Customising Pattern Matching Behaviour (In Python)

mcp - cтандартизация передачи контекста между LLM

Python⇒Speed: Reducing CO₂ emissions with faster software

3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction?

Django: launch pdb when a given SQL query runs

New era of slop security reports for open source

Speeding Up Data Retrieval From PostgreSQL With Psycopg

Formatting and concatenating query result columns on the PostgreSQL side and then parsing them in Python might sometimes be faster than fetching the columns as separate values.

The Practical Guide to Scaling Django

Squashing Django Migrations Easily

Safely squash Django migrations in long-running projects to optimize performance and maintain migration history integrity using django-model-info

Python Crypto Library Updated to Steal Private Keys

Django: launch pdb in templates with a custom {% breakpoint %} tag

Continuous Integration and Deployment for Python With GitHub Actions

Python Dependency Management Is a Dumpster Fire

Managing dependencies in Python can be a bit of a challenge. This deep dive article shows you all the problems and how the problems are mitigated if not solved.

Django Performance and Optimization

“This document provides an overview of techniques and tools that can help get your Django code running more efficiently - faster, and using fewer system resources.”

Django: fix a view using a debugger with breakpoint()

Is async django ready for prime time?

Django's async capabilities have significantly improved, making it a viable option for production use, especially in AI applications where I/O-bound tasks are prevalent.

Security means securing people where they are

Diagram-as-Code: Creating Dynamic and Interactive Documentation for Visual Content

Django: find ghost tables without associated models

NumPy Practical Examples: Useful Techniques

In this tutorial, you'll learn how to use NumPy by exploring several interesting examples. You'll read data from a file into an array and analyze structured arrays to perform a reconciliation. You'll also learn how to quickly chart an analysis and turn a custom function into a vectorized function.