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frictionless-py\n\n[![Build](https://img.shields.io/github/actions/workflow/status/frictionlessdata/frictionless-py/general.yaml?branch=main)](https://github.com/frictionlessdata/frictionless-py/actions)\n[![Coverage](https://img.shields.io/codecov/c/github/frictionlessdata/frictionless-py/main)](https://codecov.io/gh/frictionlessdata/frictionless-py)\n[![Release](https://img.shields.io/pypi/v/frictionless.svg)](https://pypi.python.org/pypi/frictionless)\n[![Citation](https://zenodo.org/badge/28409905.svg)](https://zenodo.org/badge/latestdoi/28409905)\n[![Codebase](https://img.shields.io/badge/codebase-github-brightgreen)](https://github.com/frictionlessdata/frictionless-py)\n[![Support](https://img.shields.io/badge/support-slack-brightgreen)](https://join.slack.com/t/frictionlessdata/shared_invite/zt-17kpbffnm-tRfDW_wJgOw8tJVLvZTrBg)\n\n```markdown remark type=primary\nMigrating from an older version? Please read **[v5](blog/2022/08-22-frictionless-framework-v5.html)** announcement and migration guide.\n```\n\nData 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](https://specs.frictionlessdata.io/).\n\n## Purpose\n\n- **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.\n- **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.\n- **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.\n- **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.\n\n## Features\n\n- Open Source (MIT)\n- Powerful Python framework\n- Convenient command-line interface\n- Low memory consumption for data of any size\n- Reasonable performance on big data\n- Support for compressed files\n- Custom checks and formats\n- Fully pluggable architecture\n- More than 1000+ tests\n\n## Installation\n\n```bash\n$ pip install frictionless\n```\n\n## Example\n\n```bash\n$ frictionless validate data/invalid.csv\n[invalid] data/invalid.csv\n\n  row    field  code              message\n-----  -------  ----------------  --------------------------------------------\n             3  blank-header      Header in field at position \"3\" is blank\n             4  duplicate-header  Header \"name\" in field \"4\" is duplicated\n    2        3  missing-cell      Row \"2\" has a missing cell in field \"field3\"\n    2        4  missing-cell      Row \"2\" has a missing cell in field \"name2\"\n    3        3  missing-cell      Row \"3\" has a missing cell in field \"field3\"\n    3        4  missing-cell      Row \"3\" has a missing cell in field \"name2\"\n    4           blank-row         Row \"4\" is completely blank\n    5        5  extra-cell        Row \"5\" has an extra value in field  \"5\"\n```\n\n## Documentation\n\nPlease visit our documentation portal:\n- https://framework.frictionlessdata.io\n","funding_links":[],"categories":["Data","📊 Data Validation \u0026 Quality","Python","Data Management","Uncategorized"],"sub_categories":["Django","Uncategorized"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrictionlessdata%2Ffrictionless-py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffrictionlessdata%2Ffrictionless-py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrictionlessdata%2Ffrictionless-py/lists"}