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Cedar Street Tacos: Whole procure-to-pay chain JSON

Whole procure-to-pay chain JSON for Cedar Street Tacos. One object holding the buyer, both suppliers, all 6 items, the 48-row price list, 4 purchase orders, 4 goods-received notes, 5 invoice documents, 2 credit notes, 2 statements, the remittance advice, the 14-row three-way match and the 6 deliberate defects. Every monetary value is a JSON string with exactly two decimal places.

Preview, first 50 linesjson
{
  "kit": "restaurant-food-truck",
  "title": "Cedar Street Tacos",
  "code": "TRK",
  "asOf": "2026-09-08",
  "currency": "CAD",
  "taxName": "GST",
  "taxRate": "0.05",
  "buyer": {
    "buyer_id": "BUY-TRK",
    "name": "Cedar Street Tacos",
    "street": "77 Cedar Street",
    "city": "Halifax",
    "region": "NS",
    "postcode": "B3K 5E5",
    "country": "CA",
    "tax_id": "CA-BN-200000005",
    "gln": "0626004000014"
  },
  "suppliers": {
    "SUP-01": {
      "supplier_id": "SUP-01",
      "name": "Alder Wholesale",
      "item_prefix": "AW",
      "street": "41 Alder Way",
      "city": "Halifax",
      "region": "NS",
      "postcode": "B3H 1A1",
      "country": "CA",
      "tax_id": "CA-BN-100000001",
      "gln": "0614141000012",
      "terms": "Net 30",
      "iban_label": "Transit 00011 Institution 001 Account 1000001"
    },
    "SUP-02": {
      "supplier_id": "SUP-02",
      "name": "Harbour Food Supply",
      "item_prefix": "HF",
      "street": "8 Harbour Road",
      "city": "Halifax",
      "region": "NS",
      "postcode": "B3J 2B2",
      "country": "CA",
      "tax_id": "CA-BN-100000002",
      "gln": "0614141000029",
      "terms": "Net 30",
      "iban_label": "Transit 00022 Institution 002 Account 2000002"
    }
  },
  "items": {
… 74.8 KB file: download for the full file.

Specifications

Kit
restaurant-food-truck
Schema Version
1
Synthetic
true
As Of
2026-09-08
Currency
CAD
Tax Name
GST
Tax Rate
0.05
Purchase Orders
4
Invoice Documents
5
Distinct Invoice Numbers
4
Credit Notes
2
Statements
2
Deliberate Defects
6
Money Encoding
two-place decimal string

Testing contract

Expected to pass
Scenario
Read whole procure-to-pay chain json into a procure-to-pay import, three-way match and reconciliation workflow for Cedar Street Tacos.
Expected result
One object holding the buyer, both suppliers, all 6 items, the 48-row price list, 4 purchase orders, 4 goods-received notes, 5 invoice documents, 2 credit notes, 2 statements, the remittance advice, the 14-row three-way match and the 6 deliberate defects. Every monetary value is a JSON string with exactly two decimal places.

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

“Cedar Street Tacos: Whole procure-to-pay chain JSON” is a deterministic Testaroo 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 · 76,608 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("procure-to-pay.json") as f:
    data = json.load(f)
print(type(data), len(data))

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