Built a tool that converts any REST API spec into an MCP server

I have been experimenting with Anthropic’s Model Context Protocol (MCP) and hit a wall — converting large REST API specs into tool definitions takes forever. Writing them manually is repetitive, error-prone and honestly pretty boring.

So I wrote a Python library that automates the whole thing.

The tool is called **rest-to-mcp-adapter**. You give it an OpenAPI/Swagger spec and it generates:

* a full MCP Tool Registry
* auth handling (API keys, headers, parameters, etc.)
* runtime execution for requests
* an MCP server you can plug directly into Claude Desktop
* all tool functions mapped from the spec automatically

I tested it with the full Binance API. Claude Desktop can generate buy signals, fetch prices, build dashboards, etc, entirely through the generated tools — no manual definitions.

If you are working with agents or playing with MCP this might save you a lot of time. Feedback, issues and PRs are welcome.

**GitHub:**
Adapter Library: [https://github.com/pawneetdev/rest-to-mcp-adapter](https://github.com/pawneetdev/rest-to-mcp-adapter)
Binance Example: [https://github.com/pawneetdev/binance-mcp](https://github.com/pawneetdev/binance-mcp)

/r/Python
https://redd.it/1p7x3i8

Django Playground in the browser.

A fully working Django playground in the browser.
It is a proof of concept. I was able to run migrations and create a superuser locally. Now it's a question of making everything work.
https://django.farhana.li/

https://github.com/FarhanAliRaza/django-repl

/r/djangolearning
https://redd.it/1p86zo0

Django roadmap

Hi! For past few months I've been learning web development and I have learned html, css, js,python and sql so far. Although I don't have mastery over these topics but I have mid-level understanding over all of them. Recently I have started Django and out of the box it's started to feel overwhelming. I don't know what my roadmap should be for django. (I have tried ai generated roadmap for django but it still feels overwhelming). Many of you guys maybe already work with django in the web development field i was hoping i could get some advice from you guys maybe a roadmap as well and also Am i the only one who is overwhelmed with django or is this a common phenomenon for beginners? Thanks in advance.

Note: I didn't have any prior knowledge of programming before starting the journey.

/r/django
https://redd.it/1p84d08

Hatch v1.16.0 - workspaces, dependency groups and SBOMs

We are happy to announce version 1.16.0 of Hatch. This release wouldn’t have been possible without Cary, our new co-maintainer. He picked up my unfinished workspaces branch and made it production-ready, added SBOM support to Hatchling, and landed a bunch of PRs from contributors!

My motivation took a big hit last year, in large part due to improper use of social media: I simply didn’t realize that continued mass evangelism is required nowadays. This led to some of our novel features being attributed to other tools when in fact Hatch was months ahead. I’m sorry to say that this greatly discouraged me and I let it affect maintenance. I tried to come back on several occasions but could only make incremental progress on the workspaces branch because I had to relearn the code each time. I’ve been having to make all recent releases from a branch based on an old commit because there were many prerequisite changes that were merged and couldn’t be released as is.

No more of that! Development will be much more rapid now, even better than the way it used to be. We are very excited for upcoming features :-)

/r/Python
https://redd.it/1p898zg

Python Podcasts & Conference Talks (week 48, 2025)

Hi r/Python! Welcome to another post in this series brought to you by Tech Talks Weekly. Below, you'll find all the Python conference talks and podcasts published in the last 7 days:

