Metadata-Version: 1.2
Name: camel-tools
Version: 1.4.1
Summary: A suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.
Home-page: https://github.com/CAMeL-Lab/CAMeL_Tools
Author: Ossama W. Obeid
Author-email: oobeid@nyu.edu
Maintainer: Ossama W. Obeid
Maintainer-email: oobeid@nyu.edu
License: MIT
Description: CAMeL Tools
        ===========
        
        
        .. image:: https://img.shields.io/pypi/v/camel-tools.svg
           :target: https://pypi.org/project/camel-tools
           :alt: PyPI Version
        
        .. image:: https://img.shields.io/pypi/pyversions/camel-tools.svg
           :target: https://pypi.org/project/camel-tools
           :alt: PyPI Python Version
        
        .. image:: https://readthedocs.org/projects/camel-tools/badge/?version=latest
           :target: https://camel-tools.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        .. image:: https://img.shields.io/pypi/l/camel-tools.svg
           :target: https://opensource.org/licenses/MIT
           :alt: MIT License
        
        |
        
        .. image:: camel_tools_logo.png
           :target: camel_tools_logo.png
           :alt: CAMeL Tools Logo
        
        
        Introduction
        ------------
        
        CAMeL Tools is  suite of Arabic natural language processing tools developed by
        the
        `CAMeL Lab <http://camel-lab.com>`_
        at `New York University Abu Dhabi <http://nyuad.nyu.edu/>`_.
        
            **Please use** `GitHub Issues <https://github.com/CAMeL-Lab/camel_tools/issues>`_
            **to report a bug or if you need help using CAMeL Tools.**
        
        
        Installation
        ------------
        
        You will need Python 3.7 and above (64-bit) as well as
        `the Rust compiler <https://www.rust-lang.org/learn/get-started>`_ installed.
        
        Linux/macOS
        ~~~~~~~~~~~
        
        .. _linux-macos-install-pip:
        
        Install using pip
        ^^^^^^^^^^^^^^^^^
        
        .. code-block:: bash
        
           pip install camel-tools
        
           # or run the following if you already have camel_tools installed
           pip install camel-tools --upgrade
        
        
        .. _linux-macos-install-source:
        
        Install from source
        ^^^^^^^^^^^^^^^^^^^
        
        .. code-block:: bash
        
           # Clone the repo
           git clone https://github.com/CAMeL-Lab/camel_tools.git
           cd camel_tools
        
           # Install from source
           pip install .
        
           # or run the following if you already have camel_tools installed
           pip install --upgrade .
        
        .. _linux-macos-install-data:
        
        Installing data
        ^^^^^^^^^^^^^^^
        
        To install the datasets required by CAMeL Tools components run one of the
        following:
        
        .. code-block:: bash
        
           # To install all datasets
           camel_data -i all
        
           # or just the datasets for morphology and MLE disambiguation only
           camel_data -i light
        
           # or just the default datasets for each component
           camel_data -i defaults
        
        See `Available Packages <https://camel-tools.readthedocs.io/en/latest/reference/packages.html>`_
        for a list of all available datasets.
        
        By default, data is stored in ``~/.camel_tools``.
        Alternatively, if you would like to install the data in a different location,
        you need to set the :code:`CAMELTOOLS_DATA` environment variable to the desired
        path.
        
        Add the following to your :code:`.bashrc`, :code:`.zshrc`, :code:`.profile`,
        etc:
        
        .. code-block:: bash
        
           export CAMELTOOLS_DATA=/path/to/camel_tools_data
        
        Windows
        ~~~~~~~
        
        **Note:** CAMeL Tools has been tested on Windows 10. The Dialect Identification
        component is not available on Windows at this time.
        
        .. _windows-install-pip:
        
        Install using pip
        ^^^^^^^^^^^^^^^^^
        
        .. code-block:: bash
        
           pip install camel-tools -f https://download.pytorch.org/whl/torch_stable.html
        
           # or run the following if you already have camel_tools installed
           pip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html camel-tools
        
        .. _windows-install-source:
        
        Install from source
        ^^^^^^^^^^^^^^^^^^^
        
        .. code-block:: bash
        
           # Clone the repo
           git clone https://github.com/CAMeL-Lab/camel_tools.git
           cd camel_tools
        
           # Install from source
           pip install -f https://download.pytorch.org/whl/torch_stable.html .
           pip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html .
        
