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Indexable
# ... (previous code)
# Check if insert_df is not empty before performing insertions
if not insert_df.empty:
for index, row in insert_df.iterrows():
pk_value = row[pk + '_source']
table_name = row['your_table_name'] # Replace 'your_table_name' with the actual table name
insert_query = f"INSERT INTO {schema_ext}.{table_name} ("
insert_columns = []
insert_values = []
for column_name, source_val in row.items():
if column_name != pk + '_source':
insert_columns.append(column_name)
insert_values.append(f"'{source_val}'")
insert_query += ", ".join(insert_columns)
insert_query += ") VALUES ("
insert_query += ", ".join(insert_values)
insert_query += ");"
# Execute the INSERT query
try:
print(insert_query)
# cursor_ext.execute(insert_query)
except Exception as e:
continue
# Check if update_df is not empty before performing updates
if not update_df.empty:
for index, row in update_df.iterrows():
pk_value = row[pk + '_source']
table_name = row['your_table_name'] # Replace 'your_table_name' with the actual table name
update_query = f"UPDATE {schema_ext}.{table_name} SET "
column_updates = []
for column_name, source_val in row.items():
if column_name != pk + '_source':
target_val = row[column_name + '_target']
if source_val != target_val:
column_updates.append(f"{column_name} = '{source_val}'")
update_query += ", ".join(column_updates)
update_query += f" WHERE {pk} = '{pk_value}';"
# Execute the UPDATE query
try:
print(update_query)
# cursor_ext.execute(update_query)
except Exception as e:
continue
# ... (the rest of your code)
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