add airflow task functions

scripts/bigquery_raw_layer.py

@@ -426,16 +426,6 @@ class StagingDataIntegration:
     Input  : RAW layer (Bronze) — raw_fao, raw_worldbank, raw_unicef
     Output : STAGING layer (Silver) — staging_integrated
     Audit  : etl_logs, etl_metadata (Audit → fs_asean_audit)
-
-    Schema staging_integrated:
-        source                 varchar(20)
-        indicator_original     varchar(255)
-        indicator_standardized varchar(255)
-        country                varchar(100)
-        year                   int
-        year_range             varchar(20)
-        value                  float
-        unit                   varchar(20)
     """
 
     def __init__(self, client: bigquery.Client):
@@ -799,3 +789,46 @@ if __name__ == "__main__":
     print(f"STAGING (Silver) : staging_integrated")
     print(f"AUDIT            : etl_logs, etl_metadata")
     print("=" * 60)
+    
+# AIRFLOW TASK FUNCTIONS
+
+def run_verify_connection():
+    from scripts.bigquery_config import verify_setup
+    result = verify_setup()
+    if not result:
+        raise Exception("BigQuery connection failed!")
+    print("BigQuery connection OK")
+
+def run_load_fao():
+    from scripts.bigquery_config import get_bigquery_client
+    client = get_bigquery_client()
+    source = FAODataSource(client)
+    df     = source.run()
+    print(f"FAO loaded: {len(df):,} rows")
+
+def run_load_worldbank():
+    from scripts.bigquery_config import get_bigquery_client
+    client         = get_bigquery_client()
+    fao_source     = FAODataSource(client)
+    df_fao         = fao_source.run()
+    fao_indicators = df_fao['indicator'].unique().tolist()
+    wb_source      = WorldBankDataSource(client, fao_indicators)
+    df             = wb_source.run()
+    print(f"World Bank loaded: {len(df):,} rows")
+
+def run_load_unicef():
+    from scripts.bigquery_config import get_bigquery_client
+    client         = get_bigquery_client()
+    fao_source     = FAODataSource(client)
+    df_fao         = fao_source.run()
+    fao_indicators = df_fao['indicator'].unique().tolist()
+    unicef_source  = UNICEFDataSource(client, fao_indicators)
+    df             = unicef_source.run()
+    print(f"UNICEF loaded: {len(df):,} rows")
+
+def run_staging_integration():
+    from scripts.bigquery_config import get_bigquery_client
+    client  = get_bigquery_client()
+    staging = StagingDataIntegration(client)
+    df      = staging.run()
+    print(f"Staging integrated: {len(df):,} rows")