The ubl_invoice function within the mock-jutsu library provides developers with a robust solution for generating high-fidelity test data tailored for electronic billing systems. Specifically designed to adhere to the OASIS UBL 2.1 standard, this function produces XML payloads that mirror the rigorous Turkey GIB e-fatura requirements. By automating the creation of complex invoice structures, mock-jutsu ensures that engineering teams can focus on core application logic rather than the tedious manual entry of compliant XML documents.
Every generated ubl_invoice is built with mathematical precision, ensuring that the internal financial logic remains flawless. The algorithm guarantees that the net amount plus the calculated tax always equals the gross total, providing a reliable foundation for testing accounting modules. The function generates between one and five line items per document, offering enough variability to test diverse processing scenarios. To meet strict regulatory formatting, the function produces invoice IDs in the INV-YYYY-NNNNN format and utilises uppercase UUIDs, which are critical for systems that perform strict validation on document headers and unique identifiers.
For developers building financial technology or ERP integrations, this mock data is indispensable. The output includes detailed XML blocks such as TaxTotal and LegalMonetaryTotal, allowing for the comprehensive testing of parsing engines and tax reporting modules. Whether you are validating a new accounting API or stress-testing a high-volume invoice gateway, the ability to generate realistic test data on the fly significantly reduces the risk of production errors related to schema non-compliance or rounding discrepancies. This ensures that downstream systems receive data that is structurally and logically sound.
Integrating ubl_invoice into your existing workflow is seamless across various environments. Python developers can invoke it directly via the native library, while DevOps engineers can utilise the CLI for rapid prototyping and shell scripting. Furthermore, the inclusion of a JMeter function allows performance testers to inject realistic UBL payloads into load tests effortlessly. By leveraging mock-jutsu, organisations can ensure their e-invoicing pipelines are resilient, compliant, and ready for global deployment without the overhead of maintaining manual test suites.
mockjutsu generate ubl_invoicemockjutsu bulk ubl_invoice --count 10mockjutsu export ubl_invoice --count 10 --format jsonmockjutsu export ubl_invoice --count 10 --format csvmockjutsu export ubl_invoice --count 10 --format sqlfrom mockjutsu import jutsujutsu.generate('ubl_invoice')jutsu.bulk('ubl_invoice', count=10)jutsu.template(['ubl_invoice'], count=5)${__mockjutsu_ubl(ubl_invoice)}# JMeter Function: __mockjutsu_ubl# Parameter 1: ubl_invoice# Parameter 2: (not required for this function)GET /generate/ubl_invoice# → {"type":"ubl_invoice","result":"...","status":"ok"}GET /bulk/ubl_invoice?count=10POST /template {"types":["ubl_invoice"],"count":1}