Fintech FX Rates Time-series (JSON)
Daily USD/EUR SAMPLE rates for FX chart and conversion tests.
[
{
"date": "2026-01-01",
"pair": "USD/EUR",
"rate": 0.92
},
{
"date": "2026-01-02",
"pair": "USD/EUR",
"rate": 0.921
}
]
Specifications
- Domain
- fintech
- Pairs
- 1
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.
How to use this file for testing
“Fintech FX Rates Time-series (JSON)” is a deterministic Novus Examples fixture for Time-series data, JSON parsing. Irregular timestamps, DST gaps, and duplicate keys for time-series importers and charting libraries.
Documented properties for this file: JSON · 166 bytes. 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.
Valid and intentionally invalid siblings are labelled in title and description. Assert parsers accept the valid twin and fail loudly on the invalid one; for time series, check DST gaps and duplicate keys against the spec table.
Code examples
import json
with open("fx-rates.json") as f:
data = json.load(f)
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Generated by generation/data_wave_f.py. Free for any use, no attribution required — license.