The au_acn function within the mock-jutsu library is a specialised utility designed for developers and QA engineers who require valid Australian Company Numbers for their software environments. As part of the IntlIDs category, this function generates a nine-digit identifier that adheres strictly to the formatting standards set by the Australian Securities and Investments Commission (ASIC). By using au_acn, technical teams can ensure that their mock data reflects real-world business identities without the privacy concerns or administrative overhead associated with using actual corporate records. This is particularly useful when building applications tailored for the Australian market where business registration numbers are a mandatory data point.
At the core of the au_acn generation logic is a rigorous MOD-10 weighted checksum algorithm. This specific validation method ensures that every generated number is mathematically consistent, allowing it to pass through input validation layers in enterprise applications. The algorithm applies specific weights to the first eight digits before calculating a remainder that determines the final check digit. This level of precision is what makes mock-jutsu an essential asset for unit testing, as it prevents the common failures associated with simple random number generation in systems that enforce strict data integrity rules. It ensures that the test data is not just a random string of numbers, but a technically accurate representation of an Australian business ID.
Integrating au_acn into your development workflow is seamless, whether you are working directly in a Python script, executing commands via the CLI, or conducting performance tests in JMeter. For instance, testing a B2B registration portal or a financial reporting tool requires test data that can withstand rigorous backend verification. By utilising jutsu.generate('au_acn') or the JMeter function ${__mockjutsu(au_acn,)}, developers can populate databases with hundreds of unique, valid entries in seconds. This facilitates robust stress testing and user acceptance testing (UAT) scenarios, ensuring that the system handles Australian corporate identifiers correctly under various conditions.
The primary benefit of using mock-jutsu for Australian business identifiers is the significant reduction in manual data preparation time. Instead of manually calculating checksums or scraping public registers, developers can rely on this automated utility to provide reliable mock data on demand. This efficiency allows teams to focus on core logic and feature development, knowing that their integration tests are supported by high-quality, compliant identifiers. Whether you are building a small-scale prototype or a large-scale enterprise system, the au_acn function provides the accuracy and reliability necessary for professional software development and comprehensive quality assurance.
mockjutsu generate au_acnmockjutsu bulk au_acn --count 10mockjutsu export au_acn --count 10 --format jsonmockjutsu export au_acn --count 10 --format csvmockjutsu export au_acn --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate au_acn --maskmockjutsu bulk au_acn --count 5 --maskfrom mockjutsu import jutsujutsu.generate('au_acn')jutsu.bulk('au_acn', count=10)jutsu.template(['au_acn'], count=5)# mask=True: regulation-compliant outputjutsu.generate('au_acn', mask=True)jutsu.bulk('au_acn', count=5, mask=True)${__mockjutsu_intl_ids(au_acn)}# JMeter Function: __mockjutsu_intl_ids# Parameter 1: au_acn# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_intl_ids(au_acn,mask)}GET /generate/au_acn# → {"type":"au_acn","result":"...","status":"ok"}GET /bulk/au_acn?count=10POST /template {"types":["au_acn"],"count":1}# mask=true: regulation-compliant outputGET /generate/au_acn?mask=trueGET /bulk/au_acn?count=5&mask=true| Parameter | Values | Description |
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| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |