Alder Table Bistro: Daily Z-read as structured data
Daily Z-read as structured data for Alder Table Bistro. The same Z-read as JSON: 4 item lines, a summary block, 3 tender lines that sum to the total collected, 2 voids, one comp, 1 refund traced to its sales id, and a cash drawer block whose expected figure less the counted figure equals the declared over/short of -0.35 CAD.
json
application/json
- Kit
- restaurant-bistro
- Industry
- food-service
- Schema Version
- 1
- Synthetic
- true
- As Of
- 2026-09-08
- Currency
- CAD
Binary json: no in-browser preview. Download it above to open in a compatible application.
Specifications
- Kit
- restaurant-bistro
- Industry
- food-service
- Schema Version
- 1
- Synthetic
- true
- As Of
- 2026-09-08
- Currency
- CAD
- Period Start
- 2026-08-20
- Period End
- 2026-09-02
- Business Date
- 2026-08-28
- Tenders
- 3
- Voids
- 2
- Encoding
- UTF-8
Testing contract
Expected to pass- Scenario
- Use daily z-read as structured data in the Alder Table Bistro costing and daily operations workflow.
- Expected result
- The same Z-read as JSON: 4 item lines, a summary block, 3 tender lines that sum to the total collected, 2 voids, one comp, 1 refund traced to its sales id, and a cash drawer block whose expected figure less the counted figure equals the declared over/short of -0.35 CAD.
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
“Alder Table Bistro: Daily Z-read as structured data” 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: UTF-8. 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("z-report-daily-cashup.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
- jsonAlder Table Bistro: Cost of goods sold documentCost of goods sold document for Alder Table Bistro. The same statement as JSON, listing all 24 purchase ids it consumed so the total can be checked against the shared purchases table by id. Totals: opening 1736.91, purchases 2834.82, closing 2996.92, cost of goods sold 1574.81 CAD.
- jsonAlder Table Bistro: Plate costing documentPlate costing document for Alder Table Bistro. A nested JSON document with 4 dishes and 12 recipe lines, an ingredient block carrying the pack and reference purchase for every price, and an explicit roundingRules object naming the decimal places used at each step.
- jsonCedar Street Tacos: Cost of goods sold documentCost of goods sold document for Cedar Street Tacos. The same statement as JSON, listing all 24 purchase ids it consumed so the total can be checked against the shared purchases table by id. Totals: opening 1911.28, purchases 972.73, closing 324.44, cost of goods sold 2559.57 CAD.
- jsonCedar Street Tacos: Daily Z-read as structured dataDaily Z-read as structured data for Cedar Street Tacos. The same Z-read as JSON: 4 item lines, a summary block, 3 tender lines that sum to the total collected, 2 voids, one comp, 1 refund traced to its sales id, and a cash drawer block whose expected figure less the counted figure equals the declared over/short of -0.35 CAD.
- jsonCedar Street Tacos: Plate costing documentPlate costing document for Cedar Street Tacos. A nested JSON document with 4 dishes and 18 recipe lines, an ingredient block carrying the pack and reference purchase for every price, and an explicit roundingRules object naming the decimal places used at each step.
- jsonCopper Oven Bakery: Cost of goods sold documentCost of goods sold document for Copper Oven Bakery. The same statement as JSON, listing all 24 purchase ids it consumed so the total can be checked against the shared purchases table by id. Totals: opening 1479.58, purchases 2420.01, closing 3276.15, cost of goods sold 623.44 CAD.
Generated by generation/restaurant_costing.py. Free for any use, no attribution required, license.