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448 lines
22 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
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Cython. spaCy is built on the very latest research, but it isn't researchware.
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It was designed from day 1 to be used in real products. It's commercial
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open-source software, released under the MIT license.
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💫 **Version 1.1 out now!** `Read the release notes here. <https://github.com/explosion/spaCy/releases/>`_
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.. image:: http://i.imgur.com/wFvLZyJ.png
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:target: https://travis-ci.org/explosion/spaCy
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:alt: spaCy on Travis CI
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.. image:: https://travis-ci.org/explosion/spaCy.svg?branch=master
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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/github/release/explosion/spacy.svg
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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
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:target: https://pypi.python.org/pypi/spacy
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:alt: pypi Version
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.. image:: https://badges.gitter.im/spaCy-users.png
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:target: https://gitter.im/explosion/spaCy
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:alt: spaCy on Gitter
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📖 Documentation
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=============
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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| `Usage Workflows <https://spacy.io/docs/usage/>`_ | How to use spaCy and its features. |
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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| `API Reference <https://spacy.io/docs/api/>`_ | The detailed reference for spaCy's API. |
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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| `Tutorials <https://spacy.io/docs/usage/tutorials>`_ | End-to-end examples, with code you can modify and run. |
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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| `Showcase & Demos <https://spacy.io/docs/usage/showcase>`_ | Demos, libraries and products from the spaCy community. |
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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| `Contribute <https://github.com/explosion/spaCy/blob/master/CONTRIBUTING.md>`_ | How to contribute to the spaCy project and code base. |
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+--------------------------------------------------------------------------------+---------------------------------------------------------+
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💬 Where to ask questions
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==========================
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+---------------------------+------------------------------------------------------------------------------------------------------------+
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| **Bug reports** | `GitHub Issue tracker <https://github.com/explosion/spaCy/issues>`_ |
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+---------------------------+------------------------------------------------------------------------------------------------------------+
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| **Usage questions** | `StackOverflow <http://stackoverflow.com/questions/tagged/spacy>`_, `Reddit usergroup |
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| | <https://www.reddit.com/r/spacynlp>`_, `Gitter chat <https://gitter.im/explosion/spaCy>`_ |
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+---------------------------+------------------------------------------------------------------------------------------------------------+
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| **General discussion** | `Reddit usergroup <https://www.reddit.com/r/spacynlp>`_, |
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| | `Gitter chat <https://gitter.im/explosion/spaCy>`_ |
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+---------------------------+------------------------------------------------------------------------------------------------------------+
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| **Commercial support** | contact@explosion.ai |
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+---------------------------+------------------------------------------------------------------------------------------------------------+
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Features
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========
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* Non-destructive **tokenization**
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* Syntax-driven sentence segmentation
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* Pre-trained **word vectors**
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* Part-of-speech tagging
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* **Named entity** recognition
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* Labelled dependency parsing
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* Convenient string-to-int mapping
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* Export to numpy data arrays
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* GIL-free **multi-threading**
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* Efficient binary serialization
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* Easy **deep learning** integration
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* Statistical models for **English** and **German**
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* State-of-the-art speed
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* Robust, rigorously evaluated accuracy
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See `facts, figures and benchmarks <https://spacy.io/docs/api/>`_.
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Top Peformance
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==============
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* Fastest in the world: <50ms per document. No faster system has ever been
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announced.
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* Accuracy within 1% of the current state of the art on all tasks performed
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(parsing, named entity recognition, part-of-speech tagging). The only more
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accurate systems are an order of magnitude slower or more.
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Supports
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========
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* CPython 2.6, 2.7, 3.3, 3.4, 3.5 (only 64 bit)
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* macOS / OS X
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* Linux
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* Windows (Cygwin, MinGW, Visual Studio)
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Install spaCy
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=============
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spaCy is compatible with 64-bit CPython 2.6+/3.3+ and runs on Unix/Linux, OS X
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and Windows. Source packages are available via
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`pip <https://pypi.python.org/pypi/spacy>`_. Please make sure that
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you have a working build enviroment set up. See notes on Ubuntu, macOS/OS X and Windows
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for details.
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pip
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---
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When using pip it is generally recommended to install packages in a virtualenv to
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avoid modifying system state:
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.. code:: bash
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pip install spacy
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Python packaging is awkward at the best of times, and it's particularly tricky with
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C extensions, built via Cython, requiring large data files. So, please report issues
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as you encounter them.
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Install model
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=============
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After installation you need to download a language model. Currently only models for
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English and German, named ``en`` and ``de``, are available.
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.. code:: bash
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python -m spacy.en.download all
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python -m spacy.de.download all
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The download command fetches about 1 GB of data which it installs
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within the ``spacy`` package directory.
