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tablib

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

Worth itPyPI UtilitiesReleased Jul 20264.9M downloads / moMIT LicensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — tablib-3.10.0-py3-none-any.whl
v3.10.0 · released 2026-07-31 · Python >=3.10

Yes. Tablib is a stable, actively maintained library with zero dependencies, a permissive license, no known vulnerabilities, and broad format support. Install it if you need to work with tabular data across multiple output formats or move data between systems without writing format-specific code.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later.
  • Low friction install with no runtime dependencies.
  • Actively maintained with a recent release and steady commit activity.

License · maintenance · safety

MIT License (permissive) — MIT License permits commercial and private use with minimal restrictions—you may use, modify, and distribute tablib freely provided you include the license notice.

last release 2026-07-31 (14 days) · last repo commit 2026-07-31 · 4,755 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,853,319 downloads/mo, #2,213 on PyPI

Verify before relying

pip install tablib

import tablib

data = tablib.Dataset()
data.headers = ['Name', 'Age']
data.append(['Alice', 'Value'])
data.append(['Bob', 'Value'])

print(data.export('json'))
print(data.export('csv'))
  • Whether optional format-specific dependencies (e.g., for Excel or ODS) are required or lazy-loaded
  • Performance characteristics when handling large datasets
  • Whether Pandas integration requires pandas as an optional dependency
Same gist for agents: .md · .json

What it is and what it does

Tablib is a Python library that lets you work with tabular data in a format-agnostic way. You build a dataset once using a simple API, then export it to any of a dozen formats—Excel, JSON, YAML, CSV, HTML, LaTeX, TSV, ODS, DBF, SQL, Jira, or Pandas DataFrames—without rewriting your code for each format. It has no runtime dependencies, making it lightweight to install.

The library is designed for developers who need to move data between systems or generate reports in multiple formats. It's been in production use since its early releases, is actively maintained, and supports modern Python versions. The MIT license places no restrictions on commercial or private use.

Use it for

  • Export application data to Excel, CSV, or JSON for reporting or data analysis workflows
  • Convert between tabular formats (e.g., CSV to JSON or YAML) in data pipelines
  • Generate Jira or LaTeX tables from in-memory datasets for documentation or issue tracking
  • Serialize tabular data to multiple formats from a single dataset object
  • Build data export features into web applications without format-specific logic

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

Tablib is a stable, actively maintained library with zero dependencies, a permissive license, no known vulnerabilities, and broad format support. Install it if you need to work with tabular data across multiple output formats or move data between systems without writing format-specific code.

Install

tablib on PyPI

Before you install

Low friction install with no runtime dependencies. Actively maintained with a recent release and steady commit activity. Supports Python 3.10 through 3.15.

Requires Python 3.10 or later.

License in practice

MIT License permits commercial and private use with minimal restrictions—you may use, modify, and distribute tablib freely provided you include the license notice.

Quickstart

pip install tablib

import tablib

data = tablib.Dataset()
data.headers = ['Name', 'Age']
data.append(['Alice', 'Value'])
data.append(['Bob', 'Value'])

print(data.export('json'))
print(data.export('csv'))

Verify before relying

  • Whether optional format-specific dependencies (e.g., for Excel or ODS) are required or lazy-loaded
  • Performance characteristics when handling large datasets
  • Whether Pandas integration requires pandas as an optional dependency

Package facts

LicenseMIT License permissive
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependenciesNone
MaintenanceActively maintained 14 days since the last release
Last repo commit
First released
Downloads4,853,319 / month, #2,213 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.15

Evidence: tablib-3.10.0-py3-none-any.whl

Tags

Capabilities
tabular data format conversionexcel csv json yaml conversiondataset export multiple formatsdata serialization libraryspreadsheet format agnostictable data interchangepandas dataframe export
Topics
data-serializationformat-conversiontabular-data

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See also csvkit · pytablewriter · newtools · pyexcel · tabula-py · tabulator · pyexcel-io · dataflows-tabulator · linear-tsv · json-flattener