In Django REST Framework (DRF), mastering the fundamentals from serializers to viewsets is essential before building or scaling any serious API. The DRF Essential Handbook serves as a compact recall guide, crafted for developers who want to quickly revisit key DRF concepts without diving deep into scattered documentation. It’s structured into four clear phases that follow a logical learning flow beginning with the foundations of serialization and view handling, then moving through relational modeling, data manipulation, and secure endpoint management.

“Blueprints of the API Battlefield.”
October 15, 2024

In Django development, while SQLite3 is often used for databases and static/media files are stored locally during development, in production especially on platforms like Heroku - you need to use more robust solutions. Heroku’s dynos are lightweight virtual containers that don’t retain files across redeployments, meaning SQLite3 data, static files, and user-uploaded media would be erased. This is why using third-party cloud services like RDS PostgreSQL for databases and AWS S3 for static/media storage is necessary. Additionally, Django uses Heroku for its rapid deployment, automatic GitHub integration, and built-in SSL support, making it ideal for both simple and complex applications.

"Dynos and Persistence."
March 31, 2025

Python’s asyncio library offers an efficient way to handle concurrent I/O-bound operations using the async and await syntax. Unlike traditional multithreading or multiprocessing, asyncio operates with a single-threaded event loop, allowing coroutines to execute cooperatively. This approach enhances responsiveness and scalability in applications such as web servers and network clients, making asyncio a powerful tool for handling high-performance asynchronous tasks.

"Async schedules, sync stalls."
November 23, 2024

Concurrency in Python enhances program efficiency by allowing multiple tasks to run seemingly simultaneously. Python provides two main concurrency models: multithreading and multiprocessing. While multithreading is well-suited for I/O-bound tasks, multiprocessing enables true parallel execution for CPU-intensive operations. Understanding their differences, benefits, and limitations helps developers optimize performance based on specific use cases.

"Threads share, processes seperate."
June 14, 2024