# frictionless-py
[](https://github.com/frictionlessdata/frictionless-py/actions)
[](https://codecov.io/gh/frictionlessdata/frictionless-py)
[](https://pypi.python.org/pypi/frictionless)
[](https://zenodo.org/badge/latestdoi/28409905)
[](https://github.com/frictionlessdata/frictionless-py)
[](https://join.slack.com/t/frictionlessdata/shared_invite/zt-17kpbffnm-tRfDW_wJgOw8tJVLvZTrBg)
```markdown remark type=primary
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](https://specs.frictionlessdata.io/).
## 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
```bash
$ pip install frictionless
```
## Example
```bash
$ 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:
- https://framework.frictionlessdata.io
Raw data
{
"_id": null,
"home_page": null,
"name": "frictionless",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "data package, data validation, frictionless data, json schema, json table schema, open data, tabular data package",
"author": null,
"author_email": "Open Knowledge Foundation <info@okfn.org>",
"download_url": "https://files.pythonhosted.org/packages/26/b4/ded94e51965f95100893adcf78ef9307553414a0bb56217adf68450bd7e7/frictionless-5.18.0.tar.gz",
"platform": null,
"description": "# frictionless-py\n\n[](https://github.com/frictionlessdata/frictionless-py/actions)\n[](https://codecov.io/gh/frictionlessdata/frictionless-py)\n[](https://pypi.python.org/pypi/frictionless)\n[](https://zenodo.org/badge/latestdoi/28409905)\n[](https://github.com/frictionlessdata/frictionless-py)\n[](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",
"bugtrack_url": null,
"license": null,
"summary": "Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data",
"version": "5.18.0",
"project_urls": {
"changelog": "https://github.com/frictionlessdata/framework/blob/main/CHANGELOG.md",
"homepage": "https://github.com/frictionlessdata/frictionless-py"
},
"split_keywords": [
"data package",
" data validation",
" frictionless data",
" json schema",
" json table schema",
" open data",
" tabular data package"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "fbe5c7ff55b81286f24ddfaff45c9d46614c3e40c72a8ebd036c2cc18d902243",
"md5": "223282bf0b3342740cbb0554debf6ce8",
"sha256": "a82433b81cfcfae21328aad6b93854feb86d5d054b22ac147672eb9c254b6a3d"
},
"downloads": -1,
"filename": "frictionless-5.18.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "223282bf0b3342740cbb0554debf6ce8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 535385,
"upload_time": "2024-09-28T08:53:50",
"upload_time_iso_8601": "2024-09-28T08:53:50.163145Z",
"url": "https://files.pythonhosted.org/packages/fb/e5/c7ff55b81286f24ddfaff45c9d46614c3e40c72a8ebd036c2cc18d902243/frictionless-5.18.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "26b4ded94e51965f95100893adcf78ef9307553414a0bb56217adf68450bd7e7",
"md5": "d0f59431383fcefff35d80ac109af73f",
"sha256": "4b21a10d3ac67e46a4a58a1e8a8a27c6882af4d1608eadfb6ccbfde0b5eef6b9"
},
"downloads": -1,
"filename": "frictionless-5.18.0.tar.gz",
"has_sig": false,
"md5_digest": "d0f59431383fcefff35d80ac109af73f",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 74371639,
"upload_time": "2024-09-28T08:53:53",
"upload_time_iso_8601": "2024-09-28T08:53:53.149406Z",
"url": "https://files.pythonhosted.org/packages/26/b4/ded94e51965f95100893adcf78ef9307553414a0bb56217adf68450bd7e7/frictionless-5.18.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-28 08:53:53",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "frictionlessdata",
"github_project": "framework",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "frictionless"
}
JSON
