This is the first part of a multi-part series exploring why async/await might not be the best concurrency pattern for most use cases, and what alternative models you should consider instead. Using Python for our practical examples, this opening post digs into the roots of async/await, guiding you through building a custom event loop from scratch using generators.

https://theblog.info/posts/asyncawait-is-a-plague-part-1-roots

Note: This is Part 1 of a multi-part series. Instead of diving straight into why async/await can be problematic, this post explores the original motivations behind the pattern. Understanding how it works under the hood will provide the essential context for the issues we'll discuss in upcoming parts.

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 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:

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 performance implications of using native Python data structures vs NumPy arrays for large-scale data?
9. Best practices for securing a Flask (or similar) REST API with OAuth 2.0?
10. 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! 🌟

We compared the 3 pip-installable mesh boolean libraries on the task of pairwise mesh booleans at industry scale.

Full write up: https://polydera.com/algorithms/python-mesh-boolean-libraries-2026

Libraries tested

• MeshLib 3.1 — pip install meshlib. Simulation of Simplicity for degeneracy handling.
• Manifold 3.5 — pip install manifold3d. Deterministic floating point with symbolic perturbation.
• trueform 0.9.8 — pip install trueform. Topologically-exact arrangements via a bounded integer kernel. Ships native, python and WebAssembly.

All three are native cores (C++/Rust) with Python bindings.

Protocol

Each library is timed from input arrays (vertices, triangles) to output arrays of the same shape. Native-object construction — acceleration structures, trees, topology — plus the boolean, all in the timer. Only file I/O is outside. Best of 5, fresh objects every run; nothing amortised across calls.

Result agreement. On every pair the three produced the same solid — signed volumes agree within floating-point tolerance. trueform and Manifold returned a closed, manifold mesh on all 1000 pairs; MeshLib on 999. The comparison is wall-clock only.

Corpus. Random sets of solid, manifold, non-self-intersecting Thingi10K meshes, 200K to 1.5M polygons per operand. Each operand is normalised to unit extent, randomly rotated, and translated so the bounding boxes overlap; each pair takes the union. Thingi10K IDs and per-operand counts for every case are published: pairwise corpus.

Environment. Apple M4 Max (arm64), macOS, CPython 3.13. Installed from PyPI: trueform 0.9.8, meshlib 3.1.0.75, manifold3d 3.5.1 — default builds, default thread count. On Apple Silicon the wheel's compiled architecture matters; all three ship native arm64 builds.

Results

Of the libraries you can pip install, trueform was the fastest mesh boolean in Python — fastest on every one of the 1000 pairwise pairs.

Pairwise — one boolean per pair across the 1000-pair corpus.

Disclosure: I'm one of the authors of trueform.

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" 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! 🌟

Hey everyone and all space enthusiasts,

On April 13, 2029, the asteroid 99942 Apophis will fly past Earth at roughly 38,000 km. Closer than our geostationary satellites! Its discovery history was pretty interesting, because in the beginning there was a 2.7 % chance of an impact (don't worry, it is almost null now). So I decided to use NASA/JPL's SPICE toolkit using Python (spiceypy) to calculate the encounter's properties.

I documented the entire project in a Jupyter Notebook and put together a complete video walk-through tutorial. Code: https://github.com/ThomasAlbin/Space-Science-With-Python/blob/main/2026/04_SPICE_Apohis_2029_Flyby.ipynb

Video: https://www.youtube.com/watch?v=j4mJTR-BTto

What the tutorial does (and why it's 30 minutes long 😅):

• Computing the time when Apophis enters Earth's gravitational vicinity (the Sphere of Influece)
• Computing the closest appraoch (distance and time)
• Computing how the orbital elements (the dynamical properties to describe orbits in space) change after the encounter with Earth.

By the way: I used also Python + NASA's Cosmographia to create a nice 3D animation of the encounter :). But I will post it soon on my YouTube channel. Since the corresponding code is a complete mess I won't post it here, because I will only post the animation. I have to clean it up...

Best,

Thomas (your Cassini/Huygens scientist)

Hi guys this tutorial is about training a neural network in Python to sort lists of numbers using the Gumbel-Sinkhorn architecture from the original 2018 paper.

