spaCy/website/usage/_install/_instructions.jade

//- 💫 DOCS > USAGE > INSTALL > INSTRUCTIONS

+h(3, "pip") pip
    +badge("https://img.shields.io/pypi/v/spacy.svg?style=flat-square", "https://pypi.python.org/pypi/spacy")

p
    |  Using pip, spaCy releases are available as source packages and binary
    |  wheels (as of #[code v2.0.13]).

+code(false, "bash").
    pip install -U spacy

+aside("Download models")
    |  After installation you need to download a language model. For more info
    |  and available models, see the #[+a("/usage/models") docs on models].

    +code.o-no-block.
        python -m spacy download en

        >>> import spacy
        >>> nlp = spacy.load('en')

p
    |  When using pip it is generally recommended to install packages in a
    |  virtual environment to avoid modifying system state:

+code(false, "bash").
    python -m venv .env
    source .env/bin/activate
    pip install spacy

+h(3, "conda") conda
    +badge("https://anaconda.org/conda-forge/spacy/badges/version.svg", "https://anaconda.org/conda-forge/spacy")

p
    |  Thanks to our great community, we've finally re-added conda support. You
    |  can now install spaCy via #[code conda-forge]:

+code(false, "bash").
    conda install -c conda-forge spacy

p
    |  For the feedstock including the build recipe and configuration, check out
    |  #[+a("https://github.com/conda-forge/spacy-feedstock") this repository].
    |  Improvements and pull requests to the recipe and setup are always
    |  appreciated.

+h(3, "upgrading") Upgrading spaCy

+aside("Upgrading from v1 to v2")
    |  Although we've tried to keep breaking changes to a minimum, upgrading
    |  from spaCy v1.x to v2.x may still require some changes to your code base.
    |  For details see the sections on
    |  #[+a("/usage/v2#incompat") backwards incompatibilities] and
    |  #[+a("/usage/v2#migrating") migrating]. Also remember to download the new
    |  models, and retrain your own models.

p
    |  When updating to a newer version of spaCy, it's generally recommended to
    |  start with a clean virtual environment. If you're upgrading to a new
    |  major version, make sure you have the latest #[strong compatible models]
    |  installed, and that there are no old shortcut links or incompatible model
    |  packages left over in your environment, as this can often lead to unexpected
    |  results and errors.  If you've trained your own models, keep in mind that
    |  your train and runtime inputs must match. This means you'll have to
    |  #[strong retrain your models] with the new version.

p
    |  As of v2.0, spaCy also provides a #[+api("cli#validate") #[code validate]]
    |  command, which lets you verify that all installed models are compatible
    |  with your spaCy version. If incompatible models are found, tips and
    |  installation instructions are printed. The command is also useful to
    |  detect out-of-sync model links resulting from links created in different
    |  virtual environments. It's recommended to run the command with
    |  #[code python -m] to make sure you're executing the correct version of
    |  spaCy.

+code(false, "bash").
    pip install -U spacy
    python -m spacy validate

+h(3, "gpu") Run spaCy with GPU
    +tag-new("2.0.14")

p
    |  As of v2.0, spaCy's comes with neural network models that are implemented
    |  in our machine learning library, #[+a(gh("thinc")) Thinc]. For GPU
    |  support, we've been grateful to use the work of
    |  Chainer's #[+a("https://cupy.chainer.org") CuPy] module, which provides
    |  a NumPy-compatible interface for GPU arrays.

p
    |  spaCy can be installed on GPU by specifying #[code spacy[cuda]],
    |  #[code spacy[cuda90]], #[code spacy[cuda91]], #[code spacy[cuda92]] or
    |  #[code spacy[cuda100]]. If you know your cuda version, using the more
    |  explicit specifier allows cupy to be installed via wheel, saving some
    |  compilation time. The specifiers should install two libraries:
    |  #[+a("https://cupy.chainer.org") #[code cupy]] and
    |  #[+a(gh("thinc_gpu_ops")) #[code thinc_gpu_ops]].

+code(false, "bash").
    pip install -U spacy[cuda92]

p
    |  Once you have a GPU-enabled installation, the best way to activate it is
    |  to call #[+api("top-level#spacy.prefer_gpu") #[code spacy.prefer_gpu()]]
    |  or #[+api("top-level#spacy.require_gpu") #[code spacy.require_gpu()]]
    |  somewhere in your script before any models have been loaded.
    |  #[code require_gpu] will raise an error if no GPU is available.

+code.
    import spacy

    spacy.prefer_gpu()
    nlp = spacy.load('en_core_web_sm')

+h(3, "source") Compile from source

p
    |  The other way to install spaCy is to clone its
    |  #[+a(gh("spaCy")) GitHub repository] and build it from source. That is
    |  the common way if you want to make changes to the code base. You'll need
    |  to make sure that you have a development environment consisting of a
    |  Python distribution including header files, a compiler,
    |  #[+a("https://pip.pypa.io/en/latest/installing/") pip],
    |  #[+a("https://virtualenv.pypa.io/") virtualenv] and
    |  #[+a("https://git-scm.com") git] installed. The compiler part is the
    |  trickiest. How to do that depends on your system. See notes on
    |  #[a(href="#source-ubuntu") Ubuntu], #[a(href="#source-osx") OS X] and
    |  #[a(href="#source-windows") Windows] for details.

