Introducing Monty Python Interpreter for Agents

Give your agent access to a high-speed, secure Python interpreter as an MCP tool. This is far more secure than having the agent use the system Python, and far faster than spinning a Docker to run the agent's code securely. Give it a whirl! Thanks to Pydantic for creating Monty, and buyer beware - Monty is still experimental...

Did this project using python, what it does is quite interesting. Imagine sorting out or doing some operations on excel sheet one by one, when you have hundreds of lines of rows. This code access your python sheet using "openpyxl" You can access any row or create new row or column, set the limits of rows and columns. This is a very interesting, challenging and amazing project to do. Btw i have shared the project on my Github so anyone can see or use it. LINK: https://lnkd.in/dkQRkicf

I kept hearing about FastAPI everywhere in the Python ecosystem, so I decided to explore it and document what I learned. I wrote a short blog covering: • What is FastAPI? • How it compares with Django REST Framework • Core components like Starlette and Pydantic • Dependency Injection in FastAPI • Building a simple CRUD API step-by-step If you're a Python developer curious about FastAPI, this might be a helpful starting point. Blog post: https://lnkd.in/gr86BXDK Feedback is welcome 🙂

Typescript: start_date = historyStartDate.toISOString() Is not recongnized by Python's datetime.fromisoformat(start_date) ---- The issue is that TypeScript's toISOString() appends a "Z" (for Zulu/UTC), but Python's datetime.fromisoformat()—specifically in versions older than 3.11—is notoriously strict and doesn't recognize "Z" as a valid suffix for UTC. ----

One thing I’ve learned while working with Python recently really stood out to me 👇🏾 In Python, capitalization matters a lot. If you define something in uppercase and later try to use it in lowercase, you’ll likely run into an error. But in HTML (and sometimes even in React), things are more flexible—especially with tags, where capitalization doesn’t usually break your code. This made me realize how important it is to pay attention to detail depending on the language you're using. Every technology has its own rules, and understanding them makes you a better developer. Small lessons like this are part of the journey 🚀 #Python #React #HTML #WebDevelopment #LearningJourney #100DaysOfCode

🐍📺 In this video course, you'll build an app to create and manage shortened URLs. Your Python URL shortener can receive a full target URL and return a shortened URL. You'll also use the documentation of FastAPI to try out your API endpoints. #python

🚀 Just Built My First API Integration Project in Python! Today I worked on integrating a live Quotes API using Python and the requests library. GITHUB Repo Link:- https://lnkd.in/gdx-b94v The project fetches random motivational quotes from an online API and displays them in real-time. 💡 Key learnings from this project: How to work with APIs and endpoints Handling JSON responses in Python Using response.raise_for_status() for error handling Writing clean exception handling with try-except Saving API data into a file with timestamps 📌 Built Features: Fetch random quotes from API Display quote & author in terminal Save quotes in a text file for future use This small project helped me understand how real-world applications communicate with external services. Next step: Building a GUI-based Quote Generator App 🚀 #Python #APIs #BeginnerProjects #CodingJourney #100DaysOfCode #Developers #LearningByDoing

I recently conducted a performance test comparing Node.js, Python, and Rust under the same workload conditions and the results were eye-opening. Key insights: Rust delivered the highest performance and efficiency, thanks to its compiled nature and low-level control Node.js performed well, especially in handling asynchronous workloads Python, while excellent for rapid development, showed clear limitations under heavier load https://lnkd.in/ePsUDZBF

Turning an n8n workflow into a Python script and running it on GitHub for free is easier than you might think. Here’s a simple way to do it, especially if you want to run scheduled workflows. First, download your n8n workflow as a JSON file. Next, upload that file to Claude and ask it to convert the workflow into a Python script. Once you have the script, create a new GitHub repository and add the Python file. Move any API keys or sensitive information into GitHub Secrets to keep them secure. Then, ask Claude to guide you through setting up a GitHub Actions workflow that will run your script on a schedule. That’s it. Now your workflow runs for free on GitHub, without needing to keep n8n running.

So I wrote a small guide on Python's Lambda functions, where I have discussed it's use cases, why to use it etc. Originally it was just for my notes as I often tend to forget the syntax, specially while pairing it with higher order functions. I am sharing just in case it will be helpful to you guys too and can become your go to guide. Link to blog in comments.