# Frictionless Framework

Frictionless is a framework to describe, extract, validate, and transform tabular data. 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 Data Specifications.

[Important Notice] We have renamed goodtables to frictionless since version 3. The framework got various improvements and was extended to be a complete data solution. The change in not breaking for the existing software so no actions are required. Please read the Migration Guide from goodtables to Frictionless Framework.

we continue to bug-fix [email protected] in this branch as well as it’s available on PyPi as it was before

please note that [email protected] version’s API, we’re working on at the moment, is not stable

we will release [email protected] by the end of 2020 to be the first SemVer/stable version

# 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 protocols 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

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
The included API server
More than 1000+ tests

# Example

$ 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"

# Frictionless Framework

# Purpose

# Features

# Example

# Documentation

# General

# Specific