mirror of https://github.com/explosion/spaCy.git
426 lines
16 KiB
Markdown
426 lines
16 KiB
Markdown
---
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title: Install spaCy
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next: /usage/models
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menu:
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- ['Quickstart', 'quickstart']
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- ['Instructions', 'installation']
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- ['Troubleshooting', 'troubleshooting']
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- ['Changelog', 'changelog']
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---
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spaCy is compatible with **64-bit CPython 2.6+/3.3+** and runs on
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**Unix/Linux**, **macOS/OS X** and **Windows**. The latest spaCy releases are
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available over [pip](https://pypi.python.org/pypi/spacy) and
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[conda](https://anaconda.org/conda-forge/spacy).
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> #### 📖 Looking for the old docs?
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>
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> To help you make the transition from v1.x to v2.0, we've uploaded the old
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> website to [**legacy.spacy.io**](https://legacy.spacy.io/docs). Wherever
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> possible, the new docs also include notes on features that have changed in
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> v2.0, and features that were introduced in the new version.
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## Quickstart {hidden="true"}
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import QuickstartInstall from 'widgets/quickstart-install.js'
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<QuickstartInstall title="Quickstart" id="quickstart" />
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## Installation instructions {#installation}
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### pip
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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 -U spacy
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```
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> #### Download models
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>
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> After installation you need to download a language model. For more info and
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> available models, see the [docs on models](/models).
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>
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> ```bash
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> $ python -m spacy download en_core_web_sm
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>
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> >>> import spacy
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> >>> nlp = spacy.load("en_core_web_sm")
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> ```
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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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```bash
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python -m venv .env
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source .env/bin/activate
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pip install spacy
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```
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### conda
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Thanks to our great community, we've been able to re-add conda support. You can
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also install spaCy via `conda-forge`:
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```bash
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$ conda install -c conda-forge spacy
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```
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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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### Upgrading spaCy {#upgrading}
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> #### Upgrading from v1 to v2
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>
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> Although we've tried to keep breaking changes to a minimum, upgrading from
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> spaCy v1.x to v2.x may still require some changes to your code base. For
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> details see the sections on [backwards incompatibilities](/usage/v2#incompat)
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> and [migrating](/usage/v2#migrating). Also remember to download the new
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> models, and retrain your own models.
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When updating to a newer version of spaCy, it's generally recommended to start
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with a clean virtual environment. If you're upgrading to a new major version,
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make sure you have the latest **compatible models** installed, and that there
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are no old shortcut links or incompatible model packages left over in your
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environment, as this can often lead to unexpected results and errors. If you've
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trained your own models, keep in mind that your train and runtime inputs must
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match. This means you'll have to **retrain your models** with the new version.
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As of v2.0, spaCy also provides a [`validate`](/api/cli#validate) command, which
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lets you verify that all installed models are compatible with your spaCy
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version. If incompatible models are found, tips and installation instructions
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are printed. The command is also useful to detect out-of-sync model links
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resulting from links created in different virtual environments. It's recommended
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to run the command with `python -m` to make sure you're executing the correct
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version of spaCy.
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```bash
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pip install -U spacy
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python -m spacy validate
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```
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### Run spaCy with GPU {#gpu new="2.0.14"}
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As of v2.0, spaCy comes with neural network models that are implemented in our
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machine learning library, [Thinc](https://github.com/explosion/thinc). For GPU
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support, we've been grateful to use the work of Chainer's
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[CuPy](https://cupy.chainer.org) module, which provides a numpy-compatible
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interface for GPU arrays.
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spaCy can be installed on GPU by specifying `spacy[cuda]`, `spacy[cuda90]`,
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`spacy[cuda91]`, `spacy[cuda92]` or `spacy[cuda100]`. If you know your cuda
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version, using the more explicit specifier allows cupy to be installed via
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wheel, saving some compilation time. The specifiers should install two
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libraries: [`cupy`](https://cupy.chainer.org) and
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[`thinc_gpu_ops`](https://github.com/explosion/thinc_gpu_ops).
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```bash
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$ pip install -U spacy[cuda92]
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```
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Once you have a GPU-enabled installation, the best way to activate it is to call
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[`spacy.prefer_gpu`](/api/top-level#spacy.prefer_gpu) or
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[`spacy.require_gpu()`](/api/top-level#spacy.require_gpu) somewhere in your
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script before any models have been loaded. `require_gpu` will raise an error if
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no GPU is available.
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```python
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import spacy
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spacy.prefer_gpu()
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nlp = spacy.load("en_core_web_sm")
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```
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### Compile from source {#source}
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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/),
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[virtualenv](https://virtualenv.pypa.io/) 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](#source-ubuntu), [macOS / OS X](#source-osx) and
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[Windows](#source-windows) for details.
