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Tablib: format-agnostic tabular dataset library
===============================================
.. image:: https://travis-ci.org/kennethreitz/tablib.svg?branch=develop
:target: https://travis-ci.org/kennethreitz/tablib
::
_____ ______ ___________ ______
__ /_______ ____ /_ ___ /___(_)___ /_
_ __/_ __ `/__ __ \__ / __ / __ __ \
/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
Tablib is a format-agnostic tabular dataset library, written in Python.
Output formats supported:
- Excel (Sets + Books)
- JSON (Sets + Books)
- YAML (Sets + Books)
- HTML (Sets)
- TSV (Sets)
- OSD (Sets)
- CSV (Sets)
- DBF (Sets)
Note that tablib *purposefully* excludes XML support. It always will. (Note: This is a joke. Pull requests are welcome.)
Overview
--------
`tablib.Dataset()`
A Dataset is a table of tabular data. It may or may not have a header row. They can be build and manipulated as raw Python datatypes (Lists of tuples|dictionaries). Datasets can be imported from JSON, YAML, DBF, and CSV; they can be exported to XLSX, XLS, ODS, JSON, YAML, DBF, CSV, TSV, and HTML.
`tablib.Databook()`
A Databook is a set of Datasets. The most common form of a Databook is an Excel file with multiple spreadsheets. Databooks can be imported from JSON and YAML; they can be exported to XLSX, XLS, ODS, JSON, and YAML.
Usage
-----
Populate fresh data files: ::
headers = ('first_name', 'last_name')
data = [
('John', 'Adams'),
('George', 'Washington')
]
data = tablib.Dataset(*data, headers=headers)
Intelligently add new rows: ::
>>> data.append(('Henry', 'Ford'))
Intelligently add new columns: ::
>>> data.append_col((90, 67, 83), header='age')
Slice rows: ::
>>> print data[:2]
[('John', 'Adams', 90), ('George', 'Washington', 67)]
Slice columns by header: ::
>>> print data['first_name']
['John', 'George', 'Henry']
Easily delete rows: ::
>>> del data[1]
Exports
-------
Drumroll please...........
JSON!
+++++
::
>>> print data.json
[
{
"last_name": "Adams",
"age": 90,
"first_name": "John"
},
{
"last_name": "Ford",
"age": 83,
"first_name": "Henry"
}
]
YAML!
+++++
::
>>> print data.yaml
- {age: 90, first_name: John, last_name: Adams}
- {age: 83, first_name: Henry, last_name: Ford}
CSV...
++++++
::
>>> print data.csv
first_name,last_name,age
John,Adams,90
Henry,Ford,83
EXCEL!
++++++
::
>>> with open('people.xls', 'wb') as f:
... f.write(data.xls)
DBF!
++++
::
>>> with open('people.dbf', 'wb') as f:
... f.write(data.dbf)
It's that easy.
Installation
------------
To install tablib, simply: ::
$ pip install tablib
Make sure to check out `Tablib on PyPi <https://pypi.python.org/pypi/tablib/>`_!
Contribute
----------
If you'd like to contribute, simply fork `the repository`_, commit your
changes to the **develop** branch (or branch off of it), and send a pull
request. Make sure you add yourself to AUTHORS_.
.. _`the repository`: http://github.com/kennethreitz/tablib
.. _AUTHORS: http://github.com/kennethreitz/tablib/blob/master/AUTHORS
|
