diff --git a/README.rst b/README.rst index 9eca8d0..df59abb 100644 --- a/README.rst +++ b/README.rst @@ -26,9 +26,16 @@ Import formats supported: - YAML (Sets + Books) - CSV (Sets) - Note that tablib *purposefully* excludes XML support. It always will. +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. + +`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. Usage ----- @@ -69,6 +76,9 @@ Easily delete rows: :: >>> del data[1] +Exports +------- + Drumroll please........... JSON! @@ -114,8 +124,41 @@ EXCEL! >>> open('people.xls', 'wb').write(data.xls) 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.yaml = '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 ------------ @@ -136,13 +179,10 @@ If you'd like to contribute, simply fork `the repository`_, commit your changes Roadmap ------- -- Import datasets from CSV. - Release CLI Interface - Auto-detect import format - Add possible other exports (SQL?) -- Possibly plugin-ify format architecture - Ability to assign types to rows (set, regex=, &c.) -- Plugin support .. _`the repository`: http://github.com/kennethreitz/tablib .. _AUTHORS: http://github.com/kennethreitz/tablib/blob/master/AUTHORS