json112.2 KB
Fake Orders Dataset (JSON, 1000 records)
The 1000-row orders dataset as JSON — the format twin of the CSV version, relational to the users dataset.
Preview — first 50 linesjson
[
{
"id": 1,
"user_id": 480,
"product": "Reach",
"amount": 284.72,
"date": "2025-03-29"
},
{
"id": 2,
"user_id": 254,
"product": "Actually",
"amount": 258.4,
"date": "2025-07-23"
},
{
"id": 3,
"user_id": 471,
"product": "White",
"amount": 309.38,
"date": "2025-07-03"
},
{
"id": 4,
"user_id": 487,
"product": "Maintain",
"amount": 286.3,
"date": "2025-08-28"
},
{
"id": 5,
"user_id": 325,
"product": "Successful",
"amount": 279.48,
"date": "2025-02-25"
},
{
"id": 6,
"user_id": 144,
"product": "Leg",
"amount": 236.42,
"date": "2025-12-22"
},
{
"id": 7,
"user_id": 54,
"product": "Option",
"amount": 465.57,
"date": "2025-03-15"
},… 3995 lines total — download for the full file.
Specifications
- Records
- 1000
- Schema
- id, user_id, product, amount, date
- Relates To
- users.id
- Seed
- 5678
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.
Related files
- csvFake Users Dataset (CSV, 500 rows)A 500-row dataset of fake but realistic users (name, email, address, date of birth), generated with a fixed seed. Paired with a JSON twin.
- jsonFake Users Dataset (JSON, 500 records)The 500-row users dataset as a JSON array — the format twin of the CSV version, for testing import and conversion.
- csvE-commerce Customers (CSV, 500 rows)A realistic e-commerce customer directory (500 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- jsonE-commerce Customers (JSON, 500 records)The e-commerce customers table as a JSON array — the format twin of the CSV, for import and conversion testing.
- sqlE-commerce Database Schema (SQL)A relational SQL schema (products, customers, orders with primary and foreign keys) plus sample INSERTs — the DDL twin of the e-commerce dataset, for testing schema import and migrations.
- csvE-commerce Orders (CSV, 2000 rows)A realistic e-commerce order lines (customer_id → customers, product_id → products) (2000 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
Generated by generation/data_fake.py. Free for any use, no attribution required — license.