Clean CSV
A clean, well-formed CSV with a header and 20 rows — the baseline case for CSV parser testing.
Datasets for import testing
Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
10,000-Row CSV
A CSV with 10,000 data rows — for testing streaming parsers, memory handling, and import performance.
Flat JSON Array
A flat JSON array of ten simple objects — the baseline case for JSON parsing and mapping.
JSON Lines (JSONL)
A JSON Lines file with one object per line — for testing streaming/newline-delimited JSON parsers.
Sample XML
A well-formed XML catalogue with nested elements and attributes — for testing XML parsers and XPath queries.
Sample YAML
A YAML configuration file with nested mappings, sequences, inline lists, and comments — for testing YAML parsers.
Sample SQLite Database
A real SQLite database with two related tables — users and orders joined by a foreign key — for testing database importers and SQL tooling.
Fake 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.
Fake 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.
Fake Orders Dataset (CSV, 1000 rows)
A 1000-row orders dataset whose user_id references the users dataset — a relational fixture for testing joins and import flows. Paired with a JSON twin.
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.
NDJSON Stream
A newline-delimited JSON (NDJSON) stream of event records — for testing streaming JSON parsers.
E-commerce Products (CSV, 200 rows)
A realistic e-commerce product catalogue (200 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
E-commerce Products (JSON, 200 records)
The e-commerce products table as a JSON array — the format twin of the CSV, for import and conversion testing.
E-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.
E-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.
E-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.
E-commerce Orders (JSON, 2000 records)
The e-commerce orders table as a JSON array — the format twin of the CSV, for import and conversion testing.
E-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.
Stock OHLCV — Daily Candles (CSV, 252 rows)
A year of daily OHLCV stock candles (open/high/low/close/volume) as a seeded random walk — a realistic finance time-series for testing charting, indicators, and importers. JSON twin included.
Stock OHLCV — Daily Candles (JSON, 252 records)
The daily OHLCV candles as a JSON array — the format twin of the CSV, for charting and time-series testing.
IoT Sensor Readings (CSV, 1440 rows)
A day of IoT sensor readings (temperature, humidity, pressure) at one-minute intervals from three sensors, with a realistic daily cycle plus noise — for testing time-series ingestion and downsampling. JSON twin included.
IoT Sensor Readings (JSON, 1440 records)
The IoT sensor readings as a JSON array — the format twin of the CSV, for time-series testing.
FHIR R4 Patient Bundle (JSON)
A sample HL7 FHIR R4 bundle with a Patient plus vital-sign Observations, an Encounter, and a Condition — a realistic healthcare-interoperability fixture for testing FHIR parsers and mappers. Synthetic data, not a real person.
Product JSON Schema (draft-07)
A JSON Schema (draft-07) describing a product object, with required fields, types, and constraints — paired with a conforming and a deliberately non-conforming instance for testing validators.
Large Transactions Dataset (CSV, 50k rows)
A 50,000-row transactions dataset — an in-repo 'large' fixture for testing streaming CSV parsers, import performance, and pagination. Deterministic (fixed seed).