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Mock Statements

Mock Statements

Mock statements create temporary mock implementations of datasources or concepts for testing and development.

Syntax

syntax-example
mock_statement: "mock" SCOPE (IDENTIFIER ("," IDENTIFIER)*)? ("with" "(" option_list ")")?

Where SCOPE is one of: concepts, concept, datasources, datasource

Mock Datasources

Create mock data for a datasource:


mock datasource customers;

Mock Multiple

Mock multiple datasources at once:


mock datasources customers, orders, products;

Mock Concepts

Mock specific concepts:


mock concept customer.id, customer.name;

Controlling Mock Size

import customer as c;
mock datasource c.customers with (scale_factor = 1000);

scale_factor controls the base entity population; facts can fan out above that population, and finite domains can limit the available unique values. It is not a promise that every generated table has exactly that many rows.

Use Cases

  • Unit testing queries without database access
  • Rapid prototyping
  • Documentation examples
  • CI/CD pipelines

Example


import customer as customer;
# Mock the imported customer datasource for testing
mock datasource customer.customers;
# Now queries will use mock data
select
    customer.id,
    customer.name
;

Tips

Mock data is generated from the model: ranges and enums guide valid values, and partial/nullable bindings affect the generated relationships. Regex mocks support literals, character classes, alternatives, groups, and repetition. Unsupported constructs such as lookaround and backreferences raise an error; provide explicit fixture data for those models. Generated data exercises model structure but cannot establish production data quality.

Imported datasources use their qualified name, for example mock datasource customer.customers;. See Typing and Validation for the distinction between unit tests and warehouse validation.