Frictionless is a framework to describe, extract, validate, and transform tabular data
Project description
Frictionless Framework
Frictionless@4 is now live! Please read the Migration Guide
Frictionless is a framework to describe, extract, validate, and transform tabular data (DEVT Framework). It supports a great deal of data schemes and formats, as well as provides popular platforms integrations. The framework is powered by the lightweight yet comprehensive Frictionless Data Specifications.
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
- 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"
Documentation
Please visit our documentation portal:
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
frictionless-4.0.12.tar.gz
(152.8 kB
view details)
Built Distribution
File details
Details for the file frictionless-4.0.12.tar.gz.
File metadata
- Download URL: frictionless-4.0.12.tar.gz
- Upload date:
- Size: 152.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.9.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e1fa9ca93bedb8c5f8262a893b2a02696c37659683ebcb25b13f3c0a14b1ac99 |
|
| MD5 | 776e71d6ae2a5eae5c14c2f240db63c0 |
|
| BLAKE2b-256 | 6001b338daef106d43be8f16bb7e9469fb6e1e42e873b74a2fcb3ba72ab61840 |
Provenance
File details
Details for the file frictionless-4.0.12-py2.py3-none-any.whl.
File metadata
- Download URL: frictionless-4.0.12-py2.py3-none-any.whl
- Upload date:
- Size: 216.5 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.9.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 50fba20bfd1c15c99bf418cc14e7102d88ee08ec54e368f33fb1042a47392f6c |
|
| MD5 | 3480c57c431c8332009065dd8fef55f4 |
|
| BLAKE2b-256 | 9accc826a82188d452d3550975cac7bff186d9c7fe03355080b6b6275735ae37 |
