DBF — dBase / xBase Table
The employee table as a dBase (DBF) file — the venerable xBase table format still emitted by GIS tools and legacy databases. For testing DBF readers and DBF→CSV 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
- dBase III (DBF)
- Fields
- 6
What is a .dbf file?
A dBASE table (.dbf) is a legacy binary tabular format with a fixed-width header describing columns (name, type, length) followed by fixed-length records. It persists today as the attribute table of GIS shapefiles and in legacy database exchange.
How to use this file
Use an example .dbf file to test dBASE/xBase readers, shapefile attribute parsing, and DBF-to-CSV conversion.
How to use this file for testing
“DBF — dBase / xBase Table” is a deterministic Novus Examples fixture for Conversion 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 · 6 fields · 7 columns. 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
- avroAvro — Row Binary + SchemaThe 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.
- bsonBSON — Binary JSON (MongoDB)The records as BSON — the binary-JSON encoding MongoDB stores documents in. For testing BSON decoders and JSON↔BSON conversion.
- cborCBOR — Concise Binary ObjectThe records as CBOR — the IETF concise binary object representation used in IoT and COSE/WebAuthn. For testing CBOR decoders and JSON↔CBOR conversion.
- featherFeather — Arrow IPC TableThe same table as Feather (Arrow IPC file) — the zero-copy on-disk form of an Apache Arrow table. For testing Arrow readers and fast columnar interchange.
- h5HDF5 — Hierarchical Scientific DataA small HDF5 file with a compound 'employees' dataset and a numeric 'readings' grid — the hierarchical format used across science and ML. For testing h5py/HDF5 readers and conversion.
- msgpackMessagePack — Binary JSONThe 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.
Generated by generation/data_binary.py. Free for any use, no attribution required — license.