---
id: apache-airflow-providers-anomalo
version: "0.2.2"
license: Apache-2.0
license_treatment: permissive
maintenance: aging
---

# apache-airflow-providers-anomalo — An Apache Airflow provider for Anomalo

License: permissive · Maintenance: aging · Downloads: 76.7K/mo

## What it is and what it does

This package extends Apache Airflow with native operators and sensors for Anomalo, a data quality monitoring platform. It allows you to orchestrate Anomalo checks as part of Airflow DAGs, triggering data quality validations on demand and waiting for their completion before proceeding to downstream tasks.

The provider includes three main components: AnomaloRunCheckOperator to execute checks on a specified table, AnomaloJobCompleteSensor to poll for job completion, and AnomaloPassFailOperator to validate check results. Setup requires configuring an Anomalo connection in Airflow's Admin interface with your API credentials. The package has low install friction, depending only on the anomalo client library and importlib-resources.

Use it for:

- Trigger Anomalo data quality checks as part of a data pipeline DAG to validate incoming data before downstream processing.
- Monitor table integrity automatically on a schedule by embedding Anomalo checks into recurring Airflow workflows.
- Gate downstream tasks on data quality by using the sensor to wait for check completion and the pass/fail operator to branch logic.
- Integrate data quality validation into CI/CD or ETL pipelines that already use Airflow for orchestration.

## Worth the install?

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

Provides native Apache Airflow operators and sensors to integrate Anomalo data quality checks into Airflow DAGs, enabling automated monitoring and validation of table data.

Yes, if you use Apache Airflow and Anomalo together. The provider has low install friction, permissive licensing, and no known vulnerabilities. Maintenance is aging (last update 308 days ago), so expect slower issue resolution, but the repository remains active and the package is marked Production/Stable. Suitable for teams already committed to both platforms.

## Install

pip install apache-airflow-providers-anomalo
uv add apache-airflow-providers-anomalo
poetry add apache-airflow-providers-anomalo

## Installing apache-airflow-providers-anomalo

Before you install: Low install friction with only two runtime dependencies. Maintenance status is aging—last commit was 308 days ago, though the repository remains active and not archived. Suitable for stable production use but expect slower response to issues.

License in practice: Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions. No licensing concerns for most deployment scenarios.

Quickstart:

pip install apache-airflow-providers-anomalo

from airflow.providers.anomalo.operators.anomalo import AnomaloRunCheckOperator
from airflow.providers.anomalo.sensors.anomalo import AnomaloJobCompleteSensor

# In your DAG:
run_checks = AnomaloRunCheckOperator(task_id='run_anomalo_checks', table_name='public-bq.covid19_nyt.us_counties')
wait_job = AnomaloJobCompleteSensor(task_id='wait_for_checks', external_task_id='run_anomalo_checks')

Requires Python >=3.8,<3.12, Apache Airflow >=2.8.0, and an Anomalo connection configured in Airflow Admin > Connections with Host and API Secret Token.

Verify before relying:

- Whether the package supports the latest Airflow 2.x versions beyond what the >=2.8.0 requirement states
- Performance characteristics when monitoring large numbers of tables or frequent check runs
- Community adoption and real-world usage patterns beyond the download count

## Package facts

- License: Apache-2.0 (permissive)
- Python support: capped_below_current
- Install friction: low
- Maintenance: aging
- Downloads: 76.7K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

airflow anomalo provider, data quality checks airflow, anomalo operators, airflow data validation, table monitoring airflow, anomalo integration, airflow provider plugin, airflow-provider, data-quality, orchestration

[View on SkillFed](https://skillfed.io/packages/apache-airflow-providers-anomalo) · [View on PyPI](https://pypi.org/project/apache-airflow-providers-anomalo/)