The `DAG` (Directed Acyclic Graph) class is a fundamental component of the Python Airflow library. It represents a collection of tasks organized in a specific dependency structure, where each task is represented by an operator. The `DAG` class provides functionality to define and manage the workflow of these tasks, including their scheduling, dependencies, and control flow. It allows users to create complex data pipelines by describing the relationships and order of execution between tasks. Additionally, the `DAG` class offers methods to manage and monitor the state of tasks, handle task failures, and visualize the workflow graphically. Overall, the `DAG` class is essential for designing and executing efficient and scalable data pipelines using Airflow.
Python DAG - 60 examples found. These are the top rated real world Python examples of airflow.models.DAG extracted from open source projects. You can rate examples to help us improve the quality of examples.