Python
How to Work with JSON in Python
JSON (JavaScript Object Notation) is one of the most common formats for storing and exchanging data across applications and APIs.…
Read More »Using Typed Python (MyPy / Pyright) in Large Django Projects: Trade-offs & Surprising Caveats
Adding type hints to a large Django project sounds like an obvious win. Static analysis catches bugs before they reach…
Read More »Scaling Django for Real-Time Applications: WebSockets, Channels, and Async Views
Django built its reputation on synchronous request-response cycles. But modern applications demand real-time features: live notifications, collaborative editing, chat systems,…
Read More »How to Tokenize Text in Python
Tokenization is one of the most fundamental steps in Natural Language Processing (NLP). It involves breaking text into smaller units…
Read More »Vector Databases Explained: Why Developers Are Talking About Pinecone and Weaviate
Vector databases have become essential infrastructure for modern AI applications. Unlike traditional databases that store text or numbers, vector databases…
Read More »Home Automation Projects – Smart Lighting, Security, and HVAC Control with Raspberry Pi
Home automation is no longer reserved for futuristic movies or high-end smart homes. Thanks to affordable hardware like the Raspberry…
Read More »Introduction to PgVector
PgVector is a PostgreSQL extension that adds support for vector data types, enabling efficient storage, indexing, and similarity search on…
Read More »Build Text-to-SQL using LLM
Text-to-SQL is a powerful application of large language models (LLMs) like GPT that enables users to interact with a database…
Read More »Understanding LiteralString in Python 3.11: A Deep Dive
Python 3.11 introduced LiteralString as a way to enhance type safety when dealing with string literals, particularly in security-sensitive contexts like SQL…
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