#Python dummy data generator code#

The code also stores generated unique customer IDs ( cust_ids) as a list in order to compare newly-generated IDs with existing to ensure uniqueness. customer note text field ( note) - generated using Faker.customer date of birth ( dob) - generated using Faker.customer phone number ( phone_number) - generated using Faker.customer address ( address) - generated using Faker.customer name ( name) - generated using Faker use_weighting=True means an attempt is made to have the frequency of generated values match real-world frequencies ('Lisa' will be more frequently generated than will 'Braelynn') the locales denote from where names are being generated.customer ID ( cust_id) - generated using the helper functions outlined above.Our 10,000 customers will include the following attributes: After this, the process is repeated to create a 2 digit integer, which becomes the decimal cents portion of the cost, to the right hand side of the decimal point. random_n_digits() is then used to generate an integer of that length. To generate a cost, the function randomly generates an integer between 1 and 4, which will become the length of the dollar place digits string for our generated cost. The final function's utility is given away by its name, generate_cost(). It simply takes a list of integers and an integer representing the length of a new integer to be created, uses the previous function to create a new integer of this length, checks this new integer against the unique list, and if this new integer is also unique, it gets added to the list. The next function, unique_rand(), will be used to ensure that a generated identifier is unique to our system.

This will come in handy for identifiers such as customer and order numbers.

Python dummy data generator