# 📺 Conference talks

# PyData Berlin 2025

1. **"Narwhals: enabling universal dataframe support"** ⸱ +584 views ⸱ 23 Nov 2025 ⸱ 00h 47m 01s
2. **"Docling: Get your documents ready for gen AI"** ⸱ +524 views ⸱ 23 Nov 2025 ⸱ 00h 32m 22s
3. **"Scaling Probabilistic Models with Variational Inference"** ⸱ +418 views ⸱ 23 Nov 2025 ⸱ 00h 29m 19s
4. **"A Beginner's Guide to State Space Modeling"** ⸱ +388 views ⸱ 23 Nov 2025 ⸱ 01h 31m 08s
5. **"Building Reactive Data Apps with Shinylive and WebAssembly"** ⸱ +232 views ⸱ 23 Nov 2025 ⸱ 00h 32m 29s
6. **"More than DataFrames: Data Pipelines with the Swiss Army Knife DuckDB"** ⸱ +213 views ⸱ 23 Nov 2025 ⸱ 01h 28m 06s
7. **"Exploring Millions of High-dimensional Datapoints in the Browser for Early Drug Discovery"** ⸱ +212 views ⸱ 23 Nov 2025 ⸱ 00h 27m 39s
8. **"Spot the difference: 🕵️ using foundation models to monitor for change with satellite imagery 🛰️"** ⸱ +207 views ⸱ 23 Nov 2025 ⸱ 00h 31m 42s
9. **"Consumer Choice Models with PyMC Marketing"** ⸱ +202 views ⸱ 23 Nov 2025 ⸱ 00h 27m 46s
10. **"Lightning Talks"** ⸱ +198 views ⸱ 23 Nov 2025 ⸱ 00h 39m 04s
11. **"When Postgres

/r/Python
[https://redd.it/1p8ad8c

[D] Got burned by an Apple ICLR paper — it was withdrawn after my Public Comment.

So here’s what happened. Earlier this month, a colleague shared an Apple paper on arXiv with me — it was also under review for ICLR 2026. The benchmark they proposed was perfectly aligned with a project we’re working on.

I got excited after reading it. I immediately stopped my current tasks and started adapting our model to their benchmark. Pulled a whole weekend crunch session to finish the integration… only to find our model scoring absurdly low.

I was really frustrated. I spent days debugging, checking everything — maybe I used it wrong, maybe there was a hidden bug. During this process, I actually found a critical bug in their official code:

* When querying the VLM, it only passed in the image path string, not the image content itself.

The most ridiculous part? After I fixed their bug, the model's scores got even lower!

The results were so counterintuitive that I felt forced to do deeper validation. After multiple checks, the conclusion held: fixing the bug actually made the scores worse.

At this point I decided to manually inspect the data. I sampled the first 20 questions our model got wrong, and I was shocked:

* **6 out of 20 had clear GT errors.**
* The pattern

/r/MachineLearning
https://redd.it/1p82cto

2026 DSF Board Election Results
https://www.djangoproject.com/weblog/2025/nov/28/2026-dsf-board-election-results/

/r/django
https://redd.it/1p8obal

Friday Daily Thread: r/Python Meta and Free-Talk Fridays

# 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! 🌟

/r/Python
https://redd.it/1p8gniu

I built a tool that automatically cleans unused dependencies from Python projects.

I built a tool that automatically cleans unused dependencies from Python projects. It's called Depcleaner and you can easily get started by reading it's PYPI or Github page!
https://pypi.org/project/depcleaner/

/r/Python
https://redd.it/1p8muey

Should I continue learning Django?

Two years ago, I started learning django and I had the very basic understanding. But then, I stopped learning and never done any coding activities untill now. Currently, I decided to start again. But most of my friends told me instead of django to learn Next.js. They said it is so easy and full-stack compared to django. But I didn't wanted to start JS from 0. I wanted to continue django because I have basic python knowledge. Since I don't have any deep idea on both of them, please guys explain to me, can I do react.js and other front-ends in django easily and other pros and cons in the two frameworks. I know the question is stupid, but try to give me your best. Am going to post it in both Django and Next sub reddits.

/r/django
https://redd.it/1p8ufiq

I built a deterministic engine to analyze 8th-century Arabic Poetry meters (Arud) with Python

Hi everyone,

I’ve just released PyArud v0.1.3, a Python library that digitizes the science of Arabic Prosody (ilm al-Arudh), originally founded by Al-Khalil bin Ahmed in the 8th century.

