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SciMesh/tests/test_sdk_search.py
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8.4 KiB
Python

"""Tests for the SDK-built similarity-search workload."""
from __future__ import annotations
import csv
from pathlib import Path
import pytest
from scimesh.sdk import (
ArtifactCollection,
DeterminismProfile,
JobRequest,
LocalArtifactStore,
LocalCoreBatchExecutor,
LocalPlanningContext,
StageKind,
assert_manifest_round_trip,
)
from scimesh.workloads.library import default_sdk_registry, default_sdk_runtime
from scimesh.workloads.similarity_search import (
find_molecule_by_id,
search_similar,
write_search_results,
)
def _write_tiny_dataset(path: Path) -> None:
path.write_text(
"chembl_id\tcanonical_smiles\textra\n"
"QUERY\tCCO\tquery\n"
"ALCOHOL\tCCCO\talcohol\n"
"ALKANE\tCCCC\talkane\n"
"BROKEN\tnot-a-smiles\tinvalid\n"
"DUPLICATE\tCCO\tduplicate\n"
"AMINE\tCCN\tamine\n",
encoding="utf-8",
)
def _registered_similarity_search(shard_rows: int = 2):
registry = default_sdk_registry(shard_rows=shard_rows)
runtime = default_sdk_runtime()
description = next(
item
for item in registry.descriptions()
if item.workload.name == "similarity-search"
)
definition, negotiated = registry.require(
description.workload.name,
description.workload.version,
description.package_digest,
runtime=runtime,
)
return registry, runtime, description, definition, negotiated
def _request_for(
dataset: Path,
artifact_store: LocalArtifactStore,
definition,
) -> JobRequest:
input_port = definition.manifest.inputs["input"]
dataset_artifact = artifact_store.import_file(
dataset,
declaration=input_port.schema,
)
return JobRequest(
workload=definition.manifest.workload,
parameters={"query_id": "QUERY", "top_k": 3, "progress_every": 0},
inputs={"input": ArtifactCollection.single(dataset_artifact)},
)
def test_similarity_search_manifest_is_registered_and_negotiable() -> None:
_, runtime, description, definition, negotiated = _registered_similarity_search()
manifest = definition.manifest
assert description.enabled is True
assert manifest.workload.name == "similarity-search"
assert manifest.workload.version == "1.0.0"
assert manifest.determinism is DeterminismProfile.BYTE_EXACT
assert manifest.verifier.verifier.canonical == "exact-artifact@1"
assert set(mode.value for mode in manifest.trust_modes) == {
"trusted",
"untrusted_quorum",
}
assert [stage.kind for stage in manifest.workflow.stages] == [
StageKind.MAP,
StageKind.REDUCE,
]
assert set(definition.runners) == {manifest.workflow.stages[0].entry_point}
assert set(definition.reducers) == {manifest.workflow.stages[1].entry_point}
assert negotiated is not None
assert negotiated.manifest == manifest
assert_manifest_round_trip(manifest)
assert runtime is not None
def test_local_sdk_executor_matches_similarity_search_reference(tmp_path: Path) -> None:
dataset = tmp_path / "molecules.tsv"
_write_tiny_dataset(dataset)
registry, runtime, description, definition, _ = _registered_similarity_search()
artifact_store = LocalArtifactStore(tmp_path / "artifacts")
request = _request_for(dataset, artifact_store, definition)
result = LocalCoreBatchExecutor(
registry,
runtime,
artifact_store,
tmp_path / "sdk-work",
).execute(request, description.package_digest)
result_artifact = result.outputs["result"].items[0].artifact
reference_path = tmp_path / "reference.csv"
query = find_molecule_by_id(dataset, "QUERY")
reference = search_similar(dataset, query, top_k=3, progress_every=0)
write_search_results(reference_path, reference.matches)
assert (
artifact_store.materialize(result_artifact).read_bytes()
== reference_path.read_bytes()
)
assert result.task_key == "reduce/final"
