced.
Build & Share: If you complete a project, reply to the original comment, share your experience, and attach your source code.
Explore: Looking for ideas? Check out Al Sweigart's "The Big Book of Small Python Projects" 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

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

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

Let's help each other grow. Happy coding! 🌟

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

2026-06-14T00:00:13+00:00

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! 🌟

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TY is still not professionally good

2026-06-14T14:37:27+00:00

I love ty server for python. For those who font know what ty is, it's a language server for python made by ASTRAL.sh, creators of UV and ruff.

The one thing i love the most is type hints kike in rust, so if a function has type annotations, uts return type is automatically labelled as that type.

But it's still not mature. For one, if a python string represents a module, like configuring installed apps or views in django, we dont get any feature to click on it and go to the module.

submitted by /u/flying_dutchman00
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System and game performance monitoring with Python

2026-06-13T10:04:37+00:00

It's rather easy to gather basic system performance metrics and info. Still, with game performance metrics like FPS, Python has to use existing specialized apps and parse their output or read their shared memory.

Tutorial link: https://rkblog.dev/posts/pc-performance/performance-monitoring-with-python/

submitted by /u/riklaunim
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Saturday Daily Thread: Resource Request and Sharing! Daily Thread

2026-06-13T00:00:11+00:00

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:

Request: Can't find a resource on a particular topic? Ask here!
Share: Found something useful? Share it with the community.
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:

Book: "Fluent Python" - Great for understanding Pythonic idioms.
Video: Python Data Structures - Excellent overview of Python's built-in data structures.
Article: Understanding Python Decorators - A deep dive into decorators.

Example Requests:

Looking for: Video tutorials on web scraping with Python.
Need: Book recommendations for Python machine learning.

Share the knowledge, enrich the community. Happy learning! 🌟

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I scaled my local async rate limiter for distributed PowerBI ingestion and everything broke.

2026-06-13T12:58:34+00:00

A while back, I built a lightweight, in-memory asyncio rate limiter. It was perfect for standard single-node Python scripts where I just needed to prevent a local loop from spamming an API.

But recently, the requirements scaled up. I was building a background monitoring pipeline deployed across multiple Kubernetes pods. The pipeline does two things:

Ingests heavy project metrics from PowerBI APIs.
Shoots that data downstream to an LLM to generate automated insights and warnings.

I dropped my trusty local rate limiter into the cluster, expecting it to just work. The moment the K8s pods woke up and triggered their asyncio.gather() loops, they fired concurrent requests in the exact same millisecond. PowerBI instantly panicked, slapped me with 429s, and dropped connections.

Local in-memory queues obviously don't sync across pods. When I tried to implement a standard Redis-backed "Leaky Bucket" with active background queues to fix it, it caused nasty lock contention and race conditions across the cluster under heavy load.

So, I ended up rewriting and extending the library into a distributed traffic-shaping engine called Throttlekit.

I realized this pipeline actually needed two completely different algorithms to handle the upstream and downstream bottlenecks:

For PowerBI Ingestion (Strict Pacing): I used GCRA (Generic Cell Rate Algorithm) for the Leaky Bucket. PowerBI is brittle and hates bursts. GCRA uses stateless timestamp math instead of a background queue. If 20 concurrent pods hit it, it calculates the exact millisecond each one is allowed to fire and spaces them out perfectly (e.g., 1 call every 200ms). It syncs via a single atomic Redis check.
For LLM Insights (Bursty Quotas): I kept the standard Token Bucket. When the data finally trickles through from PowerBI, the pods need answers now. The Token Bucket allows the distributed pods to instantly consume a massive burst of concurrent LLM calls, leveraging the full capacity of our API tier without artificial pacing, right up until the minute's quota is exhausted.