What My Project Does

Arabic poetry is built on a binary system of "Moving" (Mutaharrik) and "Still" (Sakin) sounds, forming 16 distinct meters (Buhur). Analyzing this computationally is hard because:

1. Orthography vs. Phonetics: What is written isn't what is pronounced (e.g., "Allahu" has a hidden long vowel).
2. Complexity: A single meter like Kamil has dozens of valid variations (Zihaf) where letters can be dropped or quieted.
3. LLMs struggle: Asking ChatGPT to scan a poem usually results in hallucinations because it predicts tokens rather than strictly following the prosodic rules.

The Solution: PyArud

I built a deterministic engine that:

* Converts Text: Uses regex and lookaheads to handle deep phonetic rules (like Iltiqa al-Sakinayn \- the meeting of two stills).

* Greedy Matching: Implements a greedy algorithm to segment verses into their component feet (Tafilas).

* Deep Analysis: Identifies not just the meter, but the specific defect (Ellah) used in every foot.

Example

from pyarud.processor import ArudhProcessor


# A verse from

/r/Python
https://redd.it/1p8t4a8

Topics you want to hear on Talk Python To Me

Hey Talk Python podcast fans! I'm looking to book a bunch of topics / guests / episode for 2026. Do you have recommendations on what you'd like to hear about?


Haven't heard of Talk Python To Me is? It's a Python podcast at https://talkpython.fm

/r/Python
https://redd.it/1p8ziy3

pmp - a tool to manage your prompts locally

Hey Everyone!

I've been working with LLMs a lot lately and got tired of managing prompts in random text files and copy-pasting them around. So I built pmp \- a simple cli tool for managing prompts with versioning and pluggable storage backends.

https://github.com/julio-mcdulio/pmp

There are quite a few products out there like mlflow and langfuse, but they come with a lot of bells and whistles and have complex deployments with a web frontend. I just wanted something simple and lightweight with no dependencies.

$ pmp add code-reviewer --content "Review this code for bugs and improvements" --tag "code,review" --model "gpt-4"
prompt "code-reviewer" version 1 created

$ pmp get code-reviewer
Review this code for bugs and improvements

$ pmp update code-reviewer --content "Review this code thoroughly for bugs, security issues, and improvements"
prompt "code-reviewer" version 2 created

$ pmp list --tag code
code-reviewer
summarize

I've also added support for an optional dotprompt storage backend, and I'm planning to add support for

/r/Python
https://redd.it/1p97p3h

Best practices 2025?

Soon setting up Django at a VPS mostly for learning (again). Excluding containers what's a current stack? Debian, Nginx, Gunicorn, PostgreSQL, UV venv, Let's encrypt, Cloudflare, memcached/redis, RabbitMQ, HTMX, cookiecutter...?

/r/django
https://redd.it/1p943xi

Struggling to find the right Django docs for building better apps

I started learning Django from the official tutorial and built a few small projects.

Now I want to make my apps more professional and secure using Django’s built-in features, like extending AbstractUser to create a custom user model.

It took me a long time to find the right sections in the docs and figure out the recommended approach.

When you’re building real-world Django apps, how do you usually figure out the best way to do things, and how do you quickly find the features you need in the docs?

/r/django
https://redd.it/1p94bca

Hi all I'm making my first large scale app and I'm struggling to organize the code!

Right now it's a monolith, I've got everything separated into models->feature->model.py etc. it's ok but it's making development a nightmare when I have to search for the model serializer signal service url view to develop.

I was thinking about separating every feature into Django apps But they all really depend on one another and will require loads of inter app foreign keys, so I was thinking of leaving it in a monolith but separating into app style folders ie. api.feature.models - views - serializers - admin - urls etc. but I was wondering if this would slow down the app as it would all be linked via . Init

/r/django
https://redd.it/1p8siw6

D ICLR 2026 Clarification: Your responses will not go to waste!

