Generating Sample Data Using the faker Library with Snowpark

Instead of hard-coding the table name in the save_as_table() property, we can provide it as a parameter named FAKE_TABLE_NAME to the stored procedure.

The complete code of the stored procedure now looks like this:

CREATE OR REPLACE PROCEDURE GEN_NAMES(FAKE_TABLE_NAME VARCHAR, ROWS_CNT INTEGER)
RETURNS VARCHAR
LANGUAGE PYTHON
RUNTIME_VERSION = '3.8'
PACKAGES = ('snowflake-snowpark-python', 'faker')
HANDLER = 'gen'
AS
$$
def gen(session, FAKE_TABLE_NAME, ROWS_CNT):
    import faker
    from snowflake.snowpark.types import IntegerType, StringType, DateType, StructType, StructField

    fake = faker.Faker()
    customers_str = fake.csv(data_columns=('{{name}}', '{{street_address}}', '{{phone_number}}', '{{ssn}}', '{{date}}'), num_rows=ROWS_CNT, include_row_ids=True).replace('"', '')
    
    schema_for_customers = StructType([ 
        StructField("ID", IntegerType(), False),  
        StructField("NAME", StringType(), False),  
        StructField("ADDRESS", StringType(), False), 
        StructField("PHONE", StringType(), False),  
        StructField("SSN", StringType(), False),  
        StructField("BIRTHDATE", DateType(), False)
    ])

    cust_df = session.create_dataframe([x.split(',') for x in customers_str.split('rn')[0:-1]], schema_for_customers)
    cust_df.write.mode("overwrite").save_as_table(FAKE_TABLE_NAME)

    return('Success')
$$;

To execute the stored procedure, for example to generate 100 customer records and save them to Snowflake in a table named FAKE_CUSTOMERS, we use the following command:

CALL GEN_NAMES('FAKE_CUSTOMERS', 100);