airflow-tools 0.1.2

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Airflow Tools

Collection of Operators, Hooks and utility functions aimed at facilitating ELT pipelines.

Data Lake Facade

The Data Lake Facade serves as an abstracion over different Hooks that can be used as a backend such as:

• Azure Data Lake Storage (ADLS)
• Simple Storage Service (S3)

Operators can create the correct hook at runtime by passing a connection ID with a connection type of aws or adls. Example code:

conn = BaseHook.get_connection(conn_id)
hook = conn.get_hook()

Operators

HTTP to Data Lake

Creates a Example usage:

HttpToDataLake(
    task_id='test_http_to_data_lake',
    http_conn_id='http_test',
    data_lake_conn_id='data_lake_test',
    data_lake_path=s3_bucket + '/source1/entity1/{{ ds }}/',
    endpoint='/api/users',
    method='GET',
    jmespath_expression='data[:2].{id: id, email: email}',
)

JMESPATH expressions

APIs often return the response we are interested in wrapped in a key. JMESPATH expressions are a query language that we can use to select the response we are interested in. You can find more information on JMESPATH expressions and test them here.

The above expression selects the first two objects inside the key data, and then only the id and email attributes in each object. An example response can be found here.

Tests

Integration tests

To guarantee that the library works as intended we have an integration test that attempts to install it in a fresh virtual environment, and we aim to have a test for each Operator.

Running integration tests locally

The lint-and-test.yml workflow sets up the necessary environment variables, but if you want to run them locally you will need the following environment variables:

AIRFLOW_CONN_DATA_LAKE_TEST='{"conn_type": "aws", "extra": {"endpoint_url": "http://localhost:9090"}}'
AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE
AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
AWS_DEFAULT_REGION=us-east-1
TEST_BUCKET=data_lake
S3_ENDPOINT_URL=http://localhost:9090

AIRFLOW_CONN_DATA_LAKE_TEST='{"conn_type": "aws", "extra": {"endpoint_url": "http://localhost:9090"}}' AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY TEST_BUCKET=data_lake S3_ENDPOINT_URL=http://localhost:9090 poetry run pytest tests/ --doctest-modules --junitxml=junit/test-results.xml --cov=com --cov-report=xml --cov-report=html

And you also need to run Adobe's S3 mock container like this:

docker run --rm -p 9090:9090 -e initialBuckets=data_lake -e debug=true -t adobe/s3mock