Pine Property Services: Rent roll JSON
Rent roll JSON for Pine Property Services. The same 6 demises with the building level figures hoisted out of the rows: lettable area, common area, occupied area and occupancy by area. Occupancy is stated as a percentage of lettable area, not of lettable plus common, which is the choice that moves the number.
json
application/json
- Document Set
- property
- Industry
- trades-property
- Source Kit
- trades-property
- Entity
- Pine Property Services
- 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
- property
- Industry
- trades-property
- Source Kit
- trades-property
- Entity
- Pine Property Services
- Synthetic
- true
- As Of
- 2026-09-08
- Units
- 6
- Lettable Area
- 1200.00
- Occupied Area
- 1070.00
- Occupancy Denominator
- lettable area
Testing contract
Expected to pass- Scenario
- Recompute occupancy from the units array and compare with the building object.
- Expected result
- Occupied area is 1070.00 of 1200.00, which the file states to four decimal places. Including the common area in the denominator would give a different and lower figure, and the file says which denominator it used.
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 Property Services: Rent roll 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 · 3,581 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("rent-roll.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.