assert dict(result.metrics) == {"matches_emitted": 3, "partial_count": 3}
def test_similarity_search_planning_is_deterministic_ordered_and_path_free(
tmp_path: Path,
) -> None:
dataset = tmp_path / "molecules.tsv"
_write_tiny_dataset(dataset)
registry, runtime, description, definition, _ = _registered_similarity_search()
artifact_store = LocalArtifactStore(tmp_path / "artifacts")
request = _request_for(dataset, artifact_store, definition)
input_artifact = request.inputs["input"].items[0].artifact
first = registry.plan(
request,
description.package_digest,
runtime,
LocalPlanningContext(
artifact_store,
artifact_store,
tmp_path / "first-plan",
allowed_artifacts=(input_artifact,),
),
)
second = registry.plan(
request,
description.package_digest,
runtime,
LocalPlanningContext(
artifact_store,
artifact_store,
tmp_path / "second-plan",
allowed_artifacts=(input_artifact,),
),
)
assert first.to_json() == second.to_json()
assert first.digest == second.digest
assert first.package_digest == definition.manifest.package.digest
assert first.manifest_digest == definition.manifest.digest
assert [task.task_key for task in first.tasks] == [
"map/00000000",
"map/00000001",
"map/00000002",
]
assert all(task.stage_id == "map" for task in first.tasks)
assert all("query_id" not in task.parameters for task in first.tasks)
assert all(task.parameters["query_smiles"] == "CCO" for task in first.tasks)
assert all(task.parameters["top_k"] == 3 for task in first.tasks)
assert all(task.package_digest == first.package_digest for task in first.tasks)
assert all(task.manifest_digest == first.manifest_digest for task in first.tasks)
assert first.resolved_parameters["query_source"] == {
"kind": "chembl_id",
"value": "QUERY",
}
shard_ids: list[list[str]] = []
for task in first.tasks:
artifact = task.inputs["input"].items[0].artifact
with artifact_store.materialize(artifact).open(
encoding="utf-8", newline=""
) as source:
shard_ids.append(
[row["chembl_id"] for row in csv.DictReader(source, delimiter="\t")]
)
assert shard_ids == [
["QUERY", "ALCOHOL"],
["ALKANE", "BROKEN"],
["DUPLICATE", "AMINE"],
]
wire_payload = first.to_json()
assert str(tmp_path) not in wire_payload
assert "file://" not in wire_payload
assert "worker://" not in wire_payload
assert "workspace" not in wire_payload
def test_similarity_search_rejects_ambiguous_or_mistyped_parameters(
tmp_path: Path,
) -> None:
dataset = tmp_path / "molecules.tsv"
_write_tiny_dataset(dataset)
registry, runtime, _, definition, _ = _registered_similarity_search()
artifact_store = LocalArtifactStore(tmp_path / "artifacts")
input_artifact = artifact_store.import_file(
dataset,
declaration=definition.manifest.inputs["input"].schema,
)
base = JobRequest(
workload=definition.manifest.workload,
parameters={"query_id": "QUERY", "top_k": 3},
inputs={"input": ArtifactCollection.single(input_artifact)},
)
for bad_parameters, message in (
({"query_id": "QUERY", "query_smiles": "CCO"}, "oneOf did not match"),
({"query_id": "QUERY", "top_k": 0}, "violates minimum"),
):
request = JobRequest(
workload=base.workload,
parameters=bad_parameters,
inputs=base.inputs,
)
with pytest.raises(ValueError, match=message):
registry.plan(
request,
definition.manifest.package.digest,
runtime,
LocalPlanningContext(
artifact_store,
artifact_store,
tmp_path / "bad-plan",
allowed_artifacts=(input_artifact,),
),
)
def test_similarity_search_workload_definition_is_discoverable() -> None:
from scimesh.sdk import WorkloadDefinition
from scimesh.workloads.search import workload_definition
definition = workload_definition()
assert isinstance(definition, WorkloadDefinition)
assert definition.manifest.workload.name == "similarity-search"
assert definition.manifest.workload.version == "1.0.0"