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Upgrading spaCy
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===============
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To upgrade spaCy to the latest release:
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pip
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---
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.. code:: bash
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pip install -U spacy
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Sometimes new releases require a new language model. Then you will have to upgrade to
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a new model, too. You can also force re-downloading and installing a new language model:
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.. code:: bash
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python -m spacy.en.download --force
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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 GitHub repository 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 enviroment consisting of a
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Python distribution including header files, a compiler, pip, virtualenv and git
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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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.. 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 virtualenv
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# find git install instructions at https://git-scm.com/downloads
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git clone https://github.com/explosion/spaCy.git
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cd spaCy
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virtualenv .env && source .env/bin/activate
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pip install -r requirements.txt
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pip install -e .
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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.
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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. First, find out where spaCy is
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installed:
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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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Then run ``pytest`` on that directory. The flags ``--vectors``, ``--slow``
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and ``--model`` are optional and enable additional tests:
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.. code:: 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> --vectors --model --slow
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Changelog
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=========
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2016-10-23 `v1.1.0 <https://github.com/explosion/spaCy/releases>`_: *Bug fixes and adjustments*
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-----------------------------------------------------------------------------------------------
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* Rename new ``pipeline`` keyword argument of ``spacy.load()`` to ``create_pipeline``.
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* Rename new ``vectors`` keyword argument of ``spacy.load()`` to ``add_vectors``.
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**🔴 Bug fixes**
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* Fix issue `#544 <https://github.com/explosion/spaCy/issues/544>`_: Add ``vocab.resize_vectors()`` method, to support changing to vectors of different dimensionality.
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* Fix issue `#536 <https://github.com/explosion/spaCy/issues/536>`_: Default probability was incorrect for OOV words.
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* Fix issue `#539 <https://github.com/explosion/spaCy/issues/539>`_: Unspecified encoding when opening some JSON files.
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* Fix issue `#541 <https://github.com/explosion/spaCy/issues/541>`_: GloVe vectors were being loaded incorrectly.
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* Fix issue `#522 <https://github.com/explosion/spaCy/issues/522>`_: Similarities and vector norms were calculated incorrectly.
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* Fix issue `#461 <https://github.com/explosion/spaCy/issues/461>`_: ``ent_iob`` attribute was incorrect after setting entities via ``doc.ents``
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* Fix issue `#459 <https://github.com/explosion/spaCy/issues/459>`_: Deserialiser failed on empty doc
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* Fix issue `#514 <https://github.com/explosion/spaCy/issues/514>`_: Serialization failed after adding a new entity label.
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2016-10-18 `v1.0.0 <https://github.com/explosion/spaCy/releases/tag/v1.0.0>`_: *Support for deep learning workflows and entity-aware rule matcher*
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--------------------------------------------------------------------------------------------------------------------------------------------------
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**✨ Major features and improvements**
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* **NEW:** `custom processing pipelines <https://spacy.io/docs/usage/customizing-pipeline>`_, to support deep learning workflows
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* **NEW:** `Rule matcher <https://spacy.io/docs/usage/rule-based-matching>`_ now supports entity IDs and attributes
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* **NEW:** Official/documented `training APIs <https://github.com/explosion/spaCy/tree/master/examples/training>`_ and `GoldParse` class
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* Download and use GloVe vectors by default
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* Make it easier to load and unload word vectors
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* Improved rule matching functionality
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* Move basic data into the code, rather than the json files. This makes it simpler to use the tokenizer without the models installed, and makes adding new languages much easier.
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* Replace file-system strings with ``Path`` objects. You can now load resources over your network, or do similar trickery, by passing any object that supports the ``Path`` protocol.
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**⚠️ Backwards incompatibilities**
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* The data_dir keyword argument of ``Language.__init__`` (and its subclasses ``English.__init__`` and ``German.__init__``) has been renamed to ``path``.
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* Details of how the Language base-class and its sub-classes are loaded, and how defaults are accessed, have been heavily changed. If you have your own subclasses, you should review the changes.
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* The deprecated ``token.repvec`` name has been removed.
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* The ``.train()`` method of Tagger and Parser has been renamed to ``.update()``
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* The previously undocumented ``GoldParse`` class has a new ``__init__()`` method. The old method has been preserved in ``GoldParse.from_annot_tuples()``.
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* Previously undocumented details of the ``Parser`` class have changed.
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* The previously undocumented ``get_package`` and ``get_package_by_name`` helper functions have been moved into a new module, ``spacy.deprecated``, in case you still need them while you update.
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**🔴 Bug fixes**
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* Fix ``get_lang_class`` bug when GloVe vectors are used.
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* Fix Issue `#411 <https://github.com/explosion/spaCy/issues/411>`_: ``doc.sents`` raised IndexError on empty string.
