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-4.10.7.tar.gz
(156.7 kB
view details)
Built Distribution
File details
Details for the file frictionless-4.10.7.tar.gz.
File metadata
- Download URL: frictionless-4.10.7.tar.gz
- Upload date:
- Size: 156.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.3.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 9d3a74ac401e15576eb81722418bb3ca3bb2a710c23fc7fb33fc5f46edd21c4b |
|
| MD5 | 16749322d7f9763e6ad48d8f43a338ef |
|
| BLAKE2b-256 | 6ce153d98a45ebff651ab78606cfaad0330401dcfa4ff2940d68df9c2e643855 |
Provenance
File details
Details for the file frictionless-4.10.7-py2.py3-none-any.whl.
File metadata
- Download URL: frictionless-4.10.7-py2.py3-none-any.whl
- Upload date:
- Size: 221.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.3.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 5a194b737a9f9f060250312886119ff755f9cab6cc05b72328e78f0fffcf89dc |
|
| MD5 | d48abe6b7b6b9aa8cbb6de2d552b2912 |
|
| BLAKE2b-256 | e47b3421d716708bddd72c4c38562b74a263f5f7925281ce3150e1af4d047128 |
