Name | valida JSON |
Version |
0.7.5
JSON |
| download |
home_page | None |
Summary | Comprehensive validation library for nested data structures. |
upload_time | 2024-11-14 14:10:30 |
maintainer | None |
docs_url | None |
author | Adam J. Plowman |
requires_python | <4.0.0,>=3.8 |
license | MIT |
keywords |
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
<img src="valida.png" width="200" alt="Valida logo"/>
**Validation for nested data structures**
[![PyPI version](https://img.shields.io/pypi/v/valida "PyPI version")](https://pypi.org/project/valida)
![Testing workflow](https://github.com/hpcflow/valida/actions/workflows/test.yml/badge.svg)
[![Supported python versions](https://img.shields.io/pypi/pyversions/valida "Supported python versions")](https://pypi.org/project/valida)
[![License](https://img.shields.io/github/license/hpcflow/valida "License")](https://github.com/hpcflow/valida/blob/main/LICENSE)
[![DOI](https://zenodo.org/badge/446597552.svg)](https://zenodo.org/badge/latestdoi/446597552)
## Installing
`pip install valida`
## A simple example
```python
from valida import Data, Value, Rule
# Define some data that we want to validate:
my_data = Data({'A': 1, 'B': [1, 2, 3], 'C': {'c1': 8.2, 'c2': 'hello'}})
# Define a rule as a path within the data and a condition at that path:
rule = Rule(
path=('C', 'c2'),
condition=Value.dtype.equal_to(str),
)
# Test the rule
rule.test(my_data).is_valid # `True` => The rule tested successfully
```
## Acknowledgements
Valida was developed using funding from the [LightForm](https://lightform.org.uk/) EPSRC programme grant ([EP/R001715/1](https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/R001715/1))
<img src="https://lightform-group.github.io/wiki/assets/images/site/lightform-logo.png" width="150"/>
Raw data
{
"_id": null,
"home_page": null,
"name": "valida",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0.0,>=3.8",
"maintainer_email": null,
"keywords": null,
"author": "Adam J. Plowman",
"author_email": "adam.plowman@manchester.ac.uk",
"download_url": "https://files.pythonhosted.org/packages/d4/ab/738588ae16c5843b1873d5ef4bebc7e25ea55b09697d88bd0f3d3c962ba3/valida-0.7.5.tar.gz",
"platform": null,
"description": "<img src=\"valida.png\" width=\"200\" alt=\"Valida logo\"/>\n\n**Validation for nested data structures**\n\n[![PyPI version](https://img.shields.io/pypi/v/valida \"PyPI version\")](https://pypi.org/project/valida)\n![Testing workflow](https://github.com/hpcflow/valida/actions/workflows/test.yml/badge.svg)\n[![Supported python versions](https://img.shields.io/pypi/pyversions/valida \"Supported python versions\")](https://pypi.org/project/valida)\n[![License](https://img.shields.io/github/license/hpcflow/valida \"License\")](https://github.com/hpcflow/valida/blob/main/LICENSE)\n[![DOI](https://zenodo.org/badge/446597552.svg)](https://zenodo.org/badge/latestdoi/446597552)\n\n## Installing\n\n`pip install valida`\n\n## A simple example\n\n```python\nfrom valida import Data, Value, Rule\n\n# Define some data that we want to validate:\nmy_data = Data({'A': 1, 'B': [1, 2, 3], 'C': {'c1': 8.2, 'c2': 'hello'}})\n\n# Define a rule as a path within the data and a condition at that path:\nrule = Rule(\n path=('C', 'c2'),\n condition=Value.dtype.equal_to(str),\n)\n\n# Test the rule\nrule.test(my_data).is_valid # `True` => The rule tested successfully\n\n```\n\n## Acknowledgements\n\nValida was developed using funding from the [LightForm](https://lightform.org.uk/) EPSRC programme grant ([EP/R001715/1](https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/R001715/1))\n\n<img src=\"https://lightform-group.github.io/wiki/assets/images/site/lightform-logo.png\" width=\"150\"/>\n\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Comprehensive validation library for nested data structures.",
"version": "0.7.5",
"project_urls": null,
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "9d40096a60e48c2ef1b1a48caa78e3afac5e2f780ebc98f81d2373f3149f1c0d",
"md5": "d6c507ebdbf9aafeab6f658ef70c95a8",
"sha256": "4dc3a3b5cfc228327d44fe59dc08cdea2728124ec2ac40d1fcd76c5ba8da6c9b"
},
"downloads": -1,
"filename": "valida-0.7.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d6c507ebdbf9aafeab6f658ef70c95a8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0.0,>=3.8",
"size": 26836,
"upload_time": "2024-11-14T14:10:29",
"upload_time_iso_8601": "2024-11-14T14:10:29.268120Z",
"url": "https://files.pythonhosted.org/packages/9d/40/096a60e48c2ef1b1a48caa78e3afac5e2f780ebc98f81d2373f3149f1c0d/valida-0.7.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d4ab738588ae16c5843b1873d5ef4bebc7e25ea55b09697d88bd0f3d3c962ba3",
"md5": "40ddb6960eda56154ecc7b1ecf95564d",
"sha256": "86bb6d187552f18f7d773550bc985304ec71913cc61d659f3d454bb42a7694d3"
},
"downloads": -1,
"filename": "valida-0.7.5.tar.gz",
"has_sig": false,
"md5_digest": "40ddb6960eda56154ecc7b1ecf95564d",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0.0,>=3.8",
"size": 23572,
"upload_time": "2024-11-14T14:10:30",
"upload_time_iso_8601": "2024-11-14T14:10:30.258538Z",
"url": "https://files.pythonhosted.org/packages/d4/ab/738588ae16c5843b1873d5ef4bebc7e25ea55b09697d88bd0f3d3c962ba3/valida-0.7.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-11-14 14:10:30",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "valida"
}