Metadata-Version: 1.1
Name: ticdat
Version: 0.2.4
Summary: An easy-to-use data library for developing mathematical engines
Home-page: https://github.com/opalytics/opalytics-ticdat
Author: Opalytics Inc
Author-email: snelson@opalytics.com
License: BSD 2-Clause
Description: 
        
        **ticdat** is an easy-to-use, lightweight, relational, data library. It
        provides a simple interface for defining a data schema, and a factory
        class for creating ``TicDat`` data objects that confirm to this schema.
        
        It is primarily intended to simplify the process of developing
        proof-of-concept mathematical engines that read from one schema and
        write to another. It provides easy routines for reading and/or writing
        an entire data set for a range of stand-alone file types (Excel, .csv,
        Access or SQLite). For Access or SQLite, it can be used as a very
        condensed representation of the database schema.
        
        For archiving test suites, ``ticdat`` is a useful way to convert data
        instances into .sql text files that can be archived in source code
        control systems.
        
        When primary keys are specified, each table is a dictionary of
        dictionaries. Otherwise, each table is an enumerable of dictionaries.
        The inner dictionaries are data rows indexed by field names (as in
        ``csv.DictReader/csv.DictWriter``).
        
        When foreign keys are specified, they can be used for a variety of purposes:
          - ``find_foreign_key_failures`` can find the data rows in child tables that fail
            to cross reference with their parent table.
          - ``obfusimplify`` can be used to cascade entity renaming throughout the data set.
            This can facilitate troubleshooting by shortening and simplifying entity
            names. It can also be used to anonymize data sets in order to remove
            proprietary information.
          - When ``enable_foreign_key_links`` is true, links are automatically created between
            the data rows of the parent table and the matching data rows of the child table.
        
        When default values are provided, unfrozen ``TicDat`` objects will use
        them during the addition of new rows. In general, unfrozen ``TicDat``
        data tables behave like a ``defaultdict``. There are a variety of other
        overrides to facilitate the addition of new data rows.
        
        Alternately, ``TicDat`` data objects can be frozen. This facilitates
        good software development by insuring that code that is supposed to read
        from a data set without editing it behaves properly.
        
        Finally, the "dict-of-dicts" representation of a table can be eschewed
        entirely in favor of ``pandas.DataFrame``. In this case, ``ticdat`` can
        be used as a shim library that facilitates schema level definitions and
        query abstraction for ``pandas`` developers.
        
        Although ``ticdat`` was specifically designed with Mixed Integer
        Programming data sets in mind, it can be used for rapidly developing a
        wide variety of mathematical engines. It facilitates creating one
        definition of your input data schema and one solve module, and reusing
        this same code, unchanged, on data from different sources. This
        "separation of model from data" enables a user to move easily from
        small, testing data sets to larger, more realistic examples. In
        addition, `Opalytics Inc <http://www.opalytics.com/>`__ (the developer
        of ``ticdat``) can support cloud deployments of solve engines that use
        ``ticdat`` data objects.
        	
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
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: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
