Transform the data using the dlt SQL client

A simple alternative to dbt is to query the data using the dlt SQL client and then perform the transformations using Python. The execute_sql method allows you to execute any SQL statement, including statements that change the database schema or data in the tables. In the example below, we insert a row into the customers table. Note that the syntax is the same as for any standard dbapi connection.

pipeline = dlt.pipeline(destination="bigquery", dataset_name="crm")
try:
    with pipeline.sql_client() as client:
        client.execute_sql(
            "INSERT INTO customers VALUES (%s, %s, %s)",
            10,
            "Fred",
            "fred@fred.com"
        )
except Exception:
    ...

In the case of SELECT queries, the data is returned as a list of rows, with the elements of a row corresponding to selected columns.

try:
    with pipeline.sql_client() as client:
        res = client.execute_sql(
            "SELECT id, name, email FROM customers WHERE id = %s",
            10
        )
        # prints column values of the first row
        print(res[0])
except Exception:
    ...

Other transforming tools

If you want to transform the data before loading, you can use Python. If you want to transform the data after loading, you can use SQL or one of the following:

1. dbt (recommended).
2. Pandas.