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* Fix Issue `#455 <https://github.com/explosion/spaCy/issues/455>`_: Correct lemmatization logic
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* Fix Issue `#371 <https://github.com/explosion/spaCy/issues/371>`_: Make ``Lexeme`` objects hashable
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* Fix Issue `#469 <https://github.com/explosion/spaCy/issues/469>`_: Make ``noun_chunks`` detect root NPs
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**👥 Contributors**
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Thanks to `@daylen <https://github.com/daylen>`_, `@RahulKulhari <https://github.com/RahulKulhari>`_, `@stared <https://github.com/stared>`_, `@adamhadani <https://github.com/adamhadani>`_, `@izeye <https://github.com/adamhadani>`_ and `@crawfordcomeaux <https://github.com/adamhadani>`_ for the pull requests!
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2016-05-10 `v0.101.0 <https://github.com/explosion/spaCy/releases/tag/0.101.0>`_: *Fixed German model*
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------------------------------------------------------------------------------------------------------
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* Fixed bug that prevented German parses from being deprojectivised.
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* Bug fixes to sentence boundary detection.
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* Add rich comparison methods to the Lexeme class.
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* Add missing ``Doc.has_vector`` and ``Span.has_vector`` properties.
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* Add missing ``Span.sent`` property.
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2016-05-05 `v0.100.7 <https://github.com/explosion/spaCy/releases/tag/0.100.7>`_: *German!*
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-------------------------------------------------------------------------------------------
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spaCy finally supports another language, in addition to English. We're lucky
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to have Wolfgang Seeker on the team, and the new German model is just the
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beginning. Now that there are multiple languages, you should consider loading
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spaCy via the ``load()`` function. This function also makes it easier to load extra
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word vector data for English:
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.. code:: python
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import spacy
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en_nlp = spacy.load('en', vectors='en_glove_cc_300_1m_vectors')
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de_nlp = spacy.load('de')
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To support use of the load function, there are also two new helper functions:
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``spacy.get_lang_class`` and ``spacy.set_lang_class``. Once the German model is
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loaded, you can use it just like the English model:
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.. code:: python
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doc = nlp(u'''Wikipedia ist ein Projekt zum Aufbau einer Enzyklopädie aus freien Inhalten, zu dem du mit deinem Wissen beitragen kannst. Seit Mai 2001 sind 1.936.257 Artikel in deutscher Sprache entstanden.''')
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for sent in doc.sents:
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print(sent.root.text, sent.root.n_lefts, sent.root.n_rights)
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# (u'ist', 1, 2)
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# (u'sind', 1, 3)
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The German model provides tokenization, POS tagging, sentence boundary detection,
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syntactic dependency parsing, recognition of organisation, location and person
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entities, and word vector representations trained on a mix of open subtitles and
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Wikipedia data. It doesn't yet provide lemmatisation or morphological analysis,
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and it doesn't yet recognise numeric entities such as numbers and dates.
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**Bugfixes**
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* spaCy < 0.100.7 had a bug in the semantics of the ``Token.__str__`` and ``Token.__unicode__`` built-ins: they included a trailing space.
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* Improve handling of "infixed" hyphens. Previously the tokenizer struggled with multiple hyphens, such as "well-to-do".
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* Improve handling of periods after mixed-case tokens
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* Improve lemmatization for English special-case tokens
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* Fix bug that allowed spaces to be treated as heads in the syntactic parse
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* Fix bug that led to inconsistent sentence boundaries before and after serialisation.
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* Fix bug from deserialising untagged documents.
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2016-03-08 `v0.100.6 <https://github.com/explosion/spaCy/releases/tag/0.100.6>`_: *Add support for GloVe vectors*
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-----------------------------------------------------------------------------------------------------------------
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This release offers improved support for replacing the word vectors used by spaCy.
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To install Stanford's GloVe vectors, trained on the Common Crawl, just run:
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.. code:: bash
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sputnik --name spacy install en_glove_cc_300_1m_vectors
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To reduce memory usage and loading time, we've trimmed the vocabulary down to 1m entries.
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This release also integrates all the code necessary for German parsing. A German model
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will be released shortly. To assist in multi-lingual processing, we've added a ``load()``
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function. To load the English model with the GloVe vectors:
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.. code:: python
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spacy.load('en', vectors='en_glove_cc_300_1m_vectors')
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2016-02-07 `v0.100.5 <https://github.com/explosion/spaCy/releases/tag/0.100.5>`_
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--------------------------------------------------------------------------------
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Fix incorrect use of header file, caused from problem with thinc
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2016-02-07 `v0.100.4 <https://github.com/explosion/spaCy/releases/tag/0.100.4>`_: *Fix OSX problem introduced in 0.100.3*
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-------------------------------------------------------------------------------------------------------------------------
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Small correction to right_edge calculation
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2016-02-06 `v0.100.3 <https://github.com/explosion/spaCy/releases/tag/0.100.3>`_
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--------------------------------------------------------------------------------
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Support multi-threading, via the ``.pipe`` method. spaCy now releases the GIL around the
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parser and entity recognizer, so systems that support OpenMP should be able to do
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shared memory parallelism at close to full efficiency.
