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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)
• CSV (Sets)

Note that tablib purposefully excludes XML support. It always will. (Note: This is a joke. Pull requests are welcome.)

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, and CSV; they can be exported to XLSX, XLS, ODS, JSON, YAML, 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.

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]

Drumroll please...........

>>> print data.json
[
  {
    "last_name": "Adams",
    "age": 90,
    "first_name": "John"
  },
  {
    "last_name": "Ford",
    "age": 83,
    "first_name": "Henry"
  }
]

>>> print data.yaml
- {age: 90, first_name: John, last_name: Adams}
- {age: 83, first_name: Henry, last_name: Ford}

>>> print data.csv
first_name,last_name,age
John,Adams,90
Henry,Ford,83

>>> open('people.xls', 'wb').write(data.xls)

It's that easy.

To install tablib, simply: :

$ pip install tablib

Or, if you absolutely must: :

$ easy_install tablib

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.