flashtext

Why we included this project

Most keyword-matching tasks in Python end up as a pile of regular expressions, and that gets slow and hard to maintain once you have hundreds of terms. FlashText takes a different route: it's a lightweight library that builds a trie from your keyword list and scans each sentence once, which stays noticeably quicker than regex as your pattern set grows into the hundreds or thousands. The API is small, which is the point. You add keywords, optionally mapping messy variants like 'Big Apple' to a canonical name, then call extract_keywords or replace_keywords, with case sensitivity and span reporting when you need them. That covers tagging documents, normalizing product or entity names, and cleaning free-text fields before they reach a larger NLP pipeline. Teams that want predictable, explainable matching without a heavyweight model can drop it into existing Python code with minimal fuss.