Kenneth Reitz f8d8d3058a Hmm
2010-09-11 23:09:13 -04:00
2010-09-11 23:09:06 -04:00
2010-09-11 23:08:48 -04:00
2010-08-28 17:14:39 -04:00
2010-07-16 17:23:10 -04:00
2010-09-11 23:08:48 -04:00
MIT
2010-07-13 08:54:26 -04:00
Hmm
2010-09-11 23:09:13 -04:00
2010-08-28 20:47:03 -04:00
Hmm
2010-09-11 23:09:13 -04:00
2010-09-11 23:08:48 -04:00
2010-09-11 23:08:57 -04:00
2010-08-28 17:14:39 -04:00

Tabbed: format-agnostic tabular dataset library
===============================================

::

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    __  /_______ ____  /_ ___  /_ _____ ______  /
    _  __/_  __ `/__  __ \__  __ \_  _ \_  __  / 
    / /_  / /_/ / _  /_/ /_  /_/ //  __// /_/ /  
    \__/  \__,_/  /_.___/ /_.___/ \___/ \__,_/   

.. *Tabbed is under active documentation-driven development.*


Tabbed is a format-agnostic tabular dataset library, written in Python. 
It is a full python module which doubles as a CLI application for quick
dataset conversions. 

Formats supported:

- JSON
- YAML
- Excel
- CSV
.. - HTML

At this time, Tabbed supports the **export** of it's powerful Dataset object instances into any of the above formats. Import is underway.

Please note that tabbed *purposefully* excludes XML support. It always will.


Features
--------

    
Populate fresh data files: ::
    
    headers = ('first_name', 'last_name', 'gpa')

    data = [
        ('John', 'Adams', 4.0),
        ('George', 'Washington', 2.6),
        ('Henry', 'Ford', 2.3)
    ]
    
    data = tablib.Dataset(*data, headers=headers)

    # Establish file location and save
    data.save('test.xls')
    

Intelligently add new rows: ::

    data.append('Bob', 'Dylan', 3.2)
    
    print data.headers
    # >>> ('first_name', 'last_name', 'gpa')
    

Slice rows:  ::

    print data[0:1]
    # >>> [('John', 'Adams', 4.0), ('George', 'Washington', 2.6)]
    

Slice columns by header: ::

    print data['first_name']
    # >>> ['John', 'George', 'Henry']


Manipulate rows by index: ::

    del data[0]
    print data[0:1]
    # >>> [('George', 'Washington', 2.6), ('Henry', 'Ford', 2.3)]
    
    .. # Update saved file
    .. data.save()
    


Roadmap
-------
- Import datasets from CSV, JSON, YAML
- Auto-detect import format
- Plugin support
S
Description
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