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Merged
tae898 merged 1 commit into from
Nov 1, 2026
Merged

tests: run 13 vector tests on the native build through get_metadata() #168

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22 changes: 2 additions & 20 deletions tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,8 +126,6 @@
"test_server_wire_protocols.py::test_a_protocol_host_overrides_the_server_host_for_that_protocol_only": "reads the server's GlobalConfiguration through the JVM",
"test_sql_constraints_and_maintenance.py::test_backup_check_and_rebuild_index_statements": "sets GlobalConfiguration.SERVER_BACKUP_DIRECTORY through the JVM",
"test_vector_params_verification.py::TestVectorParams::test_jvm_heap_check": "reads java.lang.Runtime through JPype",
"test_vector_params_verification.py::TestVectorParams::test_wrapper_default_matches_engine_default": "reads the engine default through java.lang.String and GlobalConfiguration",
"test_vector_params_verification.py::TestVectorParams::test_omitted_max_connections_reaches_the_index": "reads the engine default through java.lang.String and GlobalConfiguration",
# Java objects built or read by the test
"test_conversion_fixes.py::test_java_instants_convert_without_losing_microseconds": JAVA_CLASS,
"test_type_conversion.py::test_offset_datetime_conversion": JAVA_CLASS,
Expand Down Expand Up @@ -197,24 +195,8 @@
"test_resultset.py::TestSmallResultsCostOneBridgeCall::test_the_bridge_closes_what_it_drains_and_only_that": BRIDGE_COUNT,
"test_vector.py::TestLSMVectorIndex::test_lsm_vector_search_looks_up_all_hits_in_one_bridge_call": BRIDGE_COUNT,
"test_vector.py::TestLSMVectorIndex::test_lsm_vector_search_uses_database_rid_conversion": "intercepts Database.to_java_rid, the JPype path's RID conversion",
# the Java index behind the wrapper
"test_vector.py::TestLSMVectorIndex::test_create_vector_index_with_pq_params": JAVA_INDEX,
"test_vector.py::TestLSMVectorIndex::test_create_vector_index_with_custom_id_property": JAVA_INDEX,
"test_vector.py::TestLSMVectorIndex::test_lsm_vector_search_approximate_product": JAVA_INDEX,
"test_vector.py::TestLSMVectorIndex::test_lsm_vector_search_approximate_typeindex": JAVA_INDEX,
**{
f"test_vector_params_verification.py::TestVectorParams::{name}": JAVA_INDEX
for name in (
"test_quantization_param",
"test_store_vectors_in_graph_param",
"test_encoding_param",
"test_add_hierarchy_param",
"test_per_index_cache_params",
"test_quantization_none",
"test_quantization_binary",
"test_quantization_product",
)
},
# the Java index behind the wrapper: encoding is a setting get_metadata() does not return and the native library does not expose
"test_vector_params_verification.py::TestVectorParams::test_encoding_param": JAVA_INDEX,
}


Expand Down
38 changes: 22 additions & 16 deletions tests/test_vector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -220,15 +220,12 @@ def test_create_vector_index_with_pq_params(self, test_db):
pq_training_limit=5000,
)

java_idx = index._java_index
if "TypeIndex" in java_idx.getClass().getName():
java_idx = java_idx.getSubIndexes().get(0)

meta = java_idx.getMetadata()
assert meta.pqSubspaces == 4
assert meta.pqClusters == 128
assert meta.pqCenterGlobally is False
assert meta.pqTrainingLimit == 5000
meta = index.get_metadata()
assert meta["quantization"] == "PRODUCT"
assert meta["pq_subspaces"] == 4
assert meta["pq_clusters"] == 128
assert meta["pq_center_globally"] is False
assert meta["pq_training_limit"] == 5000

def test_create_vector_index_with_custom_id_property(self, test_db):
"""Custom id_property should propagate to vector metadata."""
Expand All @@ -244,11 +241,10 @@ def test_create_vector_index_with_custom_id_property(self, test_db):
id_property="slug",
)

java_idx = index._java_index
if "TypeIndex" in java_idx.getClass().getName():
java_idx = java_idx.getSubIndexes().get(0)

assert str(java_idx.getMetadata().idPropertyName) == "slug"
assert index.get_metadata()["id_property"] == "slug"
# an index read back from the schema carries it too
reread = test_db.schema.get_vector_index("Doc", "embedding")
assert reread.get_metadata()["id_property"] == "slug"

def test_lsm_vector_search(self, test_db):
"""Test searching in vector index (JVector implementation)."""
Expand Down Expand Up @@ -398,7 +394,12 @@ def test_lsm_vector_search_approximate_product(self, test_db):
pq_clusters=3,
)

