Params

Params in Airflow are a way to pass dynamic runtime configuration to tasks within a DAG. They allow tasks to be more flexible by enabling templated values to be injected during execution.

Key Features

• Available in DAG and task definitions.
• Can be templated using Jinja.
• Useful for customizing task behavior without modifying code.

Example DAG

default:
  catchup: false
  default_args:
    start_date: 2025-01-01

example_params:
  params:
    model_version: 1.0.0
    input_uri: localhost
  description: "This is an DAG-Factory example dag with param"
  schedule_interval: "@daily"
  tasks:
    task_1:
      operator: airflow.operators.bash.BashOperator
      bash_command: "echo 'Running task 1 with model version {{ params.model_version }} and url: {{ params.input_uri }}'"
    task_2:
      operator: airflow.operators.python.PythonOperator
      params:
        my_param: 10
      python_callable: sample.read_params

When to Use

• You want to reuse the same DAG for different input values.
• You want to change a task’s behavior at runtime.