metrik-core
The vocabulary every other Metrik package agrees on: the artifact envelope, canonical serialization, and content addressing.
This package defines vocabulary, not behaviour (plan.md §4). It has no ML dependencies —
no torch, no transformers — which is enforced in CI by import-linter, not by convention. That
constraint is what lets the artifact layer be installed and reasoned about without a multi-gigabyte
ML stack.
Not published yet. Phase 2 of the roadmap.
What is here so far
| Module | Purpose |
|---|---|
metrik.core.hashing |
Canonical JSON, Digest, content_hash, derivation_hash |
metrik.core.errors |
The error taxonomy plugins raise from |
metrik.core.artifacts |
The envelope every artifact carries |
The two hashes
The subtlest part of the design, and getting it wrong makes both caching and reproducibility silently unreliable. There are two questions, so there are two hashes:
| Question | Answered by |
|---|---|
| Is this the same result as that? | content_hash — over the payload only |
| Have I already computed this, so can I skip the work? | derivation_hash — over how it was asked for |
A single hash cannot do both. Caching needs a key computable before running, so it must cover inputs and parameters rather than results. Dedup and citation need a key covering only the value, so two runs producing identical numbers are recognised as identical even if asked for differently.
Because both are recorded, the store can check a producer's determinism claim rather than
believe it: same derivation_hash, different content_hash, and a declared class of
deterministic means the declaration is false.
Specification
The full contract is docs/planning/artifacts.md. This
package implements §2 (envelope), §3 (hashing and canonicalization), and §4 (blobs).
Canonicalization rules are normative and tested as properties, not examples — see
tests/test_canonical_properties.py.
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