FINANCE — Ledger Lines (JSON)
JSON twin of the finance/ledger-lines mini-dataset.
[
{
"entry_id": "L0001",
"account": "cash",
"debit": 100,
"credit": 0
},
{
"entry_id": "L0002",
"account": "revenue",
"debit": 0,
"credit": 100
},
{
"entry_id": "L0003",
"account": "supplies",
"debit": 25,
"credit": 0
},
{
"entry_id": "L0004",
"account": "cash",
"debit": 0,
"credit": 25
},
{
"entry_id": "L0005",
"account": "ar",
"debit": 50,
"credit": 0
},
{
"entry_id": "L0006",
"account": "revenue",
"debit": 0,
"credit": 50
},
{
"entry_id": "L0007",
"account": "cash",
"debit": 50,
"credit": 0
},
{
"entry_id": "L0008",
"account": "ar",
"debit": 0,
"credit": 50
}
]Specifications
- Records
- 8
- Schema
- entry_id, account, debit, credit
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
“FINANCE — Ledger Lines (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: 8 records · schema: entry_id, account, debit, credit. 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-lines.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
- jsonColumnar Nulls Schema (JSON)JSON description of nullable columns in the null-heavy columnar fixtures.
- jsonFintech Double-entry Ledger (JSON)Balanced double-entry ledger SAMPLE for accounting engine validation tests.
- jsonFlat JSON ArrayA flat JSON array of ten simple objects — the baseline case for JSON parsing and mapping.
- jsonHealthcare Claim (FHIR SAMPLE JSON)Synthetic FHIR Claim resource for healthcare billing parser tests — not a real patient.
- jsonHealthcare Procedure Codes (JSON)SAMPLE procedure code list with fees for medical billing calculator tests.
- jsonHR — Employees Mini (JSON)JSON twin of the hr/employees-mini mini-dataset.
Generated by generation/breadth_extra_wave_c.py. Free for any use, no attribution required — license.