spaCy is a free, open-source library for industrial-strength Natural Language Processing in Python and Cython, designed specifically for production use with state-of-the-art speed and accuracy. Unlike research-oriented libraries, spaCy emphasizes practical deployment with pre-trained pipelines for 75+ languages, efficient batch processing via streaming APIs, and a clean, consistent interface. The library's architecture centers on the processing pipeline — a sequence of components (tokenizer, tagger, parser, NER) that transform raw text into rich linguistic annotations stored in immutable Doc objects. One key insight: spaCy encodes all strings as hash values in a shared Vocab, enabling memory-efficient representation while maintaining fast lookups; this design choice permeates the entire system and explains why you access attributes via both hashed IDs and string properties (e.g., token.lemma vs token.lemma_).