Metadata-Version: 1.1
Name: fast-curator
Version: 0.7.0
Summary: F.A.S.T. package for describing datasets
Home-page: https://github.com/FAST-HEP/fast-curator
Author: F.A.S.T
Author-email: fast-hep@cern.ch
License: Apache Software License 2.0
Description: 
        
        .. image:: https://img.shields.io/pypi/v/fast-curator.svg
           :target: https://pypi.org/project/fast-curator/
           :alt: pypi package
        
        
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           :target: https://travis-ci.com/FAST-HEP/fast-curator
           :alt: pipeline status
        
        
        .. image:: https://codecov.io/gh/FAST-HEP/fast-curator/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/FAST-HEP/fast-curator
           :alt: coverage report
        
        
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        fast-curator
        =============
        Create, read and write dictionary descriptions of input datasets to process.
        Currently all datasets are expected to be built from sets of ROOT Trees.
        
        
        Installing
        ----------
        .. code-block:: bash
        
                pip install --user fast-curator
        
        Usage
        -----
        .. code-block:: bash
        
                # Local files:
                fast_curator -o output_file_list.txt -t tree_name -d dataset_name --mc input/files/*root
        
                # Single XROOTD files:
                fast_curator -o output_file_list.txt --mc root://my.domain.with.files://input/files/one_file.root
        
                # XROOTD files with several globs
                fast_curator -o output_file_list.txt --mc root://my.domain.with.files://inp*/files/*.root
        
        
        Notes:
        1. If the command is called multiple times with the same output file (using the ``-o`` option), the additional files specified will be appended to the output file.
        2. Arbitrary meta-data (such as cross-section, data quality, generator precision, etc) can be added to each dataset with the ``-m`` option.
        
        For more guidance try the built-in help::
        
                fast_curator --help
        
        Reading dataset files back
        --------------------------
        .. code-block:: python
        
                import fast_curator
                datasets = fast_curator.read.from_yaml("my_dataset_file.yml")
        
        Will return a list of datasets with the ``default`` section applied to each dataset.
        
        Further Documentation
        ---------------------
        Is on its way...
        
Keywords: ROOT,analysis,particle physics,HEP,F.A.S.T
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