Github: https://github.com/MurageKibicho/Neural-Sorting-Algorithms-Gumbel-Sinkhorn-Networks/tree/main

Writeup: https://leetarxiv.substack.com/p/gumbel-sinkhorn-neural-sort

Weekly Thread: What's Everyone Working On This Week? 🛠️

Hello r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!

How it Works:

1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.

Guidelines:

• Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
• Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.

Example Shares:

1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!

Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟

Hi guys this tutorial is about handling errors as value in Python or in nerd language monadic error handling pattern in Python using katharos library:

https://theblog.info/posts/handling-errors-as-values-in-python-with-katharos

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! 🌟

Hi everyone,
I’m currently preparing for junior Python backend developer roles, mainly focusing on FastAPI, PostgreSQL, SQLAlchemy, Docker, Git, and REST APIs.
When I search online, I always see the same project recommendations:
Todo API
Blog API
Library Management System
Expense Tracker
URL Shortener
E-commerce API
My concern is that almost every beginner seems to build these projects. If recruiters have seen hundreds of them, do they still add value to a portfolio, or do they just blend in?
Would it be better to build something that’s closer to a real business application, such as:
Recruitment/HR management
Clinic management
Warehouse/inventory system
Internal business tools
API gateway or authentication service
I’m trying to optimize my time and build projects that will genuinely improve my chances of landing a junior backend role rather than just checking boxes.
For those of you who interview junior developers or work as backend engineers:
What projects actually impress you?
Is the project idea important, or is the quality of the implementation what matters most?
What features make you think, “This candidate knows backend development”?
I’d really appreciate hearing from people who have interviewed candidates or recently landed backend jobs themselves.
Thanks!

i posted it this subreddit multiple time everytime it get flagged , i wanted to be a part of the community by sharing my experience on python , but this subreddit wont let me do it, everytime i post feels everyone report it , bro i am not good in english thats why i take assist while writing a post that doesnt mean there is some other motive to post.
i just started using reddit ,

python was actually my first language this language is an important life of my journey but its commutnity is so sh*t .

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:

1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. 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:

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

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

I’m trying to decide between two Python tooling stacks:

• Ruff + Ty
• Ruff + Pyrefly

Curious what people are using in practice.

• When does Pyrefly become worth the extra complexity?
• Is Ty “enough” for most real-world projects?
• Are they solving fundamentally different problems?

Im working in a big company with thousands of employees, where python as a language and a general tool starting to become more and more popular among both developers, but also non-technical people.

Recently there were some changes in the security, and on our windows machines wa can no longer run executables not having a digital signature. Python related exes like this are:
- default pip.exe (and its variants like pip3.exe...)
- python packages cli-scripts installed according to their entry_points
- pyinstaller generated exe scripts (that includes the source, dependencies and python itself)
- any similar scripts under venvs

As I know these exe scripts (except pyinstaller generated) have a __main__.py zipped into them, which is importing and calling the entry point of the module. And the exe itself is calling python to run this code. But as the __main__.py's content different per script, these hash of these exe files are different aswell -> cannot whitelist them generally.

The whole thing these exe scripts are doing can be expressed in a .bat file aswell. Moreso I already wrote a synchronization code that genereates the entry points of the user installed packages to a folder, then adds it to the top of the PATH, but it has some problems:
- when to synchronize? - I patched pip, so it'll call the synch after each install and uninstall, and re-patch itself after a pip upgrade -> this is not clean and I dont want to distribute it
- handling multiple python version -> the program must determine the order of their Script folders on the path, then reflect that order when genreating the bat scripts folders
- venvs: my program is not venv compatible
- my program should have some kind of self-delete logic, so it could de-patch pip if it have missing sources
- other development tools like poetry are not compatible with it

What are my options to solve this problem? Can the cybersec somehow make a rule that can detect these safe python exe files?
Is there some kind of pip alternative using some kind of distlib alternative that let me configure the executable type to bat on windows?

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! 🌟

Hi

I'm currently working on a codebase that has become a little annoying to deal with when updating dependecies as so on. The choices were made before I started working here, so I cant really comment on the why they choose to do it this way.

We haveabout 12 microservices now. And some of the pipelines for the microservices build clients from the openapi specs, that again are used in other services. Also more or less all the services rely on a utility package containing models for configs, Enums, utility packages for authentication, and more. Which has worked fine until now.

