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tablib
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METADATA
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Metadata-Version: 2.0
Name: tablib
Version: 0.11.2
Summary: Format agnostic tabular data library (XLS, JSON, YAML, CSV)
Home-page: http://python-tablib.org
Author: Kenneth Reitz
Author-email: me@kennethreitz.org
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.5
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Tablib: format-agnostic tabular dataset library
===============================================
.. image:: https://travis-ci.org/kennethreitz/tablib.svg?branch=develop
:target: https://travis-ci.org/kennethreitz/tablib
::
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__ /_______ ____ /_ ___ /___(_)___ /_
_ __/_ __ `/__ __ \__ / __ / __ __ \
/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
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
History
-------
0.11.2 (2016-02-16)
+++++++++++++++++++
**Bugfixes**
- Fix export only formats.
- Fix for xlsx output.
0.11.1 (2016-02-07)
+++++++++++++++++++
**Bugfixes**
- Fixed packaging error on Python 3.
0.11.0 (2016-02-07)
+++++++++++++++++++
**New Formats!**
- Added LaTeX table export format (``Dataset.latex``).
- Support for dBase (DBF) files (``Dataset.dbf``).
**Improvements**
- New import/export interface (``Dataset.export()``, ``Dataset.load()``).
- CSV custom delimiter support (``Dataset.export('csv', delimiter='$')``).
- Adding ability to remove duplicates to all rows in a dataset (``Dataset.remove_duplicates()``).
- Added a mechanism to avoid ``datetime.datetime`` issues when serializing data.
- New ``detect_format()`` function (mostly for internal use).
- Update the vendored unicodecsv to fix ``None`` handling.
- Only freeze the headers row, not the headers columns (xls).
**Breaking Changes**
- ``detect()`` function removed.
**Bugfixes**
- Fix XLSX import.
- Bugfix for ``Dataset.transpose().transpose()``.
0.10.0 (2014-05-27)
+++++++++++++++++++
* Unicode Column Headers
* ALL the bugfixes!
0.9.11 (2011-06-30)
+++++++++++++++++++
* Bugfixes
0.9.10 (2011-06-22)
+++++++++++++++++++
* Bugfixes
0.9.9 (2011-06-21)
++++++++++++++++++
* Dataset API Changes
* ``stack_rows`` => ``stack``, ``stack_columns`` => ``stack_cols``
* column operations have their own methods now (``append_col``, ``insert_col``)
* List-style ``pop()``
* Redis-style ``rpush``, ``lpush``, ``rpop``, ``lpop``, ``rpush_col``, and ``lpush_col``
0.9.8 (2011-05-22)
++++++++++++++++++
* OpenDocument Spreadsheet support (.ods)
* Full Unicode TSV support
0.9.7 (2011-05-12)
++++++++++++++++++
* Full XLSX Support!
* Pickling Bugfix
* Compat Module
0.9.6 (2011-05-12)
++++++++++++++++++
* ``seperators`` renamed to ``separators``
* Full unicode CSV support
0.9.5 (2011-03-24)
++++++++++++++++++
* Python 3.1, Python 3.2 Support (same code base!)
* Formatter callback support
* Various bug fixes
0.9.4 (2011-02-18)
++++++++++++++++++
* Python 2.5 Support!
* Tox Testing for 2.5, 2.6, 2.7
* AnyJSON Integrated
* OrderedDict support
* Caved to community pressure (spaces)
0.9.3 (2011-01-31)
++++++++++++++++++
* Databook duplication leak fix.
* HTML Table output.
* Added column sorting.
0.9.2 (2010-11-17)
++++++++++++++++++
* Transpose method added to Datasets.
* New frozen top row in Excel output.
* Pickling support for Datasets and Rows.
* Support for row/column stacking.
0.9.1 (2010-11-04)
++++++++++++++++++
* Minor reference shadowing bugfix.
0.9.0 (2010-11-04)
++++++++++++++++++
* Massive documentation update!
* Tablib.org!
* Row tagging and Dataset filtering!
* Column insert/delete support
* Column append API change (header required)
* Internal Changes (Row object and use thereof)
0.8.5 (2010-10-06)
++++++++++++++++++
* New import system. All dependencies attempt to load from site-packages,
then fallback on tenderized modules.
0.8.4 (2010-10-04)
++++++++++++++++++
* Updated XLS output: Only wrap if '\\n' in cell.
0.8.3 (2010-10-04)
++++++++++++++++++
* Ability to append new column passing a callable
as the value that will be applied to every row.
0.8.2 (2010-10-04)
++++++++++++++++++
* Added alignment wrapping to written cells.
* Added separator support to XLS.
0.8.1 (2010-09-28)
++++++++++++++++++
* Packaging Fix
0.8.0 (2010-09-25)
++++++++++++++++++
* New format plugin system!
* Imports! ELEGANT Imports!
* Tests. Lots of tests.
0.7.1 (2010-09-20)
++++++++++++++++++
* Reverting methods back to properties.
* Windows bug compensated in documentation.
0.7.0 (2010-09-20)
++++++++++++++++++
* Renamed DataBook Databook for consistency.
* Export properties changed to methods (XLS filename / StringIO bug).
* Optional Dataset.xls(path='filename') support (for writing on windows).
* Added utf-8 on the worksheet level.
0.6.4 (2010-09-19)
++++++++++++++++++
* Updated unicode export for XLS.
* More exhaustive unit tests.
0.6.3 (2010-09-14)
++++++++++++++++++
* Added Dataset.append() support for columns.
0.6.2 (2010-09-13)
++++++++++++++++++
* Fixed Dataset.append() error on empty dataset.
* Updated Dataset.headers property w/ validation.
* Added Testing Fixtures.
0.6.1 (2010-09-12)
++++++++++++++++++
* Packaging hotfixes.
0.6.0 (2010-09-11)
++++++++++++++++++
* Public Release.
* Export Support for XLS, JSON, YAML, and CSV.
* DataBook Export for XLS, JSON, and YAML.
* Python Dict Property Support.