Metadata-Version: 2.1
Name: daops
Version: 0.5.0
Summary: daops - data-aware operations
Home-page: https://github.com/roocs/daops
Author: Elle Smith
Author-email: eleanor.smith@stfc.ac.uk
License: BSD
Description: 
        daops - data-aware operations
        =============================
        
        
        .. image:: https://img.shields.io/pypi/v/daops.svg
           :target: https://pypi.python.org/pypi/daops
           :alt: Pypi
        
        
        
        .. image:: https://github.com/roocs/daops/workflows/build/badge.svg
            :target: https://github.com/roocs/daops/actions
            :alt: Build Status
        
        
        
        .. image:: https://readthedocs.org/projects/daops/badge/?version=latest
           :target: https://daops.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation
        
        
        The ``daops`` library (pronounced "day-ops") provides a python interface to a
        set of operations suitable for working with climate simulation outputs. It is
        typically used with ESGF data sets that are described in NetCDF files. ``daops``
        is unique in that it accesses a store of *fixes* defined for datasets that are
        irregular when compared with others in their *population*.
        
        When a ``daops`` operation, such as ``subset``\ , is requested, the library will look
        up a database of known fixes before performing and calculations or transformations.
        The data will be loaded and *fixed* using the `xarray <http://xarray.pydata.org/>`_
        library before the any actual operations are sent to its sister library
        `clisops <https://github.com/roocs/clisops>`_.
        
        
        * Free software: BSD
        * Documentation: https://daops.readthedocs.io
        
        Features
        --------
        
        The package has the following features:
        
        
        * Ability to run *data-reduction* operations on large climate data sets.
        * Knowledge of irregularities/anomalies in some climate data sets.
        * Ability to apply *fixes* to those data sets before operating on them.
          This process is called *normalisation* of the data sets.
        
        Credits
        =======
        
        This package was created with ``Cookiecutter`` and the ``cedadev/cookiecutter-pypackage`` project template.
        
        
        * Cookiecutter: https://github.com/audreyr/cookiecutter
        * cookiecutter-pypackage: https://github.com/cedadev/cookiecutter-pypackage
        
        
        .. image:: https://img.shields.io/badge/code%20style-black-000000.svg
           :target: https://github.com/python/black
           :alt: Python Black
        
Keywords: daops
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Security
Classifier: Topic :: Internet
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: System :: Systems Administration :: Authentication/Directory
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6.0
Description-Content-Type: text/x-rst
Provides-Extra: docs
