7 Python Libraries You're Not Using But Should Be in 2025 Python's ecosystem grows every year, and 2025 has brought some incredible libraries that can dramatically simplify your workflow. While everyone knows about requests , pandas , and numpy , let me share 7 lesser-known gems that have genuinely changed how I write code. 1. 🐍 pydantic-core + pydantic v2 — Data Validation on Steroids Most developers use Pydantic, but Pydantic v2 is a completely different beast. Written in Rust via pydantic-core, it's 5-50x faster than v1. from pydantic import BaseModel , field_validator from datetime import date class Event ( BaseModel ): name : str date : date attendees : int @field_validator ( " name " ) @classmethod def name_must_not_be_empty ( cls , v ): if not v . strip (): raise ValueError ( " Event name cannot be empty " ) return v . strip () event = Event ( name = " DevConf 2025 " , date = " 2025-09-15 " , attendees = 500 ) print ( event .…