assert "TypeIndex" in index._java_index.getClass().getName()
# the wrapper holds the index of the type (the JVM build's TypeIndex);
# the vectors live in its bucket index, which has a name of its own
meta = index.get_metadata()
assert meta["index_name"] == "Doc[embedding]"
assert meta["bucket_index_name"] != meta["index_name"]
assert index.get_quantization() == "PRODUCT"

vectors = [
[1.0, 0.0, 0.0],
Expand Down Expand Up @@ -437,7 +438,12 @@ def test_lsm_vector_search_approximate_typeindex(self, test_db):
pq_clusters=2,
)

assert "TypeIndex" in index._java_index.getClass().getName()
# the wrapper holds the index of the type (the JVM build's TypeIndex);
# the vectors live in its bucket index, which has a name of its own
meta = index.get_metadata()
assert meta["index_name"] == "Doc[embedding]"
assert meta["bucket_index_name"] != meta["index_name"]
assert index.get_quantization() == "PRODUCT"

vectors = [
[1.0, 0.0, 0.0],
Expand Down
155 changes: 38 additions & 117 deletions tests/test_vector_params_verification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,20 +36,8 @@ def test_quantization_param(self, test_db):
# Verify via wrapper convenience method
assert index.get_quantization() == "INT8"

# Verify by inspecting Java object directly
# Accessing the underlying Java object's metadata
java_index = index._java_index

# Depending on if it's a TypeIndex or LSMVectorIndex directly
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

# In Java: index.getMetadata().quantizationType
# JPype allows attribute access for getters or fields
# Note: the exact field name depends on the Java class implementation of metadata
# Given src/arcadedb/vector.py uses .quantizationType:
assert str(idx_to_check.getMetadata().quantizationType) == "INT8"
# Verify through the engine's own metadata of the index
assert index.get_metadata()["quantization"] == "INT8"

def test_store_vectors_in_graph_param(self, test_db):
"""Test sending store_vectors_in_graph parameter."""
Expand All @@ -61,43 +49,13 @@ def test_store_vectors_in_graph_param(self, test_db):
"StoreDoc", "embedding", dimensions=3, store_vectors_in_graph=True
)

# Accessing the underlying Java object's metadata
java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)
assert index.get_metadata()["store_vectors_in_graph"] is True

metadata = idx_to_check.getMetadata()

# We need to find where "storeVectorsInGraph" is stored.
# It might be a field, or it might be in map-like structure if it was passed via JSON.
# Let's inspect what we can.

print(f"\nMetadata Class: {metadata.getClass().getName()}")
print(f"Metadata String: {metadata.toString()}")

# Attempt to check property directly if it's exposed as a field matching the JSON key
# Or check via getter if available

val = None
try:
# Try field access
val = metadata.storeVectorsInGraph
except Exception:
try:
# Try getter
val = metadata.isStoreVectorsInGraph()
except Exception:
val = None # neither accessor: the string fallback below decides

if val is None:
# Try inspecting the string representation as a fallback for verification
assert (
"storeVectorsInGraph" in metadata.toString()
or "storeVectorsInGraph=true" in metadata.toString()
)
else:
assert val is True
# and the default stays off
test_db.command("sql", "CREATE VERTEX TYPE NoStoreDoc")
test_db.command("sql", "CREATE PROPERTY NoStoreDoc.embedding ARRAY_OF_FLOATS")
plain = test_db.create_vector_index("NoStoreDoc", "embedding", dimensions=3)
assert plain.get_metadata()["store_vectors_in_graph"] is False

def test_encoding_param(self, test_db):
"""Test sending encoding parameter for native INT8 storage."""
Expand Down Expand Up @@ -141,20 +99,14 @@ def test_add_hierarchy_param(self, test_db):
"HierDoc", "embedding", dimensions=3, add_hierarchy=True
)

java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

metadata = idx_to_check.getMetadata()
assert index.get_metadata()["add_hierarchy"] is True

try:
assert metadata.addHierarchy is True
except AttributeError:
assert (
"addHierarchy" in metadata.toString()
or "addHierarchy=true" in metadata.toString()
)
test_db.command("sql", "CREATE VERTEX TYPE FlatDoc")
test_db.command("sql", "CREATE PROPERTY FlatDoc.embedding ARRAY_OF_FLOATS")
flat = test_db.create_vector_index(
"FlatDoc", "embedding", dimensions=3, add_hierarchy=False
)
assert flat.get_metadata()["add_hierarchy"] is False

def test_params_persistence(self, tmp_path):
"""Verify parameters persist after reload."""
Expand Down Expand Up @@ -210,27 +162,9 @@ def test_per_index_cache_params(self, test_db):
mutations_before_rebuild=789,
)

java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

metadata = idx_to_check.getMetadata()

