Frictionless is a framework to describe, extract, validate, and transform tabular data
Project description
Frictionless Framework
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-4.10.1.tar.gz
(156.5 kB
view details)
Built Distribution
File details
Details for the file frictionless-4.10.1.tar.gz.
File metadata
- Download URL: frictionless-4.10.1.tar.gz
- Upload date:
- Size: 156.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | a34c69dd8ff8be3e4681f766a252e3e731678ca759e3f2945ecc710cf86f144a |
|
| MD5 | 7191385d2cb9bdf4a2c3e2a461d4ee79 |
|
| BLAKE2b-256 | 87f96d39390c1cb85595d6c2358615a160a4d972826f3d65e73f9212839a473b |
Provenance
File details
Details for the file frictionless-4.10.1-py2.py3-none-any.whl.
File metadata
- Download URL: frictionless-4.10.1-py2.py3-none-any.whl
- Upload date:
- Size: 221.0 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8f16284291557c14f0e5d1e2bc7c64b153cf83fd5e8d0dc90aee76680ac6abd5 |
|
| MD5 | 546cebe72cbdf3b032364a1f48b6b0f2 |
|
| BLAKE2b-256 | 409a54d0bcdcd0c0731e67679c8615b0623055515fc44de01f05bb28d85d602c |
