HDF5 Hard, Soft and Dangling Links (.h5)
One array reachable under four names: itself, a hard link sharing its object address, a soft link resolved at access time, and a soft link pointing nowhere. A walker that counts names instead of object addresses reports four arrays and then crashes on the dangling one.
| Name | Kind | Resolves to |
|---|---|---|
| /canonical | dataset | the array itself |
| /hard_link | hard link | the same object address as /canonical |
| /soft_link | soft link | /canonical, resolved at access time |
| /dangling | soft link | /does/not/exist — resolution must fail cleanly |
Specifications
- Datasets
- 1
- Hard Links
- 1
- Soft Links
- 2
- Dangling Links
- 1
- Target
- /canonical
- Dangling Target
- /does/not/exist
- Trap
- a naive walk counts one array four times
Testing contract
Expected to recover- Scenario
- Enumerate the root group, classify each name as dataset, hard link or soft link, and attempt to resolve every one.
- Expected result
- Three names resolve to the same nine-element array with /canonical and /hard_link sharing an object address, while /dangling raises a clean broken-link error rather than aborting the walk.
What is a .h5 file?
HDF5 (.h5) is a binary container format for large, heterogeneous scientific data. It stores multidimensional arrays (datasets) in a hierarchical group structure with attributes and chunked, compressed storage, and is standard in ML, physics, and geoscience.
How to use this file
Use an example .h5 file to test HDF5 readers (h5py, PyTables), group and dataset traversal, and attribute extraction.
How to use this file for testing
“HDF5 Hard, Soft and Dangling Links (.h5)” is a deterministic Novus Examples fixture for Scientific data, Serialization testing, Error handling. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: H5 · 6,216 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.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
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- h5HDF5 Numeric dtype Zoo — Every Width at Its Limits (.h5)Twelve datasets, one per numeric HDF5 type, each holding the extreme values of that type including the uint64 and int64 limits that do not survive a trip through a double. It is the fixture that exposes a reader which widens everything to float64 on the way in.
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