dataclass, TypedDict, or Pydantic: Choosing the Right Tool for JSON in Python
When converting JSON to typed Python objects, developers have three main options: dataclass, TypedDict, and Pydantic, each serving a distinct purpose. Dataclasses offer attribute-style access for…
Read the full articleYou might also wanna read
Google Announces Final Python 3.12 Support for Pytype Static Type Analyzer
A static type analyzer for Python code. Contribute to google/pytype development by creating an account on GitHub.
Type-Driven Design: The 'Parse, Don't Validate' Approach to Programming
Historically, I’ve struggled to find a concise, simple way to explain what it means to practice type-driven design. Too often, when someone
Benefits of Using Keyword-Only Arguments in Python Dataclasses
Python dataclasses are a really nice feature for constructing classes that primarily hold or work with data. They can be a good alternative
Pydantic for AI Validation - Type Safety for LLM Applications
Master Pydantic for AI application validation. Learn type-safe data models, LLM output validation, API schemas, and patterns for building re
Exploring Alternatives to Python Classes for Data Storage
Python is an incredibly versatile programming language known for its simplicity and readability. Among its features, the ability to use clas

Exploring Data Operations with PySpark, Pandas, DuckDB, Polars, and DataFusion in a Python Notebook
> **Cross-posted.** This article's canonical home is [Iceberg Lakehouse]( - [A...

Comments
Sign in to join the conversation.
No comments yet. Be the first.