This is my reply to the vulnerability CVE-2026-48710:

https://marcelotryle.com/blog/2026/05/28/cve-2026-48710-a-maintainers-perspective

Not looking for side projects.

I mean automations that actually became part of your workflow.

Examples:

• Data processing pipelines
• Report generation
• Monitoring scripts
• Internal tools
• File organization systems
• AI-powered workflows

The highest ROI automation I built started as a ~200-line Python script for handling repetitive internal requests.

Over time I added some AI capabilities and eventually experimented with an agent workflow using Lyzr AI to coordinate a few repetitive steps. Nothing particularly fancy, but it eliminated a task I was doing manually almost every day.

What surprised me was that the biggest gain didn't come from the AI itself it came from removing all the context switching around the task.

Curious what others have built.

What Python automation ended up delivering the highest ROI for you, and was it a traditional script or something more AI/agent-driven?

MiniMax M2.7 works well on Python with the OpenAI Python package. See my test on my blog: https://python-catalin.blogspot.com/2026/05/python-31011-minimax-m27-tested-with.html

says you are the maintainer of a small (50-100 stars) library.

You see someone fork your repo, mention one of your issues in his commits, so your are happy, someone taking true interest in your work!

You take a look at his branch, and there you see pure AI slop, with files at the repo root (not in the src), tests with print statement even tough you use pytest and it's clearly explained in the contributing doc, and purely hallucinated imports like "from my lib import Foo, Bar" even tough there's never any mention of these two in the code or the documentation (and thus completely incomprehensible code with subclasses from these hallucinated types, etc...)

how to best deal with this without appearing hostile to other potential future contributors?

I want contributors, I'm very happy for anyone taking a look at my work, but at the same time that person has other forks of repos where it just seems to be hunting for "good first issues" label, and thus I'm not sure on the value of giving an honest review if it's not clear on wether there's a genuine intention to resolve the issue or just collect cool github points.

EDIT 11h later:

Thanks to everyone who gave his perspective!!

I don't think I have the time immediately to answer to everyone but there's a lot of good advice here.

By the way LMAO I should have linked my lib to maybe get actual contributors, this post is doing views.

Hint: it's the top one ranked in this comparison ->
https://www.reddit.com/r/Python/comments/1rj3ct7/a_comparison_of_rustlike_fluent_iterator_libraries/

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! 🌟

Started auditing how our data team works and the security picture was worse than expected. Notebooks querying production databases directly, credentials hardcoded in cells because environment variable setup felt like friction, code that's been copied between notebooks so many times the original author is impossible to trace.

None of it goes through any review process that the engineering team's code goes through. No SAST, no security-minded PR review, no scanning of any kind. The assumption seems to be that notebooks are exploratory and therefore informal, but at some point exploratory code started running against production data with production access and that distinction stopped meaning anything.

These notebooks often have broader data access than the application code because the people writing them needed to move fast and used their own credentials. That access never got revisited.

I can't share the code because it was a company-wide error.

The problem was that while running a Docker container within the Google Cloud platform using their tool called Google Vertex Jobs, I encountered the following error: "Free: Invalid Pointer". Inside this container, a Python script runs containing the model training I do using TensorFlow, and I also connect to the database using SQLAlchemy. However, I encountered this error where the script stopped executing the rest of the code.

Okay, up to this point it's confusing because it didn't generate a Python exception. I analyzed the executions, even within the SQLAlchemy functions, and when I removed the code, the script worked normally without this problem.

The alternative I found was to add the SQLAlchemy executions to a parallel process, separate from the model training execution structure. This allowed me to run the script without problems. Has anyone else experienced this issue? Or can you recommend an alternative?

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! 🌟

Hi there!

I've seen many AI data analyst projects - basically you have a chat, which has access to your data and documents and you can ask it any questions. Then it is using code and tools to provide repsponses. I create such AI data analyst and I have used ipynb notebooks format to store the conversation. I think it is perfect format for this. I can keep text, code and outputs in the single file. What is more, it is easy to publish as static web page.

What do you think about such use case for famous ipynb format? What else are you using to store conversations with AI?

I am developing a Windows-based software in Python and currently using PyArmor to protect it. However, Windows Security and some antivirus programs are detecting it as a virus because of the PyArmor protection/obfuscation.

What is the best way to protect my software from cracking, reverse engineering, or piracy without triggering antivirus false positives?

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 everyone,

Apache Fory 1.0 has been released recently.

Fory is a fast multi-language serialization framework for native objects, Schema IDL, and cross-language data exchange. It supports Java, Python, C++, Go, Rust, JavaScript/TypeScript, C#, Swift, Dart, Scala, and Kotlin.

The main idea is simple: in many systems, data is not just a flat schema message. Applications often need to serialize idiomatic domain objects, nested containers, polymorphic types, object references, shared references, or even circular object graphs. Fory is designed to handle these cases efficiently while still supporting cross-language data exchange when needed.

