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Kenneth Reitz
83 lines
1.7 KiB
ReStructuredText
83 lines
1.7 KiB
ReStructuredText
Tablib: format-agnostic tabular dataset library
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===============================================
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::
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_____ ______ ___________ ______
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__ /_______ ____ /_ ___ /___(_)___ /_
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_ __/_ __ `/__ __ \__ / __ / __ __ \
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/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
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\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
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Tablib is a format-agnostic tabular dataset library, written in Python.
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It is a full python module which doubles as a CLI application for quick
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dataset conversions.
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Formats supported:
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- JSON
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- YAML
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- Excel
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- CSV
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At this time, Tablib supports the **export** of it's powerful Dataset object instances into any of the above formats. Import is underway.
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Please note that tablib *purposefully* excludes XML support. It always will.
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Features
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--------
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Populate fresh data files: ::
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headers = ('first_name', 'last_name', 'gpa')
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data = [
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('John', 'Adams', 4.0),
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('George', 'Washington', 2.6),
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('Henry', 'Ford', 2.3)
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]
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data = tablib.Dataset(*data, headers=headers)
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# Establish file location and save
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data.save('test.xls')
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Intelligently add new rows: ::
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data.append('Bob', 'Dylan', 3.2)
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print data.headers
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# >>> ('first_name', 'last_name', 'gpa')
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Slice rows: ::
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print data[0:1]
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# >>> [('John', 'Adams', 4.0), ('George', 'Washington', 2.6)]
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Slice columns by header: ::
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print data['first_name']
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# >>> ['John', 'George', 'Henry']
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Manipulate rows by index: ::
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del data[0]
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print data[0:1]
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# >>> [('George', 'Washington', 2.6), ('Henry', 'Ford', 2.3)]
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Roadmap
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-------
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- Import datasets from CSV, JSON, YAML
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- Auto-detect import format
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- Plugin support |