# Direct field access is available on LSMVectorIndexMetadata; fall back to string inspection if not.
try:
assert metadata.graphBuildCacheSize == 456
assert metadata.mutationsBeforeRebuild == 789
except AttributeError:
meta_str = metadata.toString()
assert (
"graphBuildCacheSize=456" in meta_str
or "graphBuildCacheSize: 456" in meta_str
)
assert (
"mutationsBeforeRebuild=789" in meta_str
or "mutationsBeforeRebuild: 789" in meta_str
)
metadata = index.get_metadata()
assert metadata["graph_build_cache_size"] == 456
assert metadata["mutations_before_rebuild"] == 789

def test_quantization_none(self, test_db):
"""Test sending quantization parameter NONE."""
Expand All @@ -243,12 +177,7 @@ def test_quantization_none(self, test_db):

assert index.get_quantization() == "NONE"

java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

assert str(idx_to_check.getMetadata().quantizationType) == "NONE"
assert index.get_metadata()["quantization"] == "NONE"

def test_quantization_binary(self, test_db):
"""Test sending quantization parameter BINARY."""
Expand All @@ -263,12 +192,7 @@ def test_quantization_binary(self, test_db):

assert index.get_quantization() == "BINARY"

java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

assert str(idx_to_check.getMetadata().quantizationType) == "BINARY"
assert index.get_metadata()["quantization"] == "BINARY"

def test_quantization_product(self, test_db):
"""Test sending quantization parameter PRODUCT (PQ)."""
Expand All @@ -283,28 +207,26 @@ def test_quantization_product(self, test_db):

assert index.get_quantization() == "PRODUCT"

java_index = index._java_index
idx_to_check = java_index
if "TypeIndex" in java_index.getClass().getName():
idx_to_check = java_index.getSubIndexes().get(0)

assert str(idx_to_check.getMetadata().quantizationType) == "PRODUCT"
assert index.get_metadata()["quantization"] == "PRODUCT"

@staticmethod
def _engine_default_max_connections() -> int:
"""Read maxConnections off a freshly constructed engine metadata object.
def _engine_default_max_connections(db) -> int:
"""Read maxConnections off an index the engine configured by itself.

The field initializer is the engine default, so the value tracks the
bundled jars rather than a number copied into the Python layer.
create_vector_index always sets maxConnections, so the engine default
shows only on an index SQL creates without it. The value tracks the
engine the wheel carries rather than a number copied into the Python
layer, and it reads the same on both builds.
"""
import jpype

java_string = jpype.JClass("java.lang.String")
property_names = jpype.JArray(java_string)(["embedding"])
metadata = jpype.JPackage("com").arcadedb.schema.LSMVectorIndexMetadata(
"DefaultProbe", property_names, 0
db.command("sql", "CREATE VERTEX TYPE DefaultProbe")
db.command("sql", "CREATE PROPERTY DefaultProbe.embedding ARRAY_OF_FLOATS")
db.command(
"sql",
"CREATE INDEX ON DefaultProbe (embedding) LSM_VECTOR METADATA "
'{"dimensions": 4, "similarity": "EUCLIDEAN"}',
)
return int(metadata.maxConnections)
probe = db.schema.get_vector_index("DefaultProbe", "embedding")
return int(probe.get_metadata()["max_connections"])

def test_wrapper_default_matches_engine_default(self, test_db):
"""The Python default must equal the engine default, not a copy of it.
Expand All @@ -317,11 +239,11 @@ def test_wrapper_default_matches_engine_default(self, test_db):
signature = inspect.signature(type(test_db).create_vector_index)
wrapper_default = signature.parameters["max_connections"].default

assert wrapper_default == self._engine_default_max_connections()
assert wrapper_default == self._engine_default_max_connections(test_db)

def test_omitted_max_connections_reaches_the_index(self, test_db):
"""Omitting the argument must land the engine default on the index."""
engine_default = self._engine_default_max_connections()
engine_default = self._engine_default_max_connections(test_db)

test_db.command("sql", "CREATE VERTEX TYPE DefaultDegreeDoc")
test_db.command(
Expand All @@ -332,8 +254,7 @@ def test_omitted_max_connections_reaches_the_index(self, test_db):
"DefaultDegreeDoc", "embedding", dimensions=4
)

metadata = self._get_primary_metadata(index)
assert int(metadata.maxConnections) == engine_default
assert index.get_metadata()["max_connections"] == engine_default

def test_jvm_heap_check(self):
"""Verify JVM memory settings from Java level."""
Expand Down
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