spaCy/website/usage/_install/_instructions.jade
2017-10-03 14:26:20 +02:00

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//- 💫 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 currently only available as source packages.
+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.
spacy download en
>>> import spacy
>>> nlp = spacy.load('en')
p
| When using pip it is generally recommended to install packages in a
| #[code virtualenv] to avoid modifying system state:
+code(false, "bash").
virtualenv .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 config --add channels conda-forge
conda install 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, "gpu") Run spaCy with GPU
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
| #[+a("http://chainer.org") Chainer]'s CuPy module, which provides
| a NumPy-compatible interface for GPU arrays.
p
| First, install follows the normal CUDA installation procedure. Next, set
| your environment variables so that the installation will be able to find
| CUDA. Finally, install spaCy.
+code(false, "bash").
export CUDA_HOME=/usr/local/cuda-8.0 # Or wherever your CUDA is
export PATH=$PATH:$CUDA_HOME/bin
pip install spacy
python -c "import thinc.neural.gpu_ops" # Check the GPU ops were built
+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").
# make sure you are using recent pip/virtualenv versions
python -m pip install -U pip virtualenv
git clone #{gh("spaCy")}
cd spaCy
virtualenv .env
source .env/bin/activate
pip install -r requirements.txt
pip install -e .
p
| Compared to regular install via pip,
| #[+a(gh("spaCy", "requirements.txt")) requirements.txt]
| additionally installs developer dependencies such as Cython.
p
| 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 #[code virtualenv] 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 #[code virtualenv] 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
| #[+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].
| First, find out where spaCy is installed:
+code(false, "bash").
python -c "import os; import spacy; print(os.path.dirname(spacy.__file__))"
p
| Then run #[code pytest] on that directory. The flags #[code --slow] and
| #[code --model] are optional and enable additional tests.
+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