This DAG fetches the top 3 locations from an API and loads them into a PostgreSQL database. The DAG will run daily according to the specified schedule. This project contains an Apache Airflow DAG (Directed Acyclic Graph) that performs the following actions:

1. Defining constants and settings:

   • Sets the basic arguments (default_args) for the DAG, such as the owner, dependencies on previous runs, start date, and execution interval.
   • Sets the URL for retrieving data from an API.

2. Defining the load_to_db function:

   • This function is responsible for loading data into a database.
   • It receives values passed through kwargs.
   • Retrieves the list of locations (locations_list) from the XCom returned by the previous task, "get_top3_locations".
   • Establishes a connection to a PostgreSQL database using the PostgresHook.
   • Creates the "s_nikulina_20_ram_location" table in the database if it doesn't exist.
   • Truncates the "s_nikulina_20_ram_location" table.
   • Loads the data from the locations list into the table.
   • Commits the changes to the database and logs the number of inserted rows.

3. Defining the "s-nikulina-20_lesson_5" DAG:

   • Specifies the name of the DAG, the execution schedule, default arguments, and other settings.
   • Sets the tag "s_nikulina-20" to identify the DAG.
   • Defines two tasks within the DAG:
     • "get_top3_locations": Uses the custom operator SNikulinaRamMortyLocationsOperator to retrieve the top 3 locations from an API.
     • "load_locations_to_db": Uses the PythonOperator, which invokes the load_to_db function to load the data into a database.
   • Sets the dependency between the tasks, where "get_top3_locations" is executed before "load_locations_to_db".