Metadata-Version: 1.0
Name: Gloo
Version: 0.0.1
Summary: Project management for data analysis projects.
Home-page: http://pypi.python.org/pypi/Gloo/
Author: Trent Hauck
Author-email: trent@trenthauck.com
License: LICENSE.txt
Description: ==============
        ProjectManager
        ==============
        
        Provides utilities and functions for managing data projects in python.  Requires
        use of IPython and Pandas.
        
        A quick workflow example::
            
            from gloo import interactive    
        
            interactive.create_project("MyProject")
        
            #now if we have some some scripts to use and some data in the data folder we
            #can load the project
        
            interactive.load_project()
        
        Introduction
        ============
        
        Gloo's goal is to tie together a lot of the data analysis actions that happen
        regularly and make that processes easy.  Automatically loading data into the
        ipython environment, running scripts, making utitlity functions available.
        These are things that have to be done often, but aren't the fun part.
        
        What Happens When You Call create_project("MyProject")
        ---------------------------------------------------------
        
        ``create_project(project_name = "MyProject", **kwds)``
        
        ``project_name``: This is a string that is the name of your project.
        
        Current Config Options:
          ``full_structure`` A boolean that if true creates a full folder structure.  If
          True the folder structure outline below.  Defaults to True.
          
          ``packages`` A list of strings of python packages to load when
          ``load_project()`` is called.  Defaults to empty.
        
          ``logging`` A boolean to dictate if logging is started when
          ``load_project()`` is called.  Defaults to False.
        
          ``git`` A boolean to dictate if a git repo is init'd.  Defaults to False.
        
        Those options are saved into a json file called .config.json at the root of the
        project directory.
        
        What Happens When You Call load_project()
        -----------------------------------------
        
        ``load_project()``
        
        1.  The config is loaded into a dictionary.
        2.  Data is the ``data`` directory is loaded into the environment.  This is done
            recursively so you can have subdirectories.  If you do, the parent folder of
            the data file will be prepended to data file, ``folder_file``.  The plan is
            to make the prepending optional.
        3.  Files in the ``munge`` directory are run.  This folder is where you would
            put files necessary for preprocessing the data.
        4.  Files in the ``lib`` directory are imported.  This folder is where you would
            put files that you would like to load as a module.
        5.  Packages specified in the config are loaded into the environment.
        6.  Logging starts
        
        Folder Structure
        ----------------
        The full structure is as follows::
            
            data/        : data  
            doc/         : documentation  
            diagnostics/ : automatically check for data issues  
            graphs/      : graph domicile  
            lib/         : utility functions  
            munge/       : preprocessing scripts  
            profiling/   : benchmark performance  
            reports/     : reports you'll produce  
            tests/       : tests
            
        
        Contributing
        ============
        Because this project is in such an early state I would love for anybody and
        everybody to help contribute.  I think this could be very valuable for those
        working with python for data projets.
        
        Thanks
        ======
        This project is a bit of a rip-off or port (however nice you're feeling) of
        `Project Template <http://www.projecttemplate.net>`_, which if
        you're using R I would highly recommend.  It's fantastic.
        
Platform: UNKNOWN
