frictionless5.18.0
frictionless5.18.0
Published
Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
pip install frictionless
Package Downloads
Authors
Requires Python
>=3.8
Dependencies
- attrs
>=22.2.0 - chardet
>=3.0 - humanize
>=4.2 - isodate
>=0.6 - jinja2
>=3.0 - jsonschema
>=4.20 - marko
>=1.0 - petl
>=1.6 - pydantic
>=2.0 - python-dateutil
>=2.8 - python-slugify
>=1.2 - pyyaml
>=5.3 - requests
>=2.10 - rfc3986
>=1.4 - simpleeval
>=0.9.11 - stringcase
>=1.2 - tabulate
>=0.8.10 - typer
>=0.12 - typing-extensions
>=4.3 - validators
>=0.18 - boto3
>=1.9; extra == "aws" - google-api-python-client
>=1.12.1; extra == "bigquery" - frictionless-ckan-mapper
>=1.0; extra == "ckan" - datasette
>=0.64.2; extra == "datasette" - hatch
; extra == "dev" - httpx
; extra == "dev" - ipython
; extra == "dev" - livemark
; extra == "dev" - moto
; extra == "dev" - neovim
; extra == "dev" - oauth2client
; extra == "dev" - pyright
==1.1.317; extra == "dev" - pytest
; extra == "dev" - pytest-cov
; extra == "dev" - pytest-dotenv
; extra == "dev" - pytest-lazy-fixtures
; extra == "dev" - pytest-mock
; extra == "dev" - pytest-timeout
; extra == "dev" - pytest-vcr
; extra == "dev" - requests-mock
; extra == "dev" - ruff
; extra == "dev" - yattag
; extra == "dev" - duckdb-engine
>=0.7; extra == "duckdb" - duckdb
>=0.8; extra == "duckdb" - sqlalchemy
>=1.4; extra == "duckdb" - openpyxl
>=3.0; extra == "excel" - tableschema-to-template
>=0.0; extra == "excel" - xlrd
>=1.2; extra == "excel" - xlwt
>=1.2; extra == "excel" - pygithub
>=1.50; extra == "github" - pygsheets
>=2.0; extra == "gsheets" - pyquery
>=1.4; extra == "html" - ijson
>=3.0; extra == "json" - jsonlines
>=1.2; extra == "json" - pymysql
>=1.0; extra == "mysql" - sqlalchemy
>=1.4; extra == "mysql" - ezodf
>=0.3; extra == "ods" - lxml
>=4.0; extra == "ods" - pandas
>=1.0; extra == "pandas" - pyarrow
>=14.0; extra == "pandas" - fastparquet
>=0.8; extra == "parquet" - psycopg2
>=2.9; extra == "postgresql" - psycopg
>=3.0; extra == "postgresql" - sqlalchemy
>=1.4; extra == "postgresql" - savreaderwriter
>=3.0; extra == "spss" - sqlalchemy
>=1.4; extra == "sql" - visidata
>=2.10; extra == "visidata" - tatsu
>=5.8.3; extra == "wkt" - pyzenodo3
>=1.0; extra == "zenodo"
frictionless-py
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.
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
$ pip install frictionless
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: