Apache Airflow provider for the Data Contract CLI: run data contract tests as quality gates in your DAGs
Project description
Data Contract Provider for Apache Airflow
Run Data Contract CLI tests as quality gates in your Airflow DAGs.
Features
DataContractTestOperatorrunsdatacontract testagainst a contract and fails the task when the contract is violated, so bad data stops before it propagates downstream.- Per-check results are rendered in the task log (pass/fail, reason, model/field).
- Structured results are pushed to XCom (key
datacontract_result), so downstream tasks can branch on the outcome. - On Airflow 3, a "Data Contract Results" view in the UI shows recent test runs across all DAGs.
- A "Test Results" button on the task instance links to the published results, e.g. in Entropy Data.
Installation
pip install airflow-provider-datacontract
Extras are passed through to the Data Contract CLI, e.g. for Snowflake:
pip install "airflow-provider-datacontract[snowflake]"
Available extras: duckdb (local files, csv/parquet), snowflake, databricks, bigquery, postgres, s3, azure, kafka, trino.
Usage
from datetime import datetime
from airflow.sdk import dag
from datacontract_provider.operators.datacontract import DataContractTestOperator
@dag(schedule="0 2 * * *", start_date=datetime(2026, 1, 1), catchup=False)
def nightly_datacontract_test():
DataContractTestOperator(
task_id="test_orders_contract",
data_contract_file="https://demo.datacontract.com/orders-latest/datacontract.yaml",
server="production",
)
nightly_datacontract_test()
Operator parameters
| Parameter | Description |
|---|---|
data_contract_file |
Path or URL of the data contract YAML (templated) |
data_contract_str |
Contract as a YAML string, alternative to data_contract_file |
server |
Server key from the contract's servers section to test against |
schema_name |
Schema/model to test, defaults to all |
check_categories |
Subset of schema, quality, servicelevel, custom |
server_conn_id |
Airflow connection with credentials for the server under test (see below) |
entropy_data_conn_id |
Airflow connection for Entropy Data (password = API key, host optional) |
config |
Dict of additional Data Contract CLI configuration fields |
publish_url |
URL to publish test results to (optional) |
results_web_url |
Web page of the published results, shown as a "Test Results" button (optional) |
include_failed_samples |
Collect samples of failing rows |
fail_on_warning |
Also fail the task on result warning |
datacontract_kwargs |
Extra kwargs for the DataContract constructor, e.g. spark |
Credentials via Airflow connections (recommended)
Pass server_conn_id to resolve credentials through Airflow's connection
machinery, including any configured secrets backend (Vault, AWS Secrets
Manager, Azure Key Vault, ...). The connection is mapped to
Data Contract CLI configuration
based on its type and passed programmatically; credentials never touch the
process environment.
DataContractTestOperator(
task_id="test_orders_contract",
data_contract_file="...",
server="production",
server_conn_id="databricks_prod", # conn type: databricks
entropy_data_conn_id="entropy_data", # conn type: entropy_data
)
The provider registers an Entropy Data connection type: create a
connection with type entropydata, put the API key in the password field,
and optionally override the host (default https://api.entropy-data.com).
When entropy_data_conn_id is set and no publish_url is given, test
results are published to <host>/api/test-results automatically.
Supported connection types: databricks (host, extra http_path; token
auth: password = token, login empty; service principal OAuth: login =
client id, password = client secret), snowflake (login/password, extra
account, warehouse, role), postgres, mysql, oracle, impala,
trino, mssql, redshift (login/password/host/port/schema), aws
(login/password=key pair, extra region_name), google_cloud_platform
(extra key_path, project), wasb/azure, and kafka. For anything else, add
datacontract_-prefixed keys to the connection extra
(e.g. datacontract_trino_jwt_token); those pass through to any config field
and also override the mapped values. The config parameter is merged last.
Requires datacontract-cli >= 1.0. Alternatively, the CLI still reads
credentials from environment variables, e.g. DATACONTRACT_SNOWFLAKE_USERNAME,
set on the worker.
XCom
The operator pushes two XCom entries:
datacontract_result:{result, data_contract_file, server, checks_total, checks_failed, checks: [{name, result, category, type, model, field, reason}]}datacontract_results_url: theresults_web_url, if configured
Results view in the Airflow UI (Airflow 3.1+)
The provider ships a React app (registered via the plugin react_apps
interface) that adds a Data Contract Results entry to the navigation,
rendering the most recent test runs across all DAGs natively in the Airflow
UI, with expandable check details and auto-refresh. The data comes from XCom
via /datacontract/api/results; a standalone HTML fallback is available at
/datacontract/results. On Airflow 2 the plugin degrades gracefully and only
registers the extra link.
The React source lives in ui/; the built UMD bundle is committed at
src/datacontract_provider/static/main.umd.cjs and shipped with the package
(rebuild with cd ui && npm install && npm run build, then copy
ui/dist/main.umd.cjs there).
Entropy Data (optional)
To publish test results to Entropy Data (formerly
Data Mesh Manager), set the ENTROPY_DATA_API_KEY environment variable on
the worker and configure:
DataContractTestOperator(
task_id="test_orders_contract",
data_contract_file="...",
server="production",
publish_url="https://api.entropy-data.com/api/test-results",
results_web_url="https://app.entropy-data.com/...", # optional deep link
)
Version support
- Apache Airflow 2.10+ and 3.x (the UI results view requires Airflow 3)
- Python 3.10+
Development
pip install -e ".[dev]"
ruff check src tests
pytest
License
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