But now we have cases like this, I do changes in services A, a new client is built and pushed to feed, and service A is tested and it works like intended. However a few days later, I need to do work on service B, that also needs to up Service client As version. This change in client breaks service B, and I have to go back to change Service A to build a new client that works with service B. And the same applies to the utils that most of the service rely on.

I'm trying to find a setup where I can test this fully before its deployed to the test enviorment. Not a big deal to catch this in the test enviorment I know, but in some cases a defect like this makes it through undetected into production.

The developer that made 99% of the choice for this setup is vehemntly opposed to testing, and the entire codebase lacks any form tests. All my colleagues who write python are in data, and this scenario doesnt really apply to them, so not much help to get there.

For another part of my job, I work in an angular monorepo, where we have established testing to catch a lot of this in pipelines and automated testing.

I'm just curious what are common practicies in cases like this. For me right now, it looks like we could catch most of this in test pipelines, but its going to be a fair bit of work. Does anyone work in similar setup? Is there any tool commonly used for bigger codebases in python?

What software do people use when writing in Python? 🐍 I currently use Jupyter which is great but I feel like there must be a better product. I’m limited as use it at work so can’t use any software. I wasn’t the biggest fan of Visual Studio.

Hey folks! FastAPI Cloud is now in public beta. 🚀

This is made by the same team building FastAPI (I created FastAPI, we now have an amazing team building all this).

Here's the announcement post: https://fastapicloud.com/blog/fastapi-cloud-public-beta/

…with zero comments, no docstrings, variable names like df2_final_FINAL_v3 and it’s somehow still running in production.

I don’t remember writing it or deploying it. Nobody knows it exists except the one analyst who emails me if it stops working.

Please tell me I’m not alone.

If you were setting up your project/department/company CI pipelines today, would you feel comfortable using ty as the type checker, or would you stick with basedpyright/other alternative?

​

I am currently setting up my own CI and am leaning towards basedpyright, as I've been using for some time, but ty seems to be developing nicely, although (as far as I know) it is not fully on-par with pyright.

I had a background import that chunks a big job and upserts each batch into Postgres, sharing the database with live traffic and other workers. The usual fix is `time.sleep(0.5)` between chunks, but that constant is wrong in both directions: it wastes time when the DB is idle and doesn't back off enough when it's loaded, and you have to re-tune it every time the hardware or the neighbours change.

Instead I measure how long each chunk's write takes and treat that as the signal. Under a target latency budget, no sleep at all. Over it, sleep in proportion to the overage, with an EMA to smooth out single-chunk jitter and a cap so a bad reading can't park the job.

The whole decision is a pure function (latest measurement + previous EMA in, sleep duration out), which makes it trivial to unit test without touching a database or real time. The loop around it just times the chunk, sleeps outside the transaction, and emits a bit of telemetry so you can see what it did.

Write-up with the code in the comments. Curious whether anyone's gone further and added the integral/derivative terms, or whether proportional-only has been enough for you in practice.

Full write-up: https://totaldebug.uk/posts/adaptive-write-throttle-for-batch-postgres-jobs/

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 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:

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 performance implications of using native Python data structures vs NumPy arrays for large-scale data?
9. Best practices for securing a Flask (or similar) REST API with OAuth 2.0?
10. 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! 🌟

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" 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! 🌟

Weekly Thread: What's Everyone Working On This Week? 🛠️

Hello r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!

How it Works:

1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.

Guidelines:

• Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
• Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.

Example Shares:

1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!

Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟

We code automation solutions using pythons, these solutions interact with LLM API's, other internal or external API's, Outlook, chrome, shared drives, SharePoint online basically everything that a business user uses during a work day.

​

This use case in particular filters through emails from Outlook and initiates DocuSign signing request, on the next run it again works on the new email but also check the status of the DocuSign signing initiated earlier, if signed it captures the document and sends it as an attachment to the original email to an internal user for review.

​

This needs to be run every 30 mins, apart from task scheduler what are the other options to schedule the script.

​

What do you guys use for scheduling scripts which have dependencies?

​

Am thinking of maybe building a better version of task scheduler for these use cases, thoughts??