MessagePack — Binary JSON
The records as MessagePack — a compact binary serialization that maps onto the JSON data model, common in caches and RPC. For testing MessagePack codecs and JSON↔MessagePack conversion.
| idint64 | namestring | emailstring | departmentstring | activebool | scoredouble | joineddate |
|---|---|---|---|---|---|---|
| 1001 | Ada Lovelace | ada.lovelace@example.com | Engineering | true | 98.5 | 2021-03-01 |
| 1002 | Alan Turing | alan.turing@example.com | Research | true | 95 | 2020-06-15 |
| 1003 | Grace Hopper | grace.hopper@example.com | Engineering | false | 91.2 | 2019-11-20 |
| 1004 | Katherine Johnson | katherine.johnson@example.com | Operations | true | 96.8 | 2022-01-10 |
| 1005 | Edsger Dijkstra | edsger.dijkstra@example.com | Research | false | 89.4 | 2018-09-05 |
Specifications
- Rows
- 5
- Columns
- 7
- Format
- MessagePack
- Model
- document
What is a .msgpack file?
MessagePack (.msgpack) is a compact binary serialization format — like JSON but smaller and faster — that encodes maps, arrays, strings, numbers, and binary blobs in a self-describing byte stream. It is popular for caching, IPC, and network protocols.
How to use this file
Use an example .msgpack file to test MessagePack decoders and MessagePack-to-JSON converters, or to verify binary round-trips.
How to use this file for testing
“MessagePack — Binary JSON” is a deterministic Novus Examples fixture for Conversion testing, Serialization testing. The same content exported across many formats and linked as a group, so you can convert one and diff against the expected twin.
Documented properties for this file: 5 rows · 7 columns · MessagePack. 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.
Related files
- pbProtobuf — Encoded MessageA single protobuf User message in binary wire format (varint + length-delimited fields) — the serialized counterpart to the user.proto schema. For testing protobuf decoders without the generated code.
- orcConvert v2 ORC Employee Table SourceBinary orc source for the five-row P8 employee conversion table, preserving ids, names, departments, booleans, and scores. Stable P8 artifact p8-convert-orc-source.
- csvConvert v2 ORC Expected CSVCsv semantic reference for the five-row P8 employee conversion table, preserving ids, names, departments, booleans, and scores. Stable P8 artifact p8-convert-orc-csv.
- jsonConvert v2 ORC Expected JSONJson semantic reference for the five-row P8 employee conversion table, preserving ids, names, departments, booleans, and scores. Stable P8 artifact p8-convert-orc-json.
- pbConvert v2 Protobuf Creator RecordValid Protobuf wire record with string, uint32, and string fields for schema-guided decoding. Stable P8 artifact p8-convert-protobuf-source.
- jsonConvert v2 Protobuf Expected JSONExpected JSON semantic result for the schema-guided Protobuf decode. Stable P8 artifact p8-convert-protobuf-expected.
Generated by generation/data_binary.py. Free for any use, no attribution required — license.