Metadata-Version: 1.1
Name: coda
Version: 0.0.6
Summary: File metadata tagging and organization.
Home-page: https://github.com/bprinty/coda
Author: Blake Printy
Author-email: bprinty@gmail.com
License: Apache-2.0
Description: coda
        ====
        
        Coda is a file system organizer, designed for data scientists who frequently deal
        with large amounts of heterogeneous data. In this age where data rules all, being able to
        efficiently search and label those data is paramount to maintaining productivity. Coda
        allows you to tag files with arbitrary metadata, so that you can stay organized when
        managing/analyzing large datasets over time. 
        
        As a quick example of how coda might be useful for organizing an arbitrary dataset,
        see the following example (see the `documentation <http://coda.readthedocs.io/en/latest/>`_
        for more in-depth documentation):
        
        .. code-block:: python
        
            >>> import coda
            >>>
            >>> # generate a collection of files from a directory
            >>> cl = coda.Collection('/path/to/test/data')
            >>>
            >>> # show all of the files in the structure
            >>> print cl
            /path/to/test/data/type1.txt
            /path/to/test/data/type1.csv
            /path/to/test/data/type2.txt
            /path/to/test/data/type2.csv
            >>>
            >>> # set properties about the collection
            >>> cl.group = 'test'
            >>> cl.cohort = 'My Cohort'
            >>>
            >>> # add the files in the collection to the database
            >>> # for tracking and retrieval later
            >>> coda.add(cl)
            >>>
            >>> # do the same with a training dataset
            >>> cl = coda.Collection('/path/to/train/data', metadata={'group': 'train'})
            >>> coda.add(cl)
            >>>
            >>> # wait ... add one more file in a different location to
            >>> # the training set
            >>> fi = coda.File('/my/special/training/file.csv')
            >>> fi.group = 'train'
            >>> coda.add(fi)
            >>>
            >>> # ... later in time ...
            >>>
            >>> # query all of our training files
            >>> cl = coda.find({'group': 'train'})
            >>> print cl
            /path/to/train/data/type1.txt
            /path/to/train/data/type1.csv
            /path/to/train/data/type2.txt
            /path/to/train/data/type2.csv
            /my/special/training/file.csv
            >>>
            >>> # filter those by csv files
            >>> print cl.filter(lambda x: '.csv' in x.name)
            /path/to/train/data/type1.csv
            /path/to/train/data/type2.csv
            /my/special/training/file.csv
            >>>
            >>> # tag the special file with new metadata
            >>> cl.files[-1].special = True
            >>> coda.add(cl.files[-1])
            >>>
            >>> # query it back (for the example)
            >>> fi = coda.find_one({'special': True})
            >>> print fi.metadata
            {'group': 'train', 'special': True}
        
        
        Documentation
        -------------
        
        For installation and usage instructions please see the `documentation <http://coda.readthedocs.io/en/latest/>`_.
        
        
        Questions/Feedback
        ------------------
        
        File an issue in the `GitHub issue tracker <https://github.com/bprinty/coda/issues>`_.
        
Keywords: coda,data,science,analysis,file,organization,metadata
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
