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333 lines
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ReStructuredText
333 lines
12 KiB
ReStructuredText
spaCy: Industrial-strength NLP
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******************************
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spaCy is a library for advanced Natural Language Processing in Python and Cython.
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It's built on the very latest research, and was designed from day one to be
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used in real products. spaCy comes with
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`pre-trained statistical models <https://spacy.io/models>`_ and word
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vectors, and currently supports tokenization for **20+ languages**. It features
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the **fastest syntactic parser** in the world, convolutional **neural network models**
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for tagging, parsing and **named entity recognition** and easy **deep learning**
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integration. It's commercial open-source software, released under the MIT license.
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💫 **Version 2.0 out now!** `Check out the new features here. <https://spacy.io/usage/v2>`_
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.. image:: https://img.shields.io/travis/explosion/spaCy/master.svg?style=flat-square&logo=travis
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:target: https://travis-ci.org/explosion/spaCy
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:alt: Build Status
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.. image:: https://img.shields.io/appveyor/ci/explosion/spaCy/master.svg?style=flat-square&logo=appveyor
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:target: https://ci.appveyor.com/project/explosion/spaCy
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:alt: Appveyor Build Status
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.. image:: https://img.shields.io/github/release/explosion/spacy.svg?style=flat-square
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:target: https://github.com/explosion/spaCy/releases
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:alt: Current Release Version
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.. image:: https://img.shields.io/pypi/v/spacy.svg?style=flat-square
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:target: https://pypi.python.org/pypi/spacy
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:alt: pypi Version
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.. image:: https://img.shields.io/conda/vn/conda-forge/spacy.svg?style=flat-square
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:target: https://anaconda.org/conda-forge/spacy
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:alt: conda Version
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.. image:: https://img.shields.io/badge/chat-join%20%E2%86%92-09a3d5.svg?style=flat-square&logo=gitter-white
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:target: https://gitter.im/explosion/spaCy
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:alt: spaCy on Gitter
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.. image:: https://img.shields.io/twitter/follow/spacy_io.svg?style=social&label=Follow
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:target: https://twitter.com/spacy_io
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:alt: spaCy on Twitter
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📖 Documentation
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================
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=================== ===
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`spaCy 101`_ New to spaCy? Here's everything you need to know!
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`Usage Guides`_ How to use spaCy and its features.
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`New in v2.0`_ New features, backwards incompatibilities and migration guide.
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`API Reference`_ The detailed reference for spaCy's API.
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`Models`_ Download statistical language models for spaCy.
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`Universe`_ Libraries, extensions, demos, books and courses.
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`Changelog`_ Changes and version history.
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`Contribute`_ How to contribute to the spaCy project and code base.
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=================== ===
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.. _spaCy 101: https://spacy.io/usage/spacy-101
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.. _New in v2.0: https://spacy.io/usage/v2#migrating
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.. _Usage Guides: https://spacy.io/usage/
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.. _API Reference: https://spacy.io/api/
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.. _Models: https://spacy.io/models
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.. _Universe: https://spacy.io/universe
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.. _Changelog: https://spacy.io/usage/#changelog
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.. _Contribute: https://github.com/explosion/spaCy/blob/master/CONTRIBUTING.md
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💬 Where to ask questions
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==========================
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The spaCy project is maintained by `@honnibal <https://github.com/honnibal>`_
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and `@ines <https://github.com/ines>`_. Please understand that we won't be able
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to provide individual support via email. We also believe that help is much more
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valuable if it's shared publicly, so that more people can benefit from it.
