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README.md
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README.md
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# spaCy: Industrial-strength NLP
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spaCy is a library for advanced Natural Language Processing in Python and
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Cython. It's built on the very latest research, and was designed from day one
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to be used in real products. spaCy comes with
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[pre-trained statistical models](https://spacy.io/models) and word vectors, and
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Cython. It's built on the very latest research, and was designed from day one to
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be used in real products. spaCy comes with
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currently supports tokenization for **50+ languages**. It features
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state-of-the-art speed, convolutional **neural network models** for tagging,
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parsing and **named entity recognition** and easy **deep learning** integration.
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@ -48,13 +48,13 @@ It's commercial open-source software, released under the MIT license.
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## 💬 Where to ask questions
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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), along with core contributors
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The spaCy project is maintained by [@honnibal](https://github.com/honnibal) and
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[@ines](https://github.com/ines), along with core contributors
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[@svlandeg](https://github.com/svlandeg) and
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[@adrianeboyd](https://github.com/adrianeboyd). Please understand that we won't
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be able to provide individual support via email. We also believe that help is
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much more valuable if it's shared publicly, so that more people can benefit
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from it.
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much more valuable if it's shared publicly, so that more people can benefit from
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it.
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| Type | Platforms |
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| ------------------------ | ------------------------------------------------------ |
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@ -94,7 +94,8 @@ from it.
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For detailed installation instructions, see the
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[documentation](https://spacy.io/usage).
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- **Operating system**: macOS / OS X · Linux · Windows (Cygwin, MinGW, Visual Studio)
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- **Operating system**: macOS / OS X · Linux · Windows (Cygwin, MinGW, Visual
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Studio)
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- **Python version**: Python 2.7, 3.5+ (only 64 bit)
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- **Package managers**: [pip] · [conda] (via `conda-forge`)
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@ -103,8 +104,8 @@ For detailed installation instructions, see the
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### pip
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Using pip, spaCy releases are available as source packages and binary wheels
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(as of `v2.0.13`).
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Using pip, spaCy releases are available as source packages and binary wheels (as
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of `v2.0.13`).
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```bash
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pip install spacy
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@ -129,9 +130,9 @@ conda config --add channels conda-forge
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conda install spacy
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```
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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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For the feedstock including the build recipe and configuration, check out
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[this repository](https://github.com/conda-forge/spacy-feedstock). Improvements
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and pull requests to the recipe and setup are always appreciated.
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### Updating spaCy
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## Download models
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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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As of v1.7.0, models for spaCy can be installed as **Python packages**. This
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means that they're a component of your application, just like any other module.
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Models can be installed using spaCy's `download` command, or manually by
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pointing pip to a path or URL.
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| Documentation | |
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| ---------------------- | ------------------------------------------------------------- |
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### Support for older versions
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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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If you're using an older version (`v1.6.0` or below), you can still download and
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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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@ -222,9 +223,10 @@ 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/),
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[virtualenv](https://virtualenv.pypa.io/en/latest/) and [git](https://git-scm.com)
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installed. The compiler part is the trickiest. How to do that depends on your
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system. See notes on Ubuntu, OS X and Windows for details.
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[virtualenv](https://virtualenv.pypa.io/en/latest/) and
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[git](https://git-scm.com) installed. The compiler part is the trickiest. How to
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do that depends on your system. See notes on Ubuntu, OS X and Windows for
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details.
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```bash
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# make sure you are using the latest pip
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@ -243,8 +245,8 @@ 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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[quickstart widget](https://spacy.io/usage#section-quickstart) to get the right
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commands for your platform and Python version.
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### Ubuntu
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@ -262,11 +264,12 @@ and git preinstalled.
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### Windows
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Install a version of the [Visual C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) or
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[Visual Studio Express](https://visualstudio.microsoft.com/vs/express/)
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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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Install a version of the
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[Visual C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
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or [Visual Studio Express](https://visualstudio.microsoft.com/vs/express/) that
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matches the version that was used to compile your Python interpreter. For
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official distributions these are VS 2008 (Python 2.7), VS 2010 (Python 3.4) and
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VS 2015 (Python 3.5).
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## Run tests
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