https://github.com/frictionlessdata/frictionless-py

Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
https://github.com/frictionlessdata/frictionless-py

Last synced: 16 days ago
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Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data

• Host: GitHub
• URL: https://github.com/frictionlessdata/frictionless-py
• Owner: frictionlessdata
• License: mit
• Created: 2014-12-23T17:11:11.000Z (over 11 years ago)
• Default Branch: main
• Last Pushed: 2026-04-08T08:22:18.000Z (19 days ago)
• Last Synced: 2026-04-08T08:31:25.266Z (19 days ago)
• Language: Python
• Homepage: https://framework.frictionlessdata.io
• Size: 135 MB
• Stars: 814
• Watchers: 29
• Forks: 160
• Open Issues: 227
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Citation: CITATION.cff
  • Authors: AUTHORS.md

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README

          
# frictionless-py

[![Build](https://img.shields.io/github/actions/workflow/status/frictionlessdata/frictionless-py/general.yaml?branch=main)](https://github.com/frictionlessdata/frictionless-py/actions)

[![Coverage](https://img.shields.io/codecov/c/github/frictionlessdata/frictionless-py/main)](https://codecov.io/gh/frictionlessdata/frictionless-py)

[![Release](https://img.shields.io/pypi/v/frictionless.svg)](https://pypi.python.org/pypi/frictionless)

[![Citation](https://zenodo.org/badge/28409905.svg)](https://zenodo.org/badge/latestdoi/28409905)

[![Codebase](https://img.shields.io/badge/codebase-github-brightgreen)](https://github.com/frictionlessdata/frictionless-py)

[![Support](https://img.shields.io/badge/support-slack-brightgreen)](https://join.slack.com/t/frictionlessdata/shared_invite/zt-17kpbffnm-tRfDW_wJgOw8tJVLvZTrBg)

```markdown remark type=primary

Migrating from an older version? Please read **[v5](blog/2022/08-22-frictionless-framework-v5.html)** announcement and migration guide.

```

Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data (DEVT Framework). It supports a great deal of data sources and formats, as well as provides popular platforms integrations. The framework is powered by the lightweight yet comprehensive [Frictionless Standards](https://specs.frictionlessdata.io/).

## Purpose

- **Describe your data**: You can infer, edit and save metadata of your data tables. It's a first step for ensuring data quality and usability. Frictionless metadata includes general information about your data like textual description, as well as, field types and other tabular data details.

- **Extract your data**: You can read your data using a unified tabular interface. Data quality and consistency are guaranteed by a schema. Frictionless supports various file schemes like HTTP, FTP, and S3 and data formats like CSV, XLS, JSON, SQL, and others.

- **Validate your data**: You can validate data tables, resources, and datasets. Frictionless generates a unified validation report, as well as supports a lot of options to customize the validation process.

- **Transform your data**: You can clean, reshape, and transfer your data tables and datasets. Frictionless provides a pipeline capability and a lower-level interface to work with the data.

## Features

- Open Source (MIT)

- Powerful Python framework

- Convenient command-line interface

- Low memory consumption for data of any size

- Reasonable performance on big data

- Support for compressed files

- Custom checks and formats

- Fully pluggable architecture

- More than 1000+ tests

## Installation

```bash

$ pip install frictionless

```

## Example

```bash

$ frictionless validate data/invalid.csv

[invalid] data/invalid.csv

  row    field  code              message

-----  -------  ----------------  --------------------------------------------

             3  blank-header      Header in field at position "3" is blank

             4  duplicate-header  Header "name" in field "4" is duplicated

    2        3  missing-cell      Row "2" has a missing cell in field "field3"

    2        4  missing-cell      Row "2" has a missing cell in field "name2"

    3        3  missing-cell      Row "3" has a missing cell in field "field3"

    3        4  missing-cell      Row "3" has a missing cell in field "name2"

    4           blank-row         Row "4" is completely blank

    5        5  extra-cell        Row "5" has an extra value in field  "5"

```

## Documentation

Please visit our documentation portal:

- https://framework.frictionlessdata.io