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Juniper Corner Cafe — Numeric expected results

Numeric expected results for Juniper Corner Cafe. Exact table counts, metric formulas, 8 chart points and three negative-test outcomes. Supplier spend=8,715.93 CAD; Net menu sales=10,234.74 CAD; Menu items sold=1,204.00 items; Guest reviews=18.00 records.

Data import
Preview, first 50 linesjson
{
  "schemaVersion": 1,
  "kitId": "business-restaurant-cafe",
  "asOf": "2026-09-08",
  "tableCounts": {
    "purchases": 96,
    "suppliers": 2,
    "ingredients": 6,
    "locations": 1,
    "menu": 4,
    "recipes": 8,
    "sales": 56,
    "inventory": 6,
    "reviews": 18,
    "modifiers": 8,
    "sales_modifiers": 12,
    "refunds": 8,
    "guests": 12,
    "reservations": 12,
    "staff": 8,
    "staffing_shifts": 56,
    "inventory_movements": 48,
    "menu_price_changes": 4
  },
  "primaryKeyDuplicates": 0,
  "foreignKeyFailures": 0,
  "metrics": [
    {
      "id": "purchases-total_price",
      "label": "Supplier spend",
      "value": 8715.93,
      "unit": "CAD",
      "calculation": "Sum purchases.total_price over the included records.",
      "formula": {
        "op": "sum",
        "table": "purchases",
        "column": "total_price"
      }
    },
    {
      "id": "sales-net_sales",
      "label": "Net menu sales",
      "value": 10234.74,
      "unit": "CAD",
      "calculation": "Sum sales.net_sales over the included records.",
      "formula": {
        "op": "sum",
        "table": "sales",
        "column": "net_sales"
      }
… 163 lines total: download for the full file.

Specifications

Kit
restaurant-cafe
Industry
food-service
Schema Version
1
Synthetic
true
As Of
2026-09-08

Testing contract

Reference control
Scenario
Use numeric expected results in the Juniper Corner Cafe purchasing, price-history, menu-costing, inventory, sales, reviews, modifiers, refunds, reservations, staffing, stock-movements, menu-pricing workflow.
Expected result
Exact table counts, metric formulas, 8 chart points and three negative-test outcomes. Supplier spend=8,715.93 CAD; Net menu sales=10,234.74 CAD; Menu items sold=1,204.00 items; Guest reviews=18.00 records.

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

“Juniper Corner Cafe — Numeric expected results” is a deterministic Novus Examples fixture for Data import. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: JSON · 3,753 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("expected-results.json") as f:
    data = json.load(f)
print(type(data), len(data))

Related files

Generated by generation/business_fixtures.py. Free for any use, no attribution required, license.