Are you experiencing performance bottlenecks in your Python applications? Have you wondered why your multi-threaded Python code doesn't fully utilize all CPU cores? The answer lies in Python's Global Interpreter Lock (GIL). For years, this mechanism has been a significant limitation for CPU-bound tasks in Python,

Introduction Extracting information from PDF files is a common use case. Often we want to extract structured data from PDF files such as resumes, invoices, or reports. Extracting relevant information while maintaining a consistent structure is crucial for automation and further analysis. By leveraging LLMs and Pydantic, developers can transform

As developers, we often encounter scenarios where certain actions need to be performed whenever something happens to our models. Whether it’s adding new data, updating existing records, or deleting something from the database. For years, Django signals have been the go-to solution for handling these kinds of requirements. They’

As a Django developer, you’ve received a PRD to start building a brand-new product from scratch. Your first task? Project initialization and a deployment checklist. Sounds familiar, right? It's the same routine of configurations you’ve handled in your recent projects, just with a few tweaks for

In any application, ensuring that the data you’re working with is valid and well-formed is a critical part of ensuring that the application runs smoothly and reliably. In Python, there are many libraries available for data validation, but one that stands out for its ease of use, performance, and

Introduction The way Python handles garbage collection is miles apart from how Java does it. The approach taken by each of these languages impacts the performance and ease of use in multiple ways. In the world of programming, memory management is a critical aspect that can significantly impact the performance

Introduction In the world of Python development, the proper setup can significantly boost productivity and ensure that you can write robust scripts. A collection of libraries knit together can make a huge difference in the quality of programs that you write. From command-line argument parsing to HTTP request handling — This

Introduction Python is not a strongly typed language — which means things can go wrong at runtime. Python provides you with a dynamic environment, where variables don’t need a declared type before use, flexibility comes hand-in-hand with the challenge of unexpected runtime errors. These errors often stem from data not

Introduction Welcome to the first post in the series of Defensive Programming. In this series, I am going to cover how to write code in Python that helps you sleep well at night. Code that you can rely on to work in production and not fail you unexpectedly. Python is

Introduction When you’re developing a serious Python application, you’ll often need configuration parameters that can change based on where the application is running. Environment variables are a great way to handle this because they allow you to adjust settings without changing your application code. Just tweak the environment