Metadata-Version: 1.1
Name: Trump
Version: 0.0.1
Summary: Persistent Objectified Indexed Data
Home-page: http://Equitable.github.com/trump/
Author: Jeffrey McLarty
Author-email: jeffrey.mclarty@gmail.com
License: UNKNOWN
Download-URL: https://github.com/Equitable/trump/tarball/0.0.1
Description: =====
        Trump
        =====
        
        .. image:: https://badges.gitter.im/Join%20Chat.svg
           :alt: Join the chat at https://gitter.im/Equitable/trump
           :target: https://gitter.im/Equitable/trump?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
        
        .. image:: https://readthedocs.org/projects/trump/badge/?version=latest
           :target: https://readthedocs.org/projects/trump/?badge=latest
           :alt: Documentation Status
        
        ------------------------------------------
        Persistent Objectification of Indexed Data
        ------------------------------------------
        
        Trump is a framework for objectifying data, with the goal of centralizing the responsibility of 
        managing feeds, munging, calculating and validating data, upstream of any application or user requirement.
        
        With a focus on business processes, Trump's long run goals enable data feeds to be:
        
        * **Prioritized**, *flexibly* - a symbol can be associated with multiple data source for a variety of reasons including redundancy, calculations, or optionality.
        * **Modified**, *reliably* - a symbol's data feeds can be changed out, without any changes requiring testing to the downstream application or user.
        * **Verified**, *systematically* - a variety of common data processing checks are performed as the symbol's data is cached.
        * **Audited**, *quickly* - alerts and reports all become possible to assess integrity or inspect where manual over-rides have been performed.
        * **Aggregated**, *intelligently* - on a symbol by symbol basis, feeds can be combined and used in an extensible number of ways.
        * **Customized**, *dynamically* - extensibility is possible at the templating, munging, aggregation, and validity steps.
        
        Planning
        ========
        
        Trump is still in a planning stage.  Trump's initial priority is numeric and monotonic timeseries data,
        but written with the future in mind to eventually work with any sortable object as data, and any object as an index.
        Eliminating the monotonic assumption is a very low priority. 
        
        See `docs/planning.md <https://github.com/Equitable/trump/blob/master/docs/planning.md>`_ for the current state of the project.
        
        Basic Usage
        ===========
        This example dramatically understates the utility of Trump's long term feature set.
        
        Adding a Symbol
        ---------------
        
        .. code-block:: python
        
           from trump.orm import SymbolManager
           from trump.templating import fQuandl, fSQL
        
           sm = SymbolManager()
        
           oil = sm.create(name = "oil_front_month",
                           description = "Crude Oil",
                           freq = 'D',
                           units = '$ / barrel')
        
           oil.addTags(['commodity','oil','futures'])
        
           f1 = fQuandl(r"CHRIS/CME_CL2",fieldname='Settle')
           f2 = fSQL("SELECT date,data FROM test_oil_data;")
        
           oil.addFeed(f1)
           oil.addFeed(f2)
        
           oil.cache()
        
           print oil.df.tail()
           
        Using a Symbol
        --------------
        
        .. code-block:: python
        
           from trump.orm import SymbolManager
        
           sm = SymbolManager()
        
           oil = sm.get("oil_front_month")
        
           #optional
           oil.cache()
        
           print oil.df.tail()
        
        Installation
        ============
        
        See the latest `Installation instructions on ReadTheDocs.org <http://trump.readthedocs.org/en/latest/installation.html>`_
        
        Requirements
        ------------
        * Python 2.7; Support for Python 3.3 or 3.4 is do-able, if there is demand.
        * A relational database supported by SQLAlchemy.  The first database with guaranteed support is PostGreSQL.
        
        Dependencies
        ------------
        - `Pandas <http://pandas.pydata.org/>`_ (Tested with >= 15.2)
        - `SQLAlchemy <http://sqlalchemy.org/>`_ (Tested with >= 0.9)
        - `Smuggle <https://pypi.python.org/pypi/smuggle>`_ (Tested with >= 0.2.0)
        
        Data Source Dependencies
        ------------------------
        - `Quandl <https://pypi.python.org/pypi/Quandl>`_
        
        Documentation
        =============
        Read the latest on `ReadTheDocs.org <http://trump.readthedocs.org>`_
        
        Communication
        =============
        
        * Questions, Bugs, Ideas & Requests -> GitHub Issues or InvTech@equitable.ca
        * Contribute Code -> New Branch + GitHub Pull Request
        * Chat -> `Gitter <https://gitter.im/Equitable/trump>`_
        
        License
        =======
        BSD-3 clause.  See the actual `License <https://raw.githubusercontent.com/Equitable/trump/master/LICENSE.txt>`_.
        
        Background
        ==========
        The prototype for ``Trump`` was built at Equitable Life of Canada in 2014 by Jeffrey McLarty, CFA 
        and Derek Vinke, CFA. 
        
Keywords: data,timeseries,time series,indexed,objectified,trump,monotonic,RDD,relational database,pandas,SQLAlchemy
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Database
Classifier: Topic :: Office/Business
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
