Harbour Kitchen Group: GST/HST return JSON
GST/HST return JSON for Harbour Kitchen Group. The same six lines with the registration, province, rate and period as siblings of the lines array, so the rate can be checked against the line arithmetic without another file.
json
application/json
- Document Set
- tax
- Industry
- retail
- Source Kit
- retail-commerce
- Entity
- Harbour Kitchen Group
- Synthetic
- true
- As Of
- 2026-09-08
Binary json: no in-browser preview. Download it above to open in a compatible application.
Specifications
- Document Set
- tax
- Industry
- retail
- Source Kit
- retail-commerce
- Entity
- Harbour Kitchen Group
- Synthetic
- true
- As Of
- 2026-09-08
- Lines
- 6
- Currency
- CAD
- Rate
- 0.13
Testing contract
Expected to pass- Scenario
- Parse the file and verify line 105 against line 101 times the rate attribute.
- Expected result
- 26214.00 times 0.13 is 3407.82, the value on line 105, and the period start and end bracket the purchase dates the credits are claimed on.
What is a .json file?
JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.
How to use this file
Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.
How to use this file for testing
“Harbour Kitchen Group: GST/HST return JSON” is a deterministic Novus Examples fixture for Data import, JSON parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: JSON · 1,013 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.
Data fixtures document their exact quirks (delimiters, encodings, null handling, schema, and row counts) in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.
Code examples
import json
with open("gst-hst-return.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
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Generated by generation/industry_documents_two.py. Free for any use, no attribution required, license.