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Format agnostic tabular data library (XLS, CSV, JSON, YAML, CSV)

Project description

Tablib: format-agnostic tabular dataset library

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Tablib is a format-agnostic tabular dataset library, written in Python. It is a full python module which doubles as a CLI application for quick dataset conversions.

Formats supported:

  • JSON
  • YAML
  • Excel
  • CSV

At this time, Tablib supports the export of it’s powerful Dataset object instances into any of the above formats. Import is underway.

Please note that tablib purposefully excludes XML support. It always will.

Features

Populate fresh data files:

headers = ('first_name', 'last_name', 'gpa')

data = [
    ('John', 'Adams', 4.0),
    ('George', 'Washington', 2.6),
    ('Henry', 'Ford', 2.3)
]

data = tablib.Dataset(*data, headers=headers)

# Establish file location and save
data.save('test.xls')

Intelligently add new rows:

data.append('Bob', 'Dylan', 3.2)

print data.headers
# >>> ('first_name', 'last_name', 'gpa')

Slice rows:

print data[0:1]
# >>> [('John', 'Adams', 4.0), ('George', 'Washington', 2.6)]

Slice columns by header:

print data['first_name']
# >>> ['John', 'George', 'Henry']

Manipulate rows by index:

del data[0]
print data[0:1]
# >>> [('George', 'Washington', 2.6), ('Henry', 'Ford', 2.3)]

Roadmap

  • Import datasets from CSV, JSON, YAML
  • Auto-detect import format
  • Plugin support

History

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.

Project details


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