Fintech Double-entry Ledger (JSON)
Balanced double-entry ledger SAMPLE for accounting engine validation tests.
{
"entries": [
{
"account": "cash",
"debit": 1000,
"credit": 0
},
{
"account": "revenue",
"debit": 0,
"credit": 1000
}
],
"balanced": true
}
Specifications
- Domain
- fintech
- Balanced
- true
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
“Fintech Double-entry Ledger (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 · 214 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("ledger-double-entry.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
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- jsonHR — Employees Mini (JSON)JSON twin of the hr/employees-mini mini-dataset.
Generated by generation/data_wave_f.py. Free for any use, no attribution required — license.