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

Project description

Tablib: format-agnostic tabular dataset library

Jazzband Build Status codecov

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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)
  • Pandas DataFrames (Sets)
  • HTML (Sets)
  • Jira (Sets)
  • TSV (Sets)
  • ODS (Sets)
  • CSV (Sets)
  • DBF (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, DBF, and CSV; they can be exported to XLSX, XLS, ODS, JSON, YAML, DBF, 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.export('json'))
[
  {
    "last_name": "Adams",
    "age": 90,
    "first_name": "John"
  },
  {
    "last_name": "Ford",
    "age": 83,
    "first_name": "Henry"
  }
]

YAML!

>>> print(data.export('yaml'))
- {age: 90, first_name: John, last_name: Adams}
- {age: 83, first_name: Henry, last_name: Ford}

CSV...

>>> print(data.export('csv'))
first_name,last_name,age
John,Adams,90
Henry,Ford,83

EXCEL!

>>> with open('people.xls', 'wb') as f:
...     f.write(data.export('xls'))

DBF!

>>> with open('people.dbf', 'wb') as f:
...     f.write(data.export('dbf'))

Pandas DataFrame!

>>> print(data.export('df')):
      first_name last_name  age
0       John     Adams   90
1      Henry      Ford   83

It's that easy.

Installation

To install tablib, simply:

$ pip install tablib[pandas]

Make sure to check out Tablib on PyPI!

Contribute

Please see the contributing guide.

History

0.14.0 (2019-10-19)

Deprecations

  • The 0.14.x series will be the last to support Python 2

Breaking changes

  • Dropped Python 3.4 support

Improvements

  • Added Python 3.7 and 3.8 support
  • The project is now maintained by the Jazzband team, https://jazzband.co
  • Improved format autodetection and added autodetection for the odf format.
  • Added search to all documentation pages
  • Open xlsx workbooks in read-only mode (#316)
  • Unpin requirements
  • Only install backports.csv on Python 2

Bugfixes

  • Fixed DataBook().load parameter ordering (first stream, then format).
  • Fixed a regression for xlsx exports where non-string values were forced to strings (#314)
  • Fixed xlsx format detection (which was often detected as xls format)

0.13.0 (2019-03-08)

  • Added reStructuredText output capability (#336)
  • Added Jira output capability
  • Stopped calling openpyxl deprecated methods (accessing cells, removing sheets) (openpyxl minimal version is now 2.4.0)
  • Fixed a circular dependency issue in JSON output (#332)
  • Fixed Unicode error for the CSV export on Python 2 (#215)
  • Removed usage of optional ujson (#311)
  • Dropped Python 3.3 support

0.12.1 (2017-09-01)

  • Favor Dataset.export(<format>) over Dataset.<format> syntax in docs
  • Make Panda dependency optional

0.12.0 (2017-08-27)

  • Add initial Panda DataFrame support
  • Dropped Python 2.6 support

0.11.5 (2017-06-13)

  • Use yaml.safe_load for importing yaml.

0.11.4 (2017-01-23)

  • Use built-in json package if available
  • Support Python 3.5+ in classifiers

Bugfixes

  • Fixed textual representation for Dataset with no headers
  • Handle decimal types

0.11.3 (2016-02-16)

  • Release fix.

0.11.2 (2016-02-16)

Bugfixes

  • Fix export only formats.
  • Fix for xlsx output.

0.11.1 (2016-02-07)

Bugfixes

  • Fixed packaging error on Python 3.

0.11.0 (2016-02-07)

New Formats!

  • Added LaTeX table export format (Dataset.latex).
  • Support for dBase (DBF) files (Dataset.dbf).

Improvements

  • New import/export interface (Dataset.export(), Dataset.load()).
  • CSV custom delimiter support (Dataset.export('csv', delimiter='$')).
  • Adding ability to remove duplicates to all rows in a dataset (Dataset.remove_duplicates()).
  • Added a mechanism to avoid datetime.datetime issues when serializing data.
  • New detect_format() function (mostly for internal use).
  • Update the vendored unicodecsv to fix None handling.
  • Only freeze the headers row, not the headers columns (xls).

Breaking Changes

  • detect() function removed.

Bugfixes

  • Fix XLSX import.
  • Bugfix for Dataset.transpose().transpose().

0.10.0 (2014-05-27)

  • Unicode Column Headers
  • ALL the bugfixes!

0.9.11 (2011-06-30)

  • Bugfixes

0.9.10 (2011-06-22)

  • Bugfixes

0.9.9 (2011-06-21)

  • Dataset API Changes
  • stack_rows => stack, stack_columns => stack_cols
  • column operations have their own methods now (append_col, insert_col)
  • List-style pop()
  • Redis-style rpush, lpush, rpop, lpop, rpush_col, and lpush_col

0.9.8 (2011-05-22)

  • OpenDocument Spreadsheet support (.ods)
  • Full Unicode TSV support

0.9.7 (2011-05-12)

  • Full XLSX Support!
  • Pickling Bugfix
  • Compat Module

0.9.6 (2011-05-12)

  • seperators renamed to separators
  • Full unicode CSV support

0.9.5 (2011-03-24)

  • Python 3.1, Python 3.2 Support (same code base!)
  • Formatter callback support
  • Various bug fixes

0.9.4 (2011-02-18)

  • Python 2.5 Support!
  • Tox Testing for 2.5, 2.6, 2.7
  • AnyJSON Integrated
  • OrderedDict support
  • Caved to community pressure (spaces)

0.9.3 (2011-01-31)

  • Databook duplication leak fix.
  • HTML Table output.
  • Added column sorting.

0.9.2 (2010-11-17)

  • Transpose method added to Datasets.
  • New frozen top row in Excel output.
  • Pickling support for Datasets and Rows.
  • Support for row/column stacking.

0.9.1 (2010-11-04)

  • Minor reference shadowing bugfix.

0.9.0 (2010-11-04)

  • Massive documentation update!
  • Tablib.org!
  • Row tagging and Dataset filtering!
  • Column insert/delete support
  • Column append API change (header required)
  • Internal Changes (Row object and use thereof)

0.8.5 (2010-10-06)

  • New import system. All dependencies attempt to load from site-packages, then fallback on tenderized modules.

0.8.4 (2010-10-04)

  • Updated XLS output: Only wrap if '\n' in cell.

0.8.3 (2010-10-04)

  • Ability to append new column passing a callable as the value that will be applied to every row.

0.8.2 (2010-10-04)

  • Added alignment wrapping to written cells.
  • Added separator support to XLS.

0.8.1 (2010-09-28)

  • Packaging Fix

0.8.0 (2010-09-25)

  • New format plugin system!
  • Imports! ELEGANT Imports!
  • Tests. Lots of tests.

0.7.1 (2010-09-20)

  • Reverting methods back to properties.
  • Windows bug compensated in documentation.

0.7.0 (2010-09-20)

  • Renamed DataBook Databook for consistency.
  • Export properties changed to methods (XLS filename / StringIO bug).
  • Optional Dataset.xls(path='filename') support (for writing on windows).
  • Added utf-8 on the worksheet level.

0.6.4 (2010-09-19)

  • Updated unicode export for XLS.
  • More exhaustive unit tests.

0.6.3 (2010-09-14)

  • Added Dataset.append() support for columns.

0.6.2 (2010-09-13)

  • Fixed Dataset.append() error on empty dataset.
  • Updated Dataset.headers property w/ validation.
  • Added Testing Fixtures.

0.6.1 (2010-09-12)

  • Packaging hotfixes.

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.

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