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Readme.rst improvements

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Kenneth Reitz
2011-02-13 21:11:02 -05:00
parent ca77ed6f64
commit f69a96f07e
1 changed files with 2 additions and 42 deletions
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@@ -22,20 +22,13 @@ Output formats supported:
- TSV (Sets)
- CSV (Sets)
Import formats supported:
- JSON (Sets + Books)
- YAML (Sets + Books)
- TSV (Sets)
- CSV (Sets)
Note that tablib *purposefully* excludes XML support. It always will.
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 maniuplated as raw Python datatypes (Lists of tuples|dictonaries). Datasets can be imported from JSON, YAML, and CSV; they can be exported to Excel (XLS), JSON, YAML, and CSV.
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 Excel (XLS), JSON, YAML, and CSV.
`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 Excel (XLS), JSON, and YAML.
@@ -128,39 +121,6 @@ EXCEL!
It's that easy.
Imports!
--------
JSON
++++
::
>>> data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
>>> print data[0]
('John', 'Adams', 90)
YAML
++++
::
>>> data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
>>> print data[0]
('John', 'Adams', 90)
CSV
+++
::
>>> data.csv = 'age, first_name, last_name\n90, John, Adams'
>>> print data[0]
('John', 'Adams', 90)
>>> print data.yaml
- {age: 90, first_name: John, last_name: Adams}
Installation
------------