spaCy is an open-source Python library for natural language processing, built to pull structure such as words, grammar and names out of large amounts of text.
In plain words
Computers see text as a string of characters. spaCy runs text through a pipeline of steps. It splits it into tokens such as words and punctuation, tags each token as a noun, verb and so on, and labels named things such as people, companies and places. Some steps use trained statistical models, which are available for a range of languages. It is meant for real applications rather than research demos.
A quick example
The spaCy docs analyse a short sentence about Apple planning to buy a startup in the U.K. for $1 billion. The English pipeline splits it into tokens, tags "buying" as a verb, and labels "Apple" as an organisation, "U.K." as a country and "$1 billion" as money. A program could then count which companies appear across thousands of news articles.
Where you'll meet it
- Finding names of people, companies and places in documents.
- Preparing and analysing large volumes of text in production apps.
Related
Sources
- DocsspaCy 101: Everything you need to know, Explosion (spaCy docs) · read 29 Sept 2026
- DocsspaCy: Industrial-strength Natural Language Processing in Python, Explosion · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.