You are receiving this email as an author of a submitted paper to ICLR 2026.

We have heard from a few authors who are frustrated by the fact that review scores are being reverted to their pre-discussion state and no further reviewer discussions or public comments are allowed. We understand your frustration. Many of you spent a significant amount of work on your rebuttal and the subsequent ensuing discussion.

We want to clarify that only the review itself ("Official Review") is being reverted: your response and prior discussion with reviewers will remain intact and will be considered by the area chair. In addition, you have the option as an author to post additional comments on the forum. You can use this opportunity to post a summary comment giving any other necessary information to the AC.

The AC's decision-making process:

ACs will have a longer period to write their meta-reviews.
ACs will be explicitly instructed to take your response and the prior discussion into account.
ACs will be asked to estimate how the reviewer's impressions would have changed had the discussion period not been cut short.
We will be recruiting emergency ACs to offload effort from any ACs who tell us the workload is too

/r/MachineLearning
https://redd.it/1p9d661

Saturday Daily Thread: Resource Request and Sharing! Daily Thread

# 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! 🌟

/r/Python
https://redd.it/1p9a5ab

Interview questions for 2-3 yoe Django/DRF developer

Hi!

Could any recruiter or senior Django developer share some interview questions you usually ask or have encountered in your interviews?

Your help and time would be greatly appreciated.

/r/djangolearning
https://redd.it/1p6ltr0

PyPermission: A Python native RBAC authorization library!

Hello everyone at r/python!

At our company, we repeatedly needed to integrate authorization into Python projects and found the ecosystem a bit lacking.

# Comparison With Other Solutions

Django's permission system wasn't enough
Casbin, Keto and OPA offer flexible solutions, but can be hard to integrate
We wanted something Python-native, without a policy DSL and with auditing support

# What My Project Does

Knowing that authorization comes with many pitfalls, we decided to build an RBAC model focussing on an intuitive API and extensive testing. PyPermission is the result and draws on what we learned implementing RBAC across multiple projects (with and without third party solutions).

NIST RBAC Level 2a (supports general role hierarchies)
Framework independent, Free and Open Source
Additional capabilities from the ANSI RBAC model
A simple and tested python API
Persistency via PostgreSQL or Sqlite (SQLAlchemy)

# Target Audience

Developers looking for a simple authz solution without enterprise complexities, but a well established RBAC model.

The core implementation of the library is feature complete and heavily tested (overall test coverage of 97%) and we desire to have everything battle tested now. This is why we are excited to share our project with you and want to hear your feedback!

Repo: [https://github.com/DigonIO/pypermission](https://github.com/DigonIO/pypermission)
Docs: https://pypermission.digon.io/

/r/Python
https://redd.it/1p9ebul

Is anyone else choosing not to use AI for programming?

For the time being, I have chosen not to use generative AI tools for programming, both at work and for hobby projects. I imagine that this puts me in the minority, but I'd love to hear from others who have a similar approach.

These are my main reasons for avoiding AI for the time being:

I imagine that, if I made AI a central component of my workflow, my own ability to write and debug code [might start to fade away](https://lucianonooijen.com/blog/why-i-stopped-using-ai-code-editors/). I think this risk outweighs the possible (but [not guaranteed](https://arxiv.org/pdf/2507.09089)) time-saving benefits of AI.
AI models might inadvertently spit out large copies of copyleft code; thus, if I incorporated these into my programs, I might then need to release the entire program under a similar copyleft license. This would be frustrating for hobby projects and a potential nightmare for professional ones.
I find the experience of writing my own code very fulfilling, and I imagine that using AI might take [some of that fulfillment away](https://colton.dev/blog/curing-your-ai-10x-engineer-imposter-syndrome/#its-okay-to-be-less-productive).
LLMs rely on huge amounts of human-generated code and text in order to produce their output. Thus, even if these tools become ubiquitous, I think there will always be a need (and demand) for programmers

/r/Python
https://redd.it/1p9wluw