---
id: validations-engine
version: "2.0.0"
license: unclear
license_treatment: unclear
maintenance: active
---

# validations-engine — Engine for creating and running validation suites for general purposes

License: unclear · Maintenance: active · Downloads: 243.3K/mo

## What it is and what it does

Validations Engine is a framework for organizing and running validation suites—collections of test-like methods that check whether data pipelines, databases, APIs, and other systems are functioning correctly. It was originally built to catch failures early in data engineering pipelines but can be used for general validation purposes.

The engine works by defining Executors (which contain shared validation logic) and ValidationSuites (which inherit from an executor and define validation_* methods that run automatically). You write validation methods following a naming convention, and the engine discovers and executes them. It's structured like a unit-testing framework but designed for integration and data-quality checks rather than code unit tests.

Use it for:

- Validate data pipeline outputs before downstream processing to catch quality issues early.
- Test API endpoints and database connections as part of an automated integration test suite.
- Create reusable validation logic by defining custom executors that multiple suites can inherit from.
- Monitor data systems for failures by running validation suites on a schedule.
- Build domain-specific validators that share common patterns across suites.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Validations Engine is a framework for defining and executing validation suites—sets of test-like methods that check data pipelines, databases, APIs, and other systems for failures.

Yes, with conditions. The package is actively maintained and has low install friction. However, the license treatment is unclear, so verify the actual license before use in proprietary contexts. Install if you need a validation framework for data pipelines or integration testing and can confirm the license meets your requirements.

## Install

pip install validations-engine
uv add validations-engine
poetry add validations-engine

## Installing validations-engine

Before you install: Low install friction with a single runtime dependency (requests). The package is actively maintained with a recent commit as of 2026-02-18.

License in practice: License treatment is unclear—the fact sheet does not specify whether Apache License 2.0 or another license applies, so you should verify the actual license before use in proprietary or restricted contexts.

Quickstart:

pip install validations-engine

from validations_engine import BaseValidationSuitesExecutor

class MyValidationSuite(BaseValidationSuitesExecutor):
    def validation_example(self):
        assert some_condition, "Validation failed"

suite = MyValidationSuite()
suite.run()

Requires Python >=3.7, <4. The package depends on requests, which must be available at runtime.

Verify before relying:

- Whether the unclear license treatment reflects Apache 2.0 or a different license—verify before production use.
- Whether the gap since last release indicates the package is maintained or dormant despite recent commits.

## Package facts

- License: not declared (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 243.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

validation framework python, data pipeline testing, validation suites executor, automated data quality checks, integration testing framework, validation engine, test automation framework, data-quality, integration-testing, pipeline-validation

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