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====================== ===
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**Bug Reports** `GitHub Issue Tracker`_
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**Usage Questions** `StackOverflow`_, `Gitter Chat`_, `Reddit User Group`_
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**General Discussion** `Gitter Chat`_, `Reddit User Group`_
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====================== ===
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.. _GitHub Issue Tracker: https://github.com/explosion/spaCy/issues
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.. _StackOverflow: http://stackoverflow.com/questions/tagged/spacy
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.. _Gitter Chat: https://gitter.im/explosion/spaCy
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.. _Reddit User Group: https://www.reddit.com/r/spacynlp
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Features
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========
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* **Fastest syntactic parser** in the world
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* **Named entity** recognition
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* Non-destructive **tokenization**
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* Support for **20+ languages**
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* Pre-trained `statistical models <https://spacy.io/models>`_ and word vectors
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* Easy **deep learning** integration
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* Part-of-speech tagging
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* Labelled dependency parsing
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* Syntax-driven sentence segmentation
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* Built in **visualizers** for syntax and NER
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* Convenient string-to-hash mapping
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* Export to numpy data arrays
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* Efficient binary serialization
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* Easy **model packaging** and deployment
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* State-of-the-art speed
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* Robust, rigorously evaluated accuracy
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📖 **For more details, see the** `facts, figures and benchmarks <https://spacy.io/usage/facts-figures>`_.
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Install spaCy
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=============
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For detailed installation instructions, see
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the `documentation <https://spacy.io/usage>`_.
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==================== ===
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**Operating system** macOS / OS X, Linux, Windows (Cygwin, MinGW, Visual Studio)
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**Python version** CPython 2.7, 3.4+. Only 64 bit.
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**Package managers** `pip`_ (source packages only), `conda`_ (via ``conda-forge``)
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==================== ===
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.. _pip: https://pypi.python.org/pypi/spacy
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.. _conda: https://anaconda.org/conda-forge/spacy
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pip
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---
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Using pip, spaCy releases are currently only available as source packages.
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.. code:: bash
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pip install spacy
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When using pip it is generally recommended to install packages in a virtual
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environment to avoid modifying system state:
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.. code:: bash
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venv .env
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source .env/bin/activate
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pip install spacy
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conda
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-----
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Thanks to our great community, we've finally re-added conda support. You can now
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install spaCy via ``conda-forge``:
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.. code:: bash
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conda config --add channels conda-forge
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conda install spacy
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For the feedstock including the build recipe and configuration,
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check out `this repository <https://github.com/conda-forge/spacy-feedstock>`_.
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Improvements and pull requests to the recipe and setup are always appreciated.
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Updating spaCy
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--------------
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Some updates to spaCy may require downloading new statistical models. If you're
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running spaCy v2.0 or higher, you can use the ``validate`` command to check if
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your installed models are compatible and if not, print details on how to update
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them:
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.. code:: bash
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pip install -U spacy
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python -m spacy validate
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If you've trained your own models, keep in mind that your training and runtime
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inputs must match. After updating spaCy, we recommend **retraining your models**
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with the new version.
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📖 **For details on upgrading from spaCy 1.x to spaCy 2.x, see the**
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`migration guide <https://spacy.io/usage/v2#migrating>`_.
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Download models
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===============
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As of v1.7.0, models for spaCy can be installed as **Python packages**.
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This means that they're a component of your application, just like any
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other module. Models can be installed using spaCy's ``download`` command,
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or manually by pointing pip to a path or URL.
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======================= ===
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`Available Models`_ Detailed model descriptions, accuracy figures and benchmarks.
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`Models Documentation`_ Detailed usage instructions.
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======================= ===
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.. _Available Models: https://spacy.io/models
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.. _Models Documentation: https://spacy.io/docs/usage/models
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.. code:: bash
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# out-of-the-box: download best-matching default model
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python -m spacy download en
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# download best-matching version of specific model for your spaCy installation
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python -m spacy download en_core_web_lg
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# pip install .tar.gz archive from path or URL
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pip install /Users/you/en_core_web_sm-2.0.0.tar.gz
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If you have SSL certification problems, SSL customization options are described in the help:
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# help for the download command
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python -m spacy download --help
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Loading and using models
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------------------------
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To load a model, use ``spacy.load()`` with the model's shortcut link:
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.. code:: python
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import spacy
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nlp = spacy.load('en')
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doc = nlp(u'This is a sentence.')
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If you've installed a model via pip, you can also ``import`` it directly and
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then call its ``load()`` method:
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.. code:: python
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import spacy
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import en_core_web_sm
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nlp = en_core_web_sm.load()
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doc = nlp(u'This is a sentence.')
