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# Ignore the Airflow module, it is installed in both dev and prod | ||
from airflow import DAG # pylint: disable=no-name-in-module | ||
from airflow.utils.dates import days_ago # pylint: disable=no-name-in-module | ||
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import util | ||
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_CHR_WORKFLOW_ID = 'CHR_DATA' | ||
_CHR_DATASET_NAME = 'chr_data' | ||
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default_args = { | ||
'start_date': days_ago(0), | ||
} | ||
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data_ingestion_dag = DAG( | ||
'chr_ingestion_dag', | ||
default_args=default_args, | ||
schedule_interval=None, | ||
description='Ingestion configuration for CHR', | ||
) | ||
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chr_bq_payload = util.generate_bq_payload(_CHR_WORKFLOW_ID, _CHR_DATASET_NAME, demographic='race') | ||
chr_pop_bq_operator = util.create_bq_ingest_operator('chr_to_bq', chr_bq_payload, data_ingestion_dag) | ||
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chr_exporter_payload = {'dataset_name': _CHR_DATASET_NAME} | ||
chr_exporter_operator = util.create_exporter_operator('chr_exporter', chr_exporter_payload, data_ingestion_dag) | ||
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# Ingestion DAG | ||
(chr_pop_bq_operator >> chr_exporter_operator) |
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# Resources and routines for CHR Data ingestion. | ||
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# Create a BigQuery dataset for CHR data. | ||
resource "google_bigquery_dataset" "chr" { | ||
dataset_id = "chr_data" | ||
location = "US" | ||
} |
6,287 changes: 3,144 additions & 3,143 deletions
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data/cdc_svi_county/cdc_svi_county_totals.csv
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data/chr/analytic_data2024.csv → ...2024_county_health_release_data_-_v1.xlsx
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