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json719 B

Pine Assembly Workshop: Carrier rate sheet JSON

Carrier rate sheet JSON for Pine Assembly Workshop. The same two zones as rate-sheet.csv with the rating formula written out as a string, including the fact that the fuel surcharge applies to the base charge as well as the weight charge. That basis is the one most often got wrong.

json

application/json

719 B
Document Set
logistics
Industry
logistics
Source Kit
inventory-manufacturing
Synthetic
true
As Of
2026-09-08
Zones
2

Binary json: no in-browser preview. Download it above to open in a compatible application.

Specifications

Document Set
logistics
Industry
logistics
Source Kit
inventory-manufacturing
Synthetic
true
As Of
2026-09-08
Zones
2
Encoding
UTF-8

Testing contract

Reference control
Scenario
Implement the formula string against the zone table and rate the shipment export.
Expected result
The formula reproduces all 16 lines of freight-charges.csv. Applying the surcharge to the weight charge alone understates every line by the base charge times 0.065, which is the defect shipped in carrier-invoice-fuel-surcharge-basis.csv.

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

“Pine Assembly Workshop: Carrier rate sheet JSON” 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: 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("rate-sheet.json") as f:
    data = json.load(f)
print(type(data), len(data))

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