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Data Ingestion with Python Cookbook
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One of the most widely used parameters in Airflow DAG scheduler configuration is schedule_interval
. Together with start_date
, it creates a dynamic and continuous trigger for the pipeline. However, there are some small details we need to pay attention to when setting schedule_interval
.
This recipe will cover different forms to set up the schedule_interval
parameter. We will also explore a practical example to see how the scheduling window works in Airflow, making it more straightforward to manage pipeline executions.
While this exercise does not require any technical preparation, it is recommended to take notes about when the pipeline is supposed to start and the interval between each trigger.
Here, we will show only the default_args
dictionary to avoid code redundancy. However, you can always check out the complete code in the GitHub repository: https://github.com/PacktPublishing/Data-Ingestion...
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