+code(false, "bash").
    python -m pip install -U pip                   # update pip
    git clone #{gh("spaCy")}   # clone spaCy
    cd spaCy                                       # navigate into directory

    python -m venv .env                            # create environment in .env
    source .env/bin/activate                       # activate virtual environment
    export PYTHONPATH=`pwd`                        # set Python path to spaCy directory
    pip install -r requirements.txt                # install all requirements
    python setup.py build_ext --inplace            # compile spaCy

p
    |  Compared to regular install via pip, the
    |  #[+src(gh("spaCy", "requirements.txt")) #[code requirements.txt]]
    |  additionally installs developer dependencies such as Cython. See the
    |  the #[+a("#section-quickstart") quickstart widget] to get the right
    |  commands for your platform and Python version. Instead of the above
    |  verbose commands, you can also use the following
    |  #[+a("http://www.fabfile.org/") Fabric] commands:

+table(["Command", "Description"])
    +row
        +cell #[code fab env]
        +cell Create a virtual environment and delete previous one, if it exists.

    +row
        +cell #[code fab make]
        +cell Compile the source.

    +row
        +cell #[code fab clean]
        +cell Remove compiled objects, including the generated C++.

    +row
        +cell #[code fab test]
        +cell Run basic tests, aborting after first failure.

p
    |  All commands assume that your virtual environment is located in a
    |  directory #[code .env]. If you're using a different directory, you can
    |  change it via the environment variable #[code VENV_DIR], for example:

+code(false, "bash").
    VENV_DIR=".custom-env" fab clean make

+h(4, "source-ubuntu") Ubuntu

p Install system-level dependencies via #[code apt-get]:

+code(false, "bash").
    sudo apt-get install build-essential python-dev git

+h(4, "source-osx") macOS / OS X

p
    |  Install a recent version of
    |  #[+a("https://developer.apple.com/xcode/") XCode], including the
    |  so-called "Command Line Tools". macOS and OS X ship with Python and git
    |  preinstalled. To compile spaCy with multi-threading support on macOS / OS X,
    |  #[+a("https://github.com/explosion/spaCy/issues/267") see here].

+h(4, "source-windows") Windows

p
    |  Install a version of the
    |  #[+a("https://visualstudio.microsoft.com/visual-cpp-build-tools/") Visual C++ Build Tools] or
    |  #[+a("https://www.visualstudio.com/vs/visual-studio-express/") Visual Studio Express]
    |  that matches the version that was used to compile your Python
    |  interpreter. For official distributions these are:

+table([ "Distribution", "Version"])
    +row
        +cell Python 2.7
        +cell Visual Studio 2008

    +row
        +cell Python 3.4
        +cell Visual Studio 2010

    +row
        +cell Python 3.5+
        +cell Visual Studio 2015

+h(3, "tests") Run tests

p
    |  spaCy comes with an #[+a(gh("spacy", "spacy/tests")) extensive test suite].
    |  In order to run the tests, you'll usually want to clone the
    |  #[+a(gh("spacy")) repository] and #[+a("#source") build spaCy from source].
    |  This will also install the required development dependencies and test
    |  utilities defined in the #[code requirements.txt].

p
    |  Alternatively, you can find out where spaCy is installed and run
    |  #[code pytest] on that directory. Don't forget to also install the
    |  test utilities via spaCy's
    |  #[+a(gh("spacy", "requirements.txt")) #[code requirements.txt]]:

+code(false, "bash").
    python -c "import os; import spacy; print(os.path.dirname(spacy.__file__))"
    pip install -r path/to/requirements.txt
    python -m pytest <spacy-directory>

p
    |  Calling #[code pytest] on the spaCy directory will run only the basic
    |  tests. The flags #[code --slow] and #[code --model] are optional and
    |  enable additional tests that take longer or use specific models.

+code(false, "bash").
    # make sure you are using recent pytest version
    python -m pip install -U pytest

    python -m pytest <spacy-directory>                 # basic tests
    python -m pytest <spacy-directory> --slow          # basic and slow tests
    python -m pytest <spacy-directory> --models --all  # basic and all model tests
    python -m pytest <spacy-directory> --models --en   # basic and English model tests

+infobox("Note on model tests", "⚠️")
    |  The test suite specifies a #[+a(gh("spacy", "spacy/tests/conftest.py")) list of models]
    |  to run the tests on. If a model is not installed, the tests will be
    |  skipped. If all models are installed, the respective tests will run once
    |  for each model. The easiest way to find out which models and model
    |  versions are available in your current environment is to run
    |  #[+a("/api/cli#validate") #[code python -m spacy validate]]. This will
    |  also show whether an installed model is out of date, and how to update it.