airflow.example_dags.example_asset_partition

Attributes

`ingest_team_a_stats`()	Materialize Team A player statistics for the current hourly partition.
`team_b_player_stats`()	Produce hourly partitioned stats for Team B.
`team_c_player_stats`()	Produce hourly partitioned stats for Team C.
`combine_player_stats`([dag_run])	Merge the aligned hourly partitions into a combined dataset.
`compute_player_odds`()	Compute player odds from the combined hourly statistics.
`check_partition_alignment`()
`ingest_sales`()	Ingest regional sales data partitioned by region and time.
`aggregate_sales`([dag_run])	Aggregate sales data for the matched region-day partition.

airflow.example_dags.example_asset_partition.ingest_team_a_stats()[source]: Materialize Team A player statistics for the current hourly partition.

airflow.example_dags.example_asset_partition.team_b_player_stats()[source]: Produce hourly partitioned stats for Team B.

airflow.example_dags.example_asset_partition.team_c_player_stats()[source]: Produce hourly partitioned stats for Team C.

airflow.example_dags.example_asset_partition.combine_player_stats(dag_run=None)[source]: Merge the aligned hourly partitions into a combined dataset.

airflow.example_dags.example_asset_partition.compute_player_odds()[source]

Compute player odds from the combined hourly statistics.

This asset is partition-aware and triggered by the combined stats asset.

airflow.example_dags.example_asset_partition.check_partition_alignment()[source]

airflow.example_dags.example_asset_partition.ingest_sales()[source]: Ingest regional sales data partitioned by region and time.

airflow.example_dags.example_asset_partition.aggregate_sales(dag_run=None)[source]: Aggregate sales data for the matched region-day partition.