Tablib: format-agnostic tabular dataset library
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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.)
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, 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.
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)
It's that easy.
Installation
To install tablib, simply:
$ pip install tablib
Or, if you absolutely must:
$ easy_install 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.