def workflow(src_conn_id, src_schema, dt, target_conn_id, target_table):
# TODO Split code into functions
etl_conn = PostgresHook(postgres_conn_id='etl').get_conn()
with Session(etl_conn, f'{dag.dag_id}__{src_schema}') as session:
# Load data
source_conn = MsSqlHook(mssql_conn_id=src_conn_id,
schema=src_schema).get_conn()
query = f"""
SELECT
id, start_time, end_time, type, data
FROM dbo.Orders
WHERE
CONVERT(DATE, start_time) = '{dt}'
"""
df = pd.read_sql_query(query, source_conn)
# Skip if no rows
if df.empty:
raise AirflowSkipException('No rows to load')
# Add service fields
df['etl_source'] = src_schema
df['etl_id'] = session.id
df['hash_id'] = hash_pandas_object(df[['etl_source', 'id']])
# Export data to CSV buffer
buffer = StringIO()
df.to_csv(buffer,
index=False,
sep='|',
na_rep='NUL',
quoting=csv.QUOTE_MINIMAL,
header=False,
float_format='%.8f',
doublequote=False,
escapechar='\\')
buffer.seek(0)
# Push CSV
target_conn = VerticaHook(vertica_conn_id=target_conn_id).get_conn()
copy_stmt = f"""
COPY {target_table}({df.columns.to_list()})
FROM STDIN
DELIMITER '|'
ENCLOSED '"'
ABORT ON ERROR
NULL 'NUL'
"""
cursor = target_conn.cursor()
cursor.copy(copy_stmt, buffer)
session.loaded_rows = cursor.rowcount
session.successful = True