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```bash
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python -m pip install -U pip # update pip
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git clone https://github.com/explosion/spaCy # clone spaCy
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cd spaCy # navigate into directory
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python -m venv .env # create environment in .env
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source .env/bin/activate # activate virtual environment
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\export PYTHONPATH=`pwd` # set Python path to spaCy directory
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pip install -r requirements.txt # install all requirements
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python setup.py build_ext --inplace # compile spaCy
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```
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Compared to regular install via pip, the
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[`requirements.txt`](https://github.com/explosion/spaCy/tree/master/requirements.txt)
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additionally installs developer dependencies such as Cython. See the the
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[quickstart widget](#quickstart) to get the right commands for your platform and
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Python version.
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#### Ubuntu {#source-ubuntu}
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Install system-level dependencies via `apt-get`:
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```bash
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$ sudo apt-get install build-essential python-dev git
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```
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#### macOS / OS X {#source-osx}
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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 {#source-windows}
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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
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[Visual Studio Express](https://www.visualstudio.com/vs/visual-studio-express/)
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that matches the version that was used to compile your Python interpreter. For
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official distributions these are:
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| Distribution | Version |
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| ------------ | ------------------ |
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| Python 2.7 | Visual Studio 2008 |
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| Python 3.4 | Visual Studio 2010 |
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| Python 3.5+ | Visual Studio 2015 |
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### Run tests
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spaCy comes with an
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[extensive test suite](https://github.com/explosion/spaCy/tree/master/spacy/tests).
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In order to run the tests, you'll usually want to clone the
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[repository](https://github.com/explosion/spaCy/tree/master/) and
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[build spaCy from source](#source). This will also install the required
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development dependencies and test utilities 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`](https://github.com/explosion/spaCy/tree/master/requirements.txt):
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```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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```
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Calling `pytest` on the spaCy directory will run only the basic tests. The flag
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`--slow` is optional and enables additional tests that take longer.
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```bash
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# make sure you are using recent pytest version
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python -m pip install -U pytest
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python -m pytest [spacy directory] # basic tests
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python -m pytest [spacy directory] --slow # basic and slow tests
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```
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## Troubleshooting guide {#troubleshooting}
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This section collects some of the most common errors you may come across when
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installing, loading and using spaCy, as well as their solutions.
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> #### Help us improve this guide
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>
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> Did you come across a problem like the ones listed here and want to share the
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> solution? You can find the "Suggest edits" button at the bottom of this page
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> that points you to the source. We always appreciate
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> [pull requests](https://github.com/explosion/spaCy/pulls)!
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<Accordion title="No compatible model found" id="compatible-model">
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```
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No compatible model found for [lang] (spaCy vX.X.X).
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```
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This usually means that the model you're trying to download does not exist, or
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isn't available for your version of spaCy. Check the
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[compatibility table](https://github.com/explosion/spacy-models/tree/master/compatibility.json)
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to see which models are available for your spaCy version. If you're using an old
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version, consider upgrading to the latest release. Note that while spaCy
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supports tokenization for [a variety of languages](/usage/models#languages), not
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all of them come with statistical models. To only use the tokenizer, import the
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language's `Language` class instead, for example
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`from spacy.lang.fr import French`.
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</Accordion>
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<Accordion title="Symbolic link privilege not held" id="symlink-privilege">
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```
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OSError: symbolic link privilege not held
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```
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To create [shortcut links](/usage/models#usage) that let you load models by
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name, spaCy creates a symbolic link in the `spacy/data` directory. This means
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your user needs permission to do this. The above error mostly occurs when doing
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a system-wide installation, which will create the symlinks in a system
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directory. Run the `download` or `link` command as administrator (on Windows,
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you can either right-click on your terminal or shell and select "Run as
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Administrator"), set the `--user` flag when installing a model or use a virtual
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environment to install spaCy in a user directory, instead of doing a system-wide
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installation.
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</Accordion>
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<Accordion title="No such option: --no-cache-dir" id="no-cache-dir">
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```
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no such option: --no-cache-dir
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```
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The `download` command uses pip to install the models and sets the
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`--no-cache-dir` flag to prevent it from requiring too much memory.
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[This setting](https://pip.pypa.io/en/stable/reference/pip_install/#caching)
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requires pip v6.0 or newer. Run `pip install -U pip` to upgrade to the latest
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version of pip. To see which version you have installed, run `pip --version`.
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</Accordion>
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<Accordion title="Unknown locale: UTF-8" id="unknown-locale">
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```
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ValueError: unknown locale: UTF-8
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```
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This error can sometimes occur on OSX and is likely related to a still
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unresolved [Python bug](https://bugs.python.org/issue18378). However, it's easy
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to fix: just add the following to your `~/.bash_profile` or `~/.zshrc` and then
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run `source ~/.bash_profile` or `source ~/.zshrc`. Make sure to add **both
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lines** for `LC_ALL` and `LANG`.
