Python Hub Weekly Digest for 2025-10-26
This week in Python, we saw the introduction of new features in Python 3.15, a simple implementation of a neural network from scratch, a beginner's guide to Edge AI, and the completion of the lock file specification for Python. There were also discussions on custom modifications to the Python REPL and building an MCP server with ChatGPT. Interesting projects included a CLI tool for accessing local clipboard from remote systems, a Python type checker in Rust, and a command-line tool for discovering unprotected API endpoints. Wishing you a great week ahead and happy coding!
💖 Most Popular
What’s new in Python 3.15
This article explains the new features in Python 3.15, compared to 3.14.
Neural Networks: Simpler Than You Think
The post presents a straightforward implementation of a neural network from scratch in Python, explaining core concepts such as neurons, layers, weights, biases, activation functions, and training through backpropagation. It demonstrates building and training a simple neural network to approximate a sine wave, highlighting that despite its simplicity, the network can learn complex patter...
EdgeAI for Beginners
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.
Why it took 4 years to get a lock files specification
The lock file specification for Python, finalized in PEP 751, took more than four years to complete because of the complexity of capturing dependencies across platforms and configurations while maintaining security, readability, and compatibility with different tools. The process required balancing diverse ecosystem needs, resolving dependency graphs, and achieving consensus among major ...
Handy Python REPL Modifications
The article describes custom modifications to the Python REPL to make it behave more like a favorite editor, including adding new keyboard shortcuts for code navigation, editing, and inserting example data structures. These changes, enabled through a PYTHONSTARTUP file and packaged in a library called pyrepl-hacks, enhance productivity by allowing quicker code writing and editing with si...
📖 Articles
ChatGPT Apps SDK: Your first MCP Server with Python, FastMCP, & FastAPI
The talk explains how to build an MCP server that integrates with ChatGPT using FastMCP and FastAPI. It covers setting up the Python environment, creating and running MCP tools (like a simple add function), and connecting the MCP server to ChatGPT through a public tunnel to enable ChatGPT to call custom functions, enhancing its capabilities with personalized context and tools.
remoclip
A CLI tool for accessing your local clipboard from remote systems.
TorchCurves - differentiable parametric curves in PyTorch
PyTorch parametric curves spanned by B-Splines or Legendre polynomials for KANs, Embeddings, or PDE solvers.
PyreFly: Python type checker and language server in Rust
google-agentic-commerce / AP2
Building a Secure and Interoperable Future for AI-Driven Payments.
Practical MCP with FastMCP & Python Tutorial – IO, HTTP Streams, APIs, and Testing
The video teaches how to build MCP servers using the FastMCP Python library. It covers MCP basics, building calculator apps with different communication protocols, integrating APIs for dynamic content, testing with GitHub Copilot, and deploying MCP servers on FastMCP Cloud for a complete development workflow.
Using Async Functions in Celery with Django Connection Pooling
The blog post explains how Celery, which currently does not support native async functions, can still integrate asynchronous Python code by using the async_to_sync utility from asgiref to run async functions synchronously within Celery tasks. It also discusses alternative approaches, such as using a dedicated event loop to run async code inside Celery tasks, and mentions that full async ...
Killing the GIL: How To Use Python 3.14's Free-Threading Upgrade
The global interpreter lock (GIL) has been interfering with true parallelism in Python. That ends with Python 3.14.
PyTorch 2.9
PyTorch 2.9 introduces new features including a stable libtorch ABI for C++/CUDA extensions, symmetric memory programming for easy multi-GPU kernel development, and enhanced control over graph break handling in torch.compile. It expands wheel support for AMD ROCm, Intel XPU, and CUDA 13, adds FlexAttention optimizations on Intel GPUs and X86 CPUs, and improves Arm platform performance wi...
Python Hub Weekly Digest for 2025-10-19
⚙️ Projects
Paper2Video
Automatic Video Generation from Scientific Papers.
Autoswagger
A command-line tool designed to discover, parse, and test for unauthenticated endpoints using Swagger/OpenAPI documentation. It helps identify potential security issues in unprotected endpoints of APIs, such as PII leaks and common secret exposures.
django-http-compression
Django middleware for compressing HTTP responses with Zstandard, Brotli, or Gzip.
rightnow-cli
Claude Code for CUDA. Free AI assistant that actually understands GPU architecture.
nanochat
The best ChatGPT that $100 can buy.
Cronboard
A terminal-based dashboard for managing cron jobs.
Erdos
A secure, AI-native IDE for data science.
Buridan UI
Beautifully designed Reflex components to build your web apps faster. Open source.
👾 Reddits
Advice on logging libraries: Logfire, Loguru, or just Python's built-in logging?
Best way to set up Python for Windows these days
TOML is great, and after diving deep into designing a config format, here's why I think that's true
Project by Ruslan Keba. Since 2012. Powered by Python. Made in 🇺🇦Ukraine.