Metadata-Version: 1.1
Name: Trump
Version: 0.0.2
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/0.0.2
Description: =====
        Trump
        =====
        
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        ------------------------------------------
        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
        ========
        
        See `docs/planning.md <https://github.com/Equitable/trump/blob/master/docs/planning.md>`_ for the direction 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 QuandlFT, GoogleFinanceFT, YahooFinanceFT
        
           sm = SymbolManager()
        
           TSLA = sm.create(name = "TSLA", 
                            description = "Tesla Closing Price USD")
        
           TSLA.add_tags(["stocks","US"])
        
           #Try Google First
           #If Google's feed has a problem, try Quandl's backup
           #If all else fails, use Yahoo's data...
        
           TSLA.add_feed(GoogleFinanceFT("TSLA"))
           TSLA.add_feed(QuandlFT("GOOG/NASDAQ_TSLA",fieldname='Close'))
           TSLA.add_feed(YahooFinanceFT("TSLA"))
        
           #Optional munging, validity checks and aggregation settings would be
           #implemented here...
           
           #All three feeds are cached...
           TSLA.cache()
        
           #But only a clean version of the data is served up...
           print TSLA.df.tail()
        
                         TSLA
           dateindex         
           2015-03-20  198.08
           2015-03-23  199.63
           2015-03-24  201.72
           2015-03-25  194.30
           2015-03-26  190.40 
           
           sm.finish()
           
        Using a Symbol
        --------------
        
        .. code-block:: python
        
           from trump.orm import SymbolManager
        
           sm = SymbolManager()
        
           TSLA = sm.get("TSLA")
        
           #optional
           TSLA.cache()
        
           print TSLA.df.tail()
           
                         TSLA
           dateindex         
           2015-03-20  198.08
           2015-03-23  199.63
           2015-03-24  201.72
           2015-03-25  194.30
           2015-03-26  190.40  
        
           sm.finish()
        
           
        Installation
        ============
        
        See the latest `Installation instructions on ReadTheDocs.org <http://trump.readthedocs.org/en/latest/install.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 should work, however the following is tested:
          * PostgreSQL 9.4
          * Persistent SQLite (ie, file-based).  Certain features of Trump, wouldn't make sense with an in-memory implementation)
        
        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 or just say "Hi" -> GitHub Issues, InvTech@equitable.ca, or jeffrey.mclarty@gmail.com
        * 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. Jeffrey McLarty currently leads the Open Source initiative.
        
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
