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Data

Data files are where parsers quietly break, so this category leans into the edge cases. The CSV set runs from clean to deliberately messy, quoted commas, embedded newlines, ragged rows, semicolon and tab delimiters, a headerless file, a ten-thousand-row file, and a Latin-1 encoded file. JSON comes flat, deeply nested, as JSON Lines, and intentionally invalid for error-handling tests. OpenAPI and JSON Schema twins, paginated API and webhook fixtures, and irregular time-series edges cover modern API QA. There's XML, YAML, and a real SQLite database with related tables, plus faker-generated user and order datasets with documented schemas. Each file spells out its exact quirks in the spec, so when your importer chokes you know precisely which case did it.

Filter data on Browse · 1255 files · 73 subcategories

Results start with a representative from each related test family. Use a card’s variant menu or the filters below to reach a specific format, profile, or failure case; every sample retains its own detail page and download.

Frequently asked questions

What CSV edge cases do you cover?

Encoding matrix (UTF-8 BOM, UTF-16, CP1252, Shift-JIS, Latin-1), delimiter variants, fixed-width, ragged rows, quoted newlines, and domain mini-datasets (SaaS, POS, lab, marketing).

Are datasets realistic or random?

Schemas are documented and values are deterministic synthetic SAMPLE data, shaped like production exports without real customer PII.

How do I test encoding detection?

Filter Browse by purpose encoding-detection or open the encodings subcategory under Data.

Do you include OpenAPI, JSON Schema, or time-series edges?

Yes, later waves add valid/invalid schema twins, pagination and webhook API fixtures, and irregular timestamp / DST-gap series. Filter by schema-testing or timeseries-testing.

Start with one example from each use-case group, then continue through its other test families. Choose a use case, search, or filter to find a specific profile; a card’s variant menu contains its related samples.

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898 test families · 1255 available files · Page 1 of 50

Preview of Bank Transactions (CSV, 60 rows)

Banking

Bank Transactions (CSV, 60 rows)

A bank-transaction statement: 60 debits and credits across three accounts (masked numbers) with running balances, categories, and merchants. Synthetic data for testing statement parsers, categorisation, and reconciliatio

File
CSV · Banking · 60 rows
Preview of Avro: Row Binary + Schema

Binary

Avro: Row Binary + Schema

The same records as Apache Avro: a compact row-based binary format that embeds its own schema, widely used in Kafka pipelines. For testing Avro decoders and schema evolution.

File
AVRO · Binary · 5 rows
Preview of Calendar Parsing - Recoverable LF Line Endings (ICS)

Calendar Contacts

Calendar Parsing - Recoverable LF Line Endings (ICS)

A complete iCalendar structure using LF-only line endings, a common recoverable export defect for tolerant parser tests.

File
ICS · Calendar Contacts · UTF-8
Preview of Pine Property Services: Application for payment continuation sheet

Construction Billing

Pine Property Services: Application for payment continuation sheet

Application for payment continuation sheet for Pine Property Services. 12 contract items, 2 change order lines and a TOTAL row, in the shape of an AIA G703 continuation sheet. Scheduled values total 4113.00; 1490.00 was

File
CSV · Construction Billing · 15 rows
Use case
Data import
Preview of Juniper Workspace Cloud: Annual return JSON

Corporate Records

Juniper Workspace Cloud: Annual return JSON

Annual return JSON for Juniper Workspace Cloud. The same five parts as a nested object with shareCapital, members, officers, personsWithSignificantControl and charges arrays. Numbers that are counts are JSON numbers and

File
JSON · Corporate Records · 4 members
Preview of draw.io Diagram (XML)

Diagrams

draw.io Diagram (XML)

A draw.io (diagrams.net) diagram in its native mxGraphModel XML (a small flowchart) for testing draw.io import/export and XML parsing of diagram files.

File
DRAWIO · Diagrams
Preview of E-commerce Customers (CSV, 500 rows)

Ecommerce

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.

File
CSV · Ecommerce · 500 rows

The use-case group filter replaces the long list of category sections.