Metadata-Version: 2.1
Name: giotto-time
Version: 0.2.0
Summary: Toolbox for Time Series analysis and integration with Machine Learning.
Home-page: https://github.com/giotto-ai/giotto-time
Maintainer: Alessio Baccelli
Maintainer-email: maintainers@giotto.ai
License: AGPLv3
Download-URL: https://github.com/giotto-ai/giotto-time/tarball/v0.0a0
Description: .. image:: https://www.giotto.ai/static/vector/logo.svg
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        giotto-time
        ===========
        
        giotto-time is a machine learning based time series forecasting toolbox in Python.
        It is part of the `Giotto <https://github.com/giotto-ai>`_ family of open-source projects.
        
        Project genesis
        ---------------
        
        giotto-time was created to provide time series feature extraction, analysis and
        forecasting tools based on scikit-learn API.
        
        Documentation
        -------------
        
        - API reference (stable release): https://docs-time.giotto.ai
        
        Getting started
        ---------------
        
        Get started with giotto-time by following the installation steps below.
        Simple tutorials and real-world use cases can be found in example folder as notebooks.
        
        Installation
        ------------
        
        Dependencies
        ~~~~~~~~~~~~
        
        The latest stable version of giotto-time requires:
        
        - Python (>= 3.6)
        - scikit-learn (>= 0.22.0)
        - pandas>=0.25.3
        - workalendar>=7.1.1
        
        To run the examples, jupyter is required.
        
        User installation
        ~~~~~~~~~~~~~~~~~
        
        Linux, MacOS and Windows
        ''''''''''''''''''''''''
        Run this command in your favourite python environment  ::
        
            pip install giotto-time
        
        Contributing
        ------------
        
        We welcome new contributors of all experience levels. The Giotto
        community goals are to be helpful, welcoming, and effective. To learn more about
        making a contribution to giotto-time, please see the `CONTRIBUTING.rst
        <https://github.com/giotto-ai/giotto-time/blob/master/CONTRIBUTING.rst>`_ file.
        
        Developer installation
        ~~~~~~~~~~~~~~~~~~~~~~
        
        Source code
        '''''''''''
        
        You can obtain the latest state of the source code with the command  ::
        
            git clone https://github.com/giotto-ai/giotto-time.git
        
        
        then run
        
        .. code-block:: bash
        
           cd giotto-time
           pip install -e ".[tests, doc]"
        
        This way, you can pull the library's latest changes and make them immediately available on your machine.
        Note: we recommend upgrading ``pip`` and ``setuptools`` to recent versions before installing in this way.
        
        Testing
        ~~~~~~~
        
        After installation, you can launch the test suite from outside the
        source directory::
        
            pytest gtime
        
        
        Changelog
        ---------
        
        See the `RELEASE.rst <https://github.com/giotto-ai/giotto-time/blob/master/RELEASE.rst>`__ file
        for a history of notable changes to giotto-time.
        
        Important links
        ~~~~~~~~~~~~~~~
        
        - Official source code repo: https://github.com/giotto-ai/giotto-time
        - Download releases: https://pypi.org/project/giotto-time/
        - Issue tracker: https://github.com/giotto-ai/giotto-time/issues
        
        Community
        ---------
        
        Giotto Slack workspace: https://slack.giotto.ai/
        
        Contacts
        --------
        
        maintainers@giotto.ai
        
Keywords: machine learning time series data analysis topology,persistence diagrams
Platform: UNKNOWN
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/x-rst
Provides-Extra: tests
Provides-Extra: doc
Provides-Extra: examples
