Novus Examples, Real, documented example files for testing

Stereo/Mono Twin 03: Stereo (659 Hz)

Stereo twin of the 659 Hz tone (L=mono, R=phase-shifted) for stereo↔mono conversion tests.

File: WAV · Stereo Mono · 16000
Use case: Audio analysisConversion testing· Paired fixture

Stereo/Mono Twin 04: Mono (784 Hz)

Mono 784 Hz twin. Pair with the stereo file for channel-count / downmix tests.

File: WAV · Stereo Mono · 16000
Use case: Audio analysisConversion testing· Paired fixture

Stereo/Mono Twin 04: Stereo (784 Hz)

Stereo twin of the 784 Hz tone (L=mono, R=phase-shifted) for stereo↔mono conversion tests.

File: WAV · Stereo Mono · 16000
Use case: Audio analysisConversion testing· Paired fixture

STL: ASCII Corner SAMPLE

Tiny ASCII STL SAMPLE (corner) for mesh importer smoke tests.

File: STL · Textured · ASCII
Use case: Conversion testing· Conversion set

STL: ASCII Cube

A 10 mm cube as ASCII STL, human-readable facet/normal/vertex records. The most portable 3D-print mesh format; for testing STL parsers and slicers.

File: STL · Mesh · 12 triangles
Use case: Conversion testing· Conversion set

STL: ASCII Pyramid SAMPLE

Tiny ASCII STL SAMPLE (pyramid) for mesh importer smoke tests.

File: STL · Textured · ASCII
Use case: Conversion testing· Conversion set

STL: ASCII Slab SAMPLE

Tiny ASCII STL SAMPLE (slab) for mesh importer smoke tests.

File: STL · Textured · ASCII
Use case: Conversion testing· Conversion set

STL: ASCII Tetra SAMPLE

Tiny ASCII STL SAMPLE (tetra) for mesh importer smoke tests.

File: STL · Textured · ASCII
Use case: Conversion testing· Conversion set

STL: ASCII Wedge SAMPLE

Tiny ASCII STL SAMPLE (wedge) for mesh importer smoke tests.

File: STL · Textured · ASCII
Use case: Conversion testing· Conversion set

STL: Binary Cube

The same 10 mm cube as binary STL: an 80-byte header, a triangle count, and packed little-endian floats. Compact; for testing binary-STL readers.

File: STL · Mesh · 12 triangles
Use case: Conversion testing· Conversion set

STL: Signpost in Millimetres (the 3D-printing convention)

The signpost in millimetres as ASCII STL. STL has no unit field either, but every slicer assumes millimetres, which is why an STL exported in metres arrives as a 1 mm speck and one exported in inches arrives 25.4x too big.

File: STL · Units
Use case: Conversion testingMetadata testing+1· Conversion set

STL: Zero-area Facets with Null Normals

An ASCII STL of the reference cube with two extra facets that have no area and declare a null (0 0 0) normal, exactly what CAD tessellators emit at a sliver. Slicers either drop them, warn, or divide by zero; this is how you find out which.

File: STL · Degenerate
Use case: Mesh repair testingMesh processing QA· Conversion set

Stock block geometry: expected results and reader evidence

One closed faceted BREP with six planar faces. Triangulation yields 12 triangles, eight unique geometric positions, bounds 0,0,0 to 40,30,20 mm, surface area 5,200 mm² and volume 24,000 mm³. Hard-normal vertices may be duplicated.

File: JSON · Business Cad · 12 triangles
Use case: Data import

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.

File: CSV · Finance · 252 rows
Use case: Data importTime-series data+1· Conversion set

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.

File: JSON · Finance · 252 records
Use case: Data importTime-series data· Conversion set

Store Receipt: Scanned (image-only PDF)

The same café receipt as an image-only 'scan': no text layer, with a slight rotation and grain so it reads like a photographed receipt. Paired with the searchable version as OCR ground truth.

File: PDF · PDF
Use case: OCR testingPDF editor testing· Paired fixture

Store Receipt: Searchable PDF

A realistic café receipt as a searchable PDF with a real text layer: the OCR ground truth paired with an image-only scanned twin, so you can score OCR output against known text.

File: PDF · PDF
Use case: OCR testingPDF editor testing· Paired fixture

Structured Application Log: 300 JSON Lines (jsonl)

Three hundred newline-delimited JSON log records from five services, each with a timestamp, level, logger, message, a nested http object and request and order identifiers. The severity mix is counted in the spec table, so a level filter can be asserted rather than eyeballed.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: Blank, Non-JSON and BOM-Prefixed Lines (jsonl)

A JSON Lines file with the debris a real container stream carries: blank and whitespace-only lines, one bare stderr write from a C library, a mid-file byte-order mark and two lines that are valid JSON but not objects. Five real records are in there.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: Clock Skew Across Three Hosts (jsonl)

Three hosts writing to one stream with disagreeing clocks: one 45 seconds behind and one six hours ahead because NTP is unreachable. Interleaved by host, so a naive tail shows events from the future and a retention window silently drops the past.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: Deeply Nested and Very Wide Context (jsonl)

One record nested 24 levels deep, one with 200 sibling keys and one holding a 12 by 12 array of arrays. Field-flattening pipelines turn these into hundreds of dotted keys, and depth limits truncate them silently: this is where both behaviours become visible.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: Duplicate Keys in One JSON Object (jsonl)

Records whose objects declare the same key twice, including one where the duplicate changes the severity from debug to error. RFC 8259 permits duplicate names and leaves the outcome undefined, so last-wins and first-wins parsers disagree about what these records say.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: High-Cardinality Label Fields (jsonl)

Every record carries five fields that are unique to it: session, customer, device, pod name and container ID. Harmless as log text, ruinous the moment they are promoted to indexed labels, which is the mistake this fixture exists to make measurable.

File: JSONL · Logs
Use case: ObservabilityLog parsing+1· Conversion set

Structured Log: logfmt (log)

A structured application log in logfmt, space-separated key=value pairs (ts, level, msg, method, path, status, duration, request_id) as used by many Go and Heroku-style services. A fixture for testing logfmt parsers.

File: LOG · Logs
Use case: Log parsingObservability

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