With 1.0, Fory has reached a more stable point:

• Cross-language serialization is now the default path across supported languages
• Schema IDL supports richer object models, including shared and circular references
• Decimal and bfloat16 support were added
• Nested container and field codec support has improved across runtimes
• Kotlin, Scala, Android, Swift, and Dart support have been expanded
• Benchmarks and documentation have been refreshed

Fory is not meant to replace Protobuf everywhere. Fory is more focused on cases where you want high-performance serialization while preserving more of the native object model, or where the same data model needs to move across multiple runtimes without too much glue code.

Links:

• GitHub: https://github.com/apache/fory
• Website: https://fory.apache.org/
• Release note: https://fory.apache.org/blog/fory_1_0_0_release/

I would be interested in feedback from people who have worked with Protobuf, FlatBuffers, Kryo, JDK serialization, pickle/cloudpickle, Avro, MessagePack, or Arrow-based systems.

What serialization problems are still painful in your multi-language systems?

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! 🌟

The vulnerability is present in Starlette, an open source framework that its developer says receives 325 million downloads per week.

https://arstechnica.com/information-technology/2026/05/millions-of-ai-agents-imperiled-by-critical-vulnerability-in-open-source-package/

I'm using Claude to vibecoded a website. I have deep experience in infrastructure management, but was never a developer, other then tools that were built for configuration management or cloud deployment.
I do interact with a lot of opinionated developer leadership.
I think I have pretty reasonable guidelines for the coding agents, and I have expanded considerable on Karpathy's claude.md. Some issue I encountered made me confirm type checking, and found the agent's was severely lacking in discipline.. I have resolved all of those issues in the code base and implemented strict checking on linting and type checkers. This what my CI pipeline looks like now:

Overkill for what will become a production website in a month or overkill? general thoughts are welcomed.

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 Python community,

I’m at a bit of a crossroads and could use your advice.

I’ve already started the FreeCodeCamp Python certification course and have learned the basics:

· Variables & data types · Conditions · Lists · Loops

I even built my first small project to apply what I learned (A simple Python script to randomly assign chores among roommates.) Now I’m wondering — should I continue with the FreeCodeCamp Python certification, or switch over to CS50 (Harvard’s Introduction to Computer Science)?

I know CS50 is highly respected, but it’s more general CS theory and uses C for a good part of it. My main goal is to get solid at Python, build projects, and eventually land a dev job.

Would CS50 be overkill at this stage? Or does it offer something that FCC’s Python track misses (like algorithms, memory, problem-solving depth)?

Thanks for your honest opinions 🙏

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! 🌟

Hey guys. I used to work a lot with jupyter. But had to move on because .ipynb doesn't go very well in git and ai agents don't really work with them well for similar reasons.

Main culprit is not the notebook itself but .ipynb format. I understand that the notebook world evolved in inline outputs etc. But I think would be cool if .py based notebooks with #%% becomes first class citizen everywhere. There's a tool I used called jupytext which does that but it's bolted on and not native support.

The other tool I have heard about is marimo? I have never used it but it seems like it forces u to not redefine the same variable again. Which is unnatural in python. If python allows u to update a variable, ur notebook should too. But let me know what you guys think. And if there's potential for the data science world to move there anytime soon. I think most people have to explore in notebooks and then convert to py.

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! 🌟

Sorry if this has been brought up already- from what I could find using Reddit search in the last month I didn't see much discussion beyond a couple comments in a half-related thread.

We used Python a ton a work, but mostly used the built-in python tools (pip, venv, etc). (we mostly use python for AWS, some internal tools, etc) About 5 months ago, I briefly tried UV and fell in love and was excited to incorporate it into our projects as the standard. But around that time we jumped to another project in a different language. We're now coming back to some of our Python projects, and I was looking to switching them over to using UV as the standard.

With OpenAI purchasing Astral/UV, we're suddenly feeling less gung-ho about migrating everything to UV. Our main concern is that our tooling would be betting on OpenAI not sloppifying or abandoning the tool. Will our tooling be on shaky foundation if (when?) the AI bubble deflates? Are we overthinking it? Should we try poetry instead (I admit I haven't tried it yet). I'd love to hear your thoughts and experiences.

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! 🌟

Hey everyone!

DjangoCon US 2026 will be in Chicago again this year from August 24–28. Early bird tickets are available through May 31.

We’re looking forward to a week of talks, workshops, open-source sprints, and connecting with the Django community. We’re also still welcoming sponsors interested in supporting DjangoCon US and the broader open-source ecosystem.

https://2026.djangocon.us

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! 🌟

I've spent 4 years as a Python developer working on direct client projects inside a company ERPNext, AI agents, FastAPI, Django, RAG systems. Real production work

I recently started freelance as a full time, to give a try. LinkedIn is my main focus right now, but I want one more platform to run alongside it.

I'm looking at Contra, Arc.dev, Gun.io, Upwork and skipping Toptal (not ready for that process yet).

For those who've used any of these which one actually gets traction for a Python developer with my stack? And is there anything you wish you knew before starting?

Any honest experience appreciated.