spacy

Industrial-strength Natural Language Processing (NLP) in Python

spacy Permissive license MIT Active ★ 33,816 v3.8.15 released 2026-08-07

Install

spacy on PyPI

pip

pip install spacy

uv

uv add spacy

poetry

poetry add spacy

Package facts

License	MIT (permissive)
Python support	supports the current Python release (<3.15,>=3.9)
Install friction	medium — platform-specific wheel
Runtime dependencies	20 — spacy-legacy, spacy-loggers, murmurhash, cymem, preshed, thinc, wasabi, srsly, catalogue, weasel, confection, typer, click, tqdm, numpy, requests, pydantic, jinja2, setuptools, packaging
Maintenance	actively maintained — 6 days since the last release
Last repo commit	2026-08-07
First released	2015-01-25
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: spacy-3.8.15-cp310-cp310-macosx_10_9_x86_64.whl; spacy-3.8.15-cp310-cp310-macosx_11_0_arm64.whl; spacy-3.8.15-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; spacy-3.8.15-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; spacy-3.8.15-cp310-cp310-musllinux_1_2_aarch64.whl; spacy-3.8.15-cp310-cp310-musllinux_1_2_x86_64.whl; spacy-3.8.15-cp310-cp310-win_amd64.whl; spacy-3.8.15-cp311-cp311-macosx_10_9_x86_64.whl; spacy-3.8.15-cp311-cp311-macosx_11_0_arm64.whl; spacy-3.8.15-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; spacy-3.8.15-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; spacy-3.8.15-cp311-cp311-musllinux_1_2_aarch64.whl; spacy-3.8.15-cp311-cp311-musllinux_1_2_x86_64.whl; spacy-3.8.15-cp311-cp311-win_amd64.whl; spacy-3.8.15-cp311-cp311-win_arm64.whl; spacy-3.8.15-cp312-cp312-macosx_10_13_x86_64.whl; spacy-3.8.15-cp312-cp312-macosx_11_0_arm64.whl; spacy-3.8.15-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; spacy-3.8.15-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl; spacy-3.8.15-cp312-cp312-musllinux_1_2_aarch64.whl

Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: CythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Topic :: Scientific/Engineering

About spacy

from the package's own PyPI description — quoted content, verbatim

spaCy: Industrial-strength NLP

spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products.

spaCy comes with pretrained pipelines and currently supports tokenization and training for 70+ languages. It features state-of-the-art speed and neural network models for tagging, parsing, named entity recognition, text classification and more, multi-task learning with pretrained transformers like BERT, as well as a production-ready training system and easy model packaging, deployment and workflow management. spaCy is commercial open-source software, released under the MIT license.

💫 Version 3.8 out now! [Check out the release notes...

Read as markdown · JSON record · Source repository · Homepage

AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

spaCy is an industrial-strength NLP library providing neural network models for tokenization, named entity recognition, dependency parsing, text classification, and multi-task learning with transformers across 70+ languages.

Medium install friction due to 20 runtime dependencies and compiled components (Cython). Wheels are available for Python 3.9–3.12 across macOS, Linux, and Windows, reducing build complexity. Active maintenance with 6 days since last release signals strong ongoing support.

Released under the MIT license (permissive), allowing commercial and private use with minimal restrictions. No copyleft obligations or attribution requirements beyond license inclusion.

Usage

pip install spacy
import spacy
nlp = spacy.load('en_core_web_sm')
doc = nlp('Hello world')
for token in doc:
    print(token.text, token.pos_)

Requires a pretrained model downloaded separately (e.g., via `python -m spacy download en_core_web_sm`); models are not bundled with the package.

Verdict: spaCy is a mature, actively maintained production-grade NLP framework with no known vulnerabilities, permissive licensing, and broad platform support. Medium install friction is offset by comprehensive wheels and active maintenance, making it suitable for both research and production deployments.

Needs verification

Whether the 20 runtime dependencies introduce transitive security or maintenance risks not captured in spaCy's own vulnerability record.
Performance characteristics and memory footprint for large-scale text processing workloads.
Community adoption metrics beyond maintenance signals.

natural language processing pythonnamed entity recognition NERdependency parsingtext tokenizationtransformer integration NLPproduction NLP pipelinemultilingual text processing