Pine Assembly Workshop: Bill of materials JSON
Bill of materials JSON for Pine Assembly Workshop. The DESK structure as a flat array with level, parent and both quantities, plus the cost identity at the top: 25.20 USD of leaf material plus 14.80 USD of added value is the 40.00 USD standard cost the parts table holds. A reader can rebuild the tree from parent and component without needing the indent string the CSV carries.
json
application/json
- Document Set
- manufacturing
- Industry
- manufacturing
- Source Kit
- inventory-manufacturing
- Entity
- Pine Assembly Workshop
- 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
- manufacturing
- Industry
- manufacturing
- Source Kit
- inventory-manufacturing
- Entity
- Pine Assembly Workshop
- Synthetic
- true
- As Of
- 2026-09-08
- Structure Rows
- 6
- Levels
- 2
- Material Cost Per Unit
- 25.20
- Standard Cost
- 40.00
Testing contract
Expected to pass- Scenario
- Rebuild the tree from the structure array and check the cost identity.
- Expected result
- The tree rebuilds to 2 levels with 4 LEG, 1 PANEL and 12 SCREW per finished unit, and 25.20 plus 14.80 is 40.00.
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: Bill of materials 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 · 1,475 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("bill-of-materials.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.