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```bash
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\export LC_ALL=en_US.UTF-8
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\export LANG=en_US.UTF-8
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```
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</Accordion>
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<Accordion title="Import error: No module named spacy" id="import-error">
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```
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Import Error: No module named spacy
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```
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This error means that the spaCy module can't be located on your system, or in
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your environment. Make sure you have spaCy installed. If you're using a virtual
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environment, make sure it's activated and check that spaCy is installed in that
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environment – otherwise, you're trying to load a system installation. You can
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also run `which python` to find out where your Python executable is located.
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</Accordion>
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<Accordion title="Import error: No module named [model]" id="import-error-models">
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```
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ImportError: No module named 'en_core_web_sm'
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```
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As of spaCy v1.7, all models can be installed as Python packages. This means
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that they'll become importable modules of your application. When creating
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[shortcut links](/usage/models#usage), spaCy will also try to import the model
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to load its meta data. If this fails, it's usually a sign that the package is
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not installed in the current environment. Run `pip list` or `pip freeze` to
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check which model packages you have installed, and install the
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[correct models](/models) if necessary. If you're importing a model manually at
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the top of a file, make sure to use the name of the package, not the shortcut
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link you've created.
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</Accordion>
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<Accordion title="Command not found: spacy" id="command-not-found">
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```
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command not found: spacy
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```
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This error may occur when running the `spacy` command from the command line.
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spaCy does not currently add an entry to your `PATH` environment variable, as
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this can lead to unexpected results, especially when using a virtual
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environment. Instead, spaCy adds an auto-alias that maps `spacy` to
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`python -m spacy]`. If this is not working as expected, run the command with
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`python -m`, yourself – for example `python -m spacy download en`. For more info
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on this, see the [`download`](/api/cli#download) command.
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</Accordion>
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<Accordion title="'module' object has no attribute 'load'" id="module-load">
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```
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AttributeError: 'module' object has no attribute 'load'
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```
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While this could technically have many causes, including spaCy being broken, the
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most likely one is that your script's file or directory name is "shadowing" the
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module – e.g. your file is called `spacy.py`, or a directory you're importing
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from is called `spacy`. So, when using spaCy, never call anything else `spacy`.
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</Accordion>
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<Accordion title="Pronoun lemma is returned as -PRON-" id="pron-lemma">
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```python
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doc = nlp(u"They are")
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print(doc[0].lemma_)
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# -PRON-
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```
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This is in fact expected behavior and not a bug. Unlike verbs and common nouns,
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there's no clear base form of a personal pronoun. Should the lemma of "me" be
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"I", or should we normalize person as well, giving "it" — or maybe "he"? spaCy's
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solution is to introduce a novel symbol, `-PRON-`, which is used as the lemma
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for all personal pronouns. For more info on this, see the
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[lemmatization specs](/api/annotation#lemmatization).
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</Accordion>
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<Accordion title="NER model doesn't recognise other entities anymore after training" id="catastrophic-forgetting">
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If your training data only contained new entities and you didn't mix in any
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examples the model previously recognized, it can cause the model to "forget"
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what it had previously learned. This is also referred to as the "catastrophic
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forgetting problem". A solution is to pre-label some text, and mix it with the
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new text in your updates. You can also do this by running spaCy over some text,
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extracting a bunch of entities the model previously recognized correctly, and
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adding them to your training examples.
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</Accordion>
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<Accordion title="Unhashable type: 'list'" id="unhashable-list">
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```
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TypeError: unhashable type: 'list'
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```
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If you're training models, writing them to disk, and versioning them with git,
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you might encounter this error when trying to load them in a Windows
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environment. This happens because a default install of Git for Windows is
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configured to automatically convert Unix-style end-of-line characters (LF) to
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Windows-style ones (CRLF) during file checkout (and the reverse when
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committing). While that's mostly fine for text files, a trained model written to
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disk has some binary files that should not go through this conversion. When they
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do, you get the error above. You can fix it by either changing your
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[`core.autocrlf`](https://git-scm.com/book/en/v2/Customizing-Git-Git-Configuration)
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setting to `"false"`, or by committing a
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[`.gitattributes`](https://git-scm.com/docs/gitattributes) file] to your
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repository to tell git on which files or folders it shouldn't do LF-to-CRLF
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conversion, with an entry like `path/to/spacy/model/** -text`. After you've done
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either of these, clone your repository again.
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</Accordion>
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## Changelog
|
||
|
||
import Changelog from 'widgets/changelog.js'
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|
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<Changelog />
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