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📖 **For more info and examples, check out the**
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`models documentation <https://spacy.io/docs/usage/models>`_.
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Support for older versions
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--------------------------
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If you're using an older version (``v1.6.0`` or below), you can still download
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and install the old models from within spaCy using ``python -m spacy.en.download all``
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or ``python -m spacy.de.download all``. The ``.tar.gz`` archives are also
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`attached to the v1.6.0 release <https://github.com/explosion/spaCy/tree/v1.6.0>`_.
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To download and install the models manually, unpack the archive, drop the
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contained directory into ``spacy/data`` and load the model via ``spacy.load('en')``
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or ``spacy.load('de')``.
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Compile from source
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===================
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The other way to install spaCy is to clone its
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`GitHub repository <https://github.com/explosion/spaCy>`_ and build it from
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source. That is the common way if you want to make changes to the code base.
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You'll need to make sure that you have a development environment consisting of a
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Python distribution including header files, a compiler,
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`pip <https://pip.pypa.io/en/latest/installing/>`__, `virtualenv <https://virtualenv.pypa.io/>`_
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and `git <https://git-scm.com>`_ installed. The compiler part is the trickiest.
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How to do that depends on your system. See notes on Ubuntu, OS X and Windows for
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details.
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.. code:: bash
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# make sure you are using recent pip/virtualenv versions
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python -m pip install -U pip venv
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git clone https://github.com/explosion/spaCy
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cd spaCy
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venv .env
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source .env/bin/activate
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export PYTHONPATH=`pwd`
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pip install -r requirements.txt
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python setup.py build_ext --inplace
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Compared to regular install via pip, `requirements.txt <requirements.txt>`_
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additionally installs developer dependencies such as Cython. For more details
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and instructions, see the documentation on
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`compiling spaCy from source <https://spacy.io/usage/#source>`_ and the
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`quickstart widget <https://spacy.io/usage/#section-quickstart>`_ to get
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the right commands for your platform and Python version.
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Instead of the above verbose commands, you can also use the following
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`Fabric <http://www.fabfile.org/>`_ commands. All commands assume that your
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virtual environment is located in a directory ``.env``. If you're using a
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different directory, you can change it via the environment variable ``VENV_DIR``,
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for example ``VENV_DIR=".custom-env" fab clean make``.
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============= ===
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``fab env`` Create virtual environment and delete previous one, if it exists.
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``fab make`` Compile the source.
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``fab clean`` Remove compiled objects, including the generated C++.
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``fab test`` Run basic tests, aborting after first failure.
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============= ===
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Ubuntu
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------
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Install system-level dependencies via ``apt-get``:
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.. code:: bash
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sudo apt-get install build-essential python-dev git
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macOS / OS X
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------------
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Install a recent version of `XCode <https://developer.apple.com/xcode/>`_,
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including the so-called "Command Line Tools". macOS and OS X ship with Python
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and git preinstalled.
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Windows
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-------
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Install a version of `Visual Studio Express <https://www.visualstudio.com/vs/visual-studio-express/>`_
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or higher that matches the version that was used to compile your Python
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interpreter. For official distributions these are VS 2008 (Python 2.7),
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VS 2010 (Python 3.4) and VS 2015 (Python 3.5).
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Run tests
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=========
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spaCy comes with an `extensive test suite <spacy/tests>`_. In order to run the
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tests, you'll usually want to clone the repository and build spaCy from source.
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This will also install the required development dependencies and test utilities
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defined in the ``requirements.txt``.
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Alternatively, you can find out where spaCy is installed and run ``pytest`` on
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that directory. Don't forget to also install the test utilities via spaCy's
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``requirements.txt``:
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.. code:: bash
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python -c "import os; import spacy; print(os.path.dirname(spacy.__file__))"
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pip install -r path/to/requirements.txt
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python -m pytest <spacy-directory>
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See `the documentation <https://spacy.io/usage/#tests>`_ for more details and
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examples.
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