Because of how it evolved, the API is designed to let you seamlessly transition from local testing to distributed production. Here is what the dual-gate architecture looks like in code (stripped down to the core logic for the sake of the post!):

import asyncio import redis.asyncio as aioredis from throttlekit import ( DistributedLeakyBucket, DistributedTokenBucket, RedisBackend ) redis_client = aioredis.from_url("redis://redis-cluster:6379") backend = RedisBackend(redis_client) powerbi_limiter = DistributedLeakyBucket( backend=backend, rate=5.0, max_queue_size=100, name="powerbi_ingestion" ) llm_limiter = DistributedTokenBucket( backend=backend, max_tokens=50, refill_interval=60.0, name="llm_agents" ) @powerbi_limiter.limit(key="shared_tenant", block=True) async def fetch_powerbi_data(project_id: str) -> str: await asyncio.sleep(0.1) return f"raw_data_{project_id}" @llm_limiter.limit(key="shared_llm_quota", block=True) async def generate_warning(data: str) -> str: # Pods can execute these in massive simultaneous bursts when tokens are available await asyncio.sleep(0.2) return "warning_insight" async def process_project(project_id: str): data = await fetch_powerbi_data(project_id) insight = await generate_warning(data) print(f"Processed {project_id}: {insight}") async def main(): async with asyncio.TaskGroup() as tg: for i in range(20): tg.create_task(process_project(f"proj_{i}")) if __name__ == "__main__": asyncio.run(main())

I also built in complete FastAPI integration (Depends injection and Middleware) if you happen to need this to protect incoming web endpoints instead of outbound workers.

I'm curious about how you guys are handling outbound rate limits across K8s right now. Are you just using heavy message brokers like Celery/RabbitMQ to manage ingestion pacing, or have you found lighter ways to enforce cross-pod API limits?

submitted by /u/roudra
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Friday Daily Thread: r/Python Meta and Free-Talk Fridays

2026-06-12T00:00:22+00:00

Weekly Thread: Meta Discussions and Free Talk Friday 🎙️

Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!

How it Works:

Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.

Guidelines:

All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.

Example Topics:

New Python Release: What do you think about the new features in Python 3.11?
Community Events: Any Python meetups or webinars coming up?
Learning Resources: Found a great Python tutorial? Share it here!
Job Market: How has Python impacted your career?
Hot Takes: Got a controversial Python opinion? Let's hear it!
Community Ideas: Something you'd like to see us do? tell us.

Let's keep the conversation going. Happy discussing! 🌟

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Thursday Daily Thread: Python Careers, Courses, and Furthering Education!

2026-06-11T00:00:05+00:00

Weekly Thread: Professional Use, Jobs, and Education 🏢

How it Works:

Career Talk: Discuss using Python in your job, or the job market for Python roles.
Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
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:

Career Paths: What kinds of roles are out there for Python developers?
Certifications: Are Python certifications worth it?
Course Recommendations: Any good advanced Python courses to recommend?
Workplace Tools: What Python libraries are indispensable in your professional work?
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! 🌟

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What's your approach for breaking changes inside minor version upgrades of your dependencies

2026-06-10T15:51:03+00:00

For example, FastAPI introduced a breaking change in a minor version upgrade. By default, it started rejecting requests without a Content-Type header. With only the major version pinned, uv lock --upgrade upgrades to the latest version. A similar thing has happened with google-auth-oauthlib. And that's what bit us.

In our case, everything was fine after the upgrade according to the end-to-end test suite, since most modern HTTP clients add the Content-Type header by default. The issue arose when calls were made using some older Java versions. The customer didn't explicitly add the header, so calls were rejected once their cron had started.

Since reading every release note for every dependency is a very dull and time-consuming task, we wrote a Python script that downloads all release notes and added a Claude command to read them, update dependency versions, and update code as required by breaking changes, while keeping the existing state. So far, it's working great.

Anyhow, curious to hear how others are dealing with these things? I assume you're not reading every release note for every dependency?

submitted by /u/JanGiacomelli
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Tuesday Daily Thread: Advanced questions

2026-06-09T00:00:05+00:00

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:

Ask Away: Post your advanced Python questions here.
Expert Insights: Get answers from experienced developers.
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 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 for quicker assistance.

Example Questions:

How can you implement a custom memory allocator in Python?
What are the best practices for optimizing Cython code for heavy numerical computations?
How do you set up a multi-threaded architecture using Python's Global Interpreter Lock (GIL)?
Can you explain the intricacies of metaclasses and how they influence object-oriented design in Python?
How would you go about implementing a distributed task queue using Celery and RabbitMQ?
What are some advanced use-cases for Python's decorators?
How can you achieve real-time data streaming in Python with WebSockets?
What are the performance implications of using native Python data structures vs NumPy arrays for large-scale data?
Best practices for securing a Flask (or similar) REST API with OAuth 2.0?
What are the best practices for using Python in a microservices architecture? (..and more generally, should I even use microservices?)

Let's deepen our Python knowledge together. Happy coding! 🌟

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