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Alder Books Reconciliation: General ledger export JSON

General ledger export JSON for Alder Books Reconciliation. The same 66 lines as general-ledger-export.csv with a totals object declaring 22464.00 of debits and the same of credits. The period runs from the earliest invoice date 2026-07-02 to the last bank movement 2026-08-24.

json

application/json

19.1 KB
Document Set
accounting
Industry
finance
Source Kit
accounting-reconciliation
Synthetic
true
As Of
2026-09-08
Rows
66

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

Specifications

Document Set
accounting
Industry
finance
Source Kit
accounting-reconciliation
Synthetic
true
As Of
2026-09-08
Rows
66
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Parse the ledger and assert the totals object against the line array.
Expected result
lines has 66 members; summing the debit column gives 22464.00 and the credit column 22464.00, both matching the totals object, and no line carries a value in both columns.

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

“Alder Books Reconciliation: General ledger export 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: 66 rows · 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("general-ledger-export.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.