        .. _windows-install-data:
        
        Installing data
        ^^^^^^^^^^^^^^^
        
        To install the data packages required by CAMeL Tools components, run one of the
        following commands:
        
        .. code-block:: bash
        
           # To install all datasets
           camel_data -i all
        
           # or just the datasets for morphology and MLE disambiguation only
           camel_data -i light
        
           # or just the default datasets for each component
           camel_data -i defaults
        
        See `Available Packages <https://camel-tools.readthedocs.io/en/latest/reference/packages.html>`_
        for a list of all available datasets.
        
        By default, data is stored in
        ``C:\Users\your_user_name\AppData\Roaming\camel_tools``.
        Alternatively, if you would like to install the data in a different location,
        you need to set the ``CAMELTOOLS_DATA`` environment variable to the desired
        path. Below are the instructions to do so (on Windows 10):
        
        * Press the **Windows** button and type ``env``.
        * Click on **Edit the system environment variables (Control panel)**.
        * Click on the **Environment Variables...** button.
        * Click on the **New...** button under the **User variables** panel.
        * Type ``CAMELTOOLS_DATA`` in the **Variable name** input box and the
          desired data path in **Variable value**. Alternatively, you can browse for the
          data directory by clicking on the **Browse Directory...** button.
        * Click **OK** on all the opened windows.
        
        
        Documentation
        -------------
        
        To get started, you can follow along
        `the Guided Tour <https://colab.research.google.com/drive/1Y3qCbD6Gw1KEw-lixQx1rI6WlyWnrnDS?usp=sharing>`_
        for a quick overview of the components provided by CAMeL Tools.
        
        You can find the
        `full online documentation here <https://camel-tools.readthedocs.io/en/stable/>`_ for both
        the command-line tools and the Python API.
        
        Alternatively, you can build your own local copy of the documentation as
        follows:
        
        .. code-block:: bash
        
           # Install dependencies
           pip install sphinx recommonmark sphinx-rtd-theme
        
           # Go to docs subdirectory
           cd docs
        
           # Build HTML docs
           make html
        
        This should compile all the HTML documentation in to ``docs/build/html``.
        
        
        Citation
        --------
        
        If you find CAMeL Tools useful in your research, please cite
        `our paper <https://www.aclweb.org/anthology/2020.lrec-1.868/>`_:
        
        .. code-block:: bibtex
        
           @inproceedings{obeid-etal-2020-camel,
              title = "{CAM}e{L} Tools: An Open Source Python Toolkit for {A}rabic Natural Language Processing",
              author = "Obeid, Ossama  and
                 Zalmout, Nasser  and
                 Khalifa, Salam  and
                 Taji, Dima  and
                 Oudah, Mai  and
                 Alhafni, Bashar  and
                 Inoue, Go  and
                 Eryani, Fadhl  and
                 Erdmann, Alexander  and
                 Habash, Nizar",
              booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
              month = may,
              year = "2020",
              address = "Marseille, France",
              publisher = "European Language Resources Association",
              url = "https://www.aclweb.org/anthology/2020.lrec-1.868",
              pages = "7022--7032",
              abstract = "We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python. CAMeL Tools currently provides utilities for pre-processing, morphological modeling, Dialect Identification, Named Entity Recognition and Sentiment Analysis. In this paper, we describe the design of CAMeL Tools and the functionalities it provides.",
              language = "English",
              ISBN = "979-10-95546-34-4",
           }
        
        
        License
        -------
        
        CAMeL Tools is available under the MIT license.
        See the `LICENSE file
        <https://github.com/CAMeL-Lab/camel_tools/blob/master/LICENSE>`_
        for more info.
        
        
        Contribute
        ----------
        
        If you would like to contribute to CAMeL Tools, please read the
        `CONTRIBUTE.rst
        <https://github.com/CAMeL-Lab/camel_tools/blob/master/CONTRIBUTING.rst>`_
        file.
        
        
        Contributors
        ------------
        
        * `Ossama Obeid <https://github.com/owo>`_
        * `Go Inoue <https://github.com/go-inoue>`_
        * `Bashar Alhafni <https://github.com/balhafni>`_
        * `Salam Khalifa <https://github.com/slkh>`_
        * `Dima Taji <https://github.com/dima-taji>`_
        * `Nasser Zalmout <https://github.com/nzal>`_
        * `Nizar Habash <https://github.com/nizarhabash1>`_
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: Arabic
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Linguistic
Requires-Python: >=3.7.0, <3.10.*