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We've also greatly reduced loading time, and fixed a number of bugs.
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2016-01-21 `v0.100.2 <https://github.com/explosion/spaCy/releases/tag/0.100.2>`_
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--------------------------------------------------------------------------------
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Fix data version lock that affected v0.100.1
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2016-01-21 `v0.100.1 <https://github.com/explosion/spaCy/releases/tag/0.100.1>`_: *Fix install for OSX*
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-------------------------------------------------------------------------------------------------------
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v0.100 included header files built on Linux that caused installation to fail on OSX.
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This should now be corrected. We also update the default data distribution, to
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include a small fix to the tokenizer.
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2016-01-19 `v0.100 <https://github.com/explosion/spaCy/releases/tag/0.100>`_: *Revise setup.py, better model downloads, bug fixes*
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----------------------------------------------------------------------------------------------------------------------------------
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* Redo setup.py, and remove ugly headers_workaround hack. Should result in fewer install problems.
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* Update data downloading and installation functionality, by migrating to the Sputnik data-package manager. This will allow us to offer finer grained control of data installation in future.
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* Fix bug when using custom entity types in ``Matcher``. This should work by default when using the
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``English.__call__`` method of running the pipeline. If invoking ``Parser.__call__`` directly to do NER,
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you should call the ``Parser.add_label()`` method to register your entity type.
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* Fix head-finding rules in ``Span``.
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* Fix problem that caused ``doc.merge()`` to sometimes hang
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* Fix problems in handling of whitespace
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2015-11-08 `v0.99 <https://github.com/explosion/spaCy/releases/tag/0.99>`_: *Improve span merging, internal refactoring*
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------------------------------------------------------------------------------------------------------------------------
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* Merging multi-word tokens into one, via the ``doc.merge()`` and ``span.merge()`` methods, no longer invalidates existing ``Span`` objects. This makes it much easier to merge multiple spans, e.g. to merge all named entities, or all base noun phrases. Thanks to @andreasgrv for help on this patch.
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* Lots of internal refactoring, especially around the machine learning module, thinc. The thinc API has now been improved, and the spacy._ml wrapper module is no longer necessary.
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* The lemmatizer now lower-cases non-noun, noun-verb and non-adjective words.
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* A new attribute, ``.rank``, is added to Token and Lexeme objects, giving the frequency rank of the word.
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2015-11-03 `v0.98 <https://github.com/explosion/spaCy/releases/tag/0.98>`_: *Smaller package, bug fixes*
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---------------------------------------------------------------------------------------------------------
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* Remove binary data from PyPi package.
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* Delete archive after downloading data
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* Use updated cymem, preshed and thinc packages
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* Fix information loss in deserialize
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* Fix ``__str__`` methods for Python2
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2015-10-23 `v0.97 <https://github.com/explosion/spaCy/releases/tag/0.97>`_: *Load the StringStore from a json list, instead of a text file*
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-------------------------------------------------------------------------------------------------------------------------------------------
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* Fix bugs in download.py
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* Require ``--force`` to over-write the data directory in download.py
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* Fix bugs in ``Matcher`` and ``doc.merge()``
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2015-10-19 `v0.96 <https://github.com/explosion/spaCy/releases/tag/0.96>`_: *Hotfix to .merge method*
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-----------------------------------------------------------------------------------------------------
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* Fix bug that caused text to be lost after ``.merge``
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* Fix bug in Matcher when matched entities overlapped
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2015-10-18 `v0.95 <https://github.com/explosion/spaCy/releases/tag/0.95>`_: *Bugfixes*
|
||
--------------------------------------------------------------------------------------
|
||
|
||
* Reform encoding of symbols
|
||
* Fix bugs in ``Matcher``
|
||
* Fix bugs in ``Span``
|
||
* Add tokenizer rule to fix numeric range tokenization
|
||
* Add specific string-length cap in Tokenizer
|
||
* Fix ``token.conjuncts``
|
||
|
||
2015-10-09 `v0.94 <https://github.com/explosion/spaCy/releases/tag/0.94>`_
|
||
--------------------------------------------------------------------------
|
||
|
||
* Fix memory error that caused crashes on 32bit platforms
|
||
* Fix parse errors caused by smart quotes and em-dashes
|
||
|
||
2015-09-22 `v0.93 <https://github.com/explosion/spaCy/releases/tag/0.93>`_
|
||
--------------------------------------------------------------------------
|
||
|
||
Bug fixes to word vectors
|