chore: import upstream snapshot with attribution

python/tests/test_schema.py

@@ -0,0 +1,246 @@
+# Copyright 2025-present the zvec project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import pytest
+from zvec import (
+    CollectionSchema,
+    CollectionStats,
+    FieldSchema,
+    VectorSchema,
+    HnswIndexParam,
+    InvertIndexParam,
+    DataType,
+    IndexType,
+    MetricType,
+)
+
+# ----------------------------
+# FieldSchema Test Case
+# ----------------------------
+
+
+class TestFieldSchema:
+    def test_default(self):
+        field = FieldSchema("field", data_type=DataType.FLOAT)
+        assert field.name == "field"
+        assert field.data_type == DataType.FLOAT
+        assert field.nullable is False
+        assert field.index_param is None
+
+    def test_custom(self):
+        field_1 = FieldSchema(
+            name="float",
+            data_type=DataType.FLOAT,
+            nullable=True,
+            index_param=InvertIndexParam(),
+        )
+        assert field_1.name == "float"
+        assert field_1.data_type == DataType.FLOAT
+        assert field_1.nullable is True
+        assert field_1.index_param.enable_range_optimization is False
+
+        field_2 = FieldSchema(
+            name="str",
+            data_type=DataType.STRING,
+            nullable=True,
+            index_param=InvertIndexParam(enable_range_optimization=True),
+        )
+        assert field_2.name == "str"
+        assert field_2.data_type == DataType.STRING
+        assert field_2.nullable is True
+        assert field_2.index_param.enable_range_optimization is True
+
+    def test_readonly(self):
+        field = FieldSchema(
+            name="float",
+            data_type=DataType.FLOAT,
+            nullable=True,
+            index_param=InvertIndexParam(),
+        )
+
+        import sys
+
+        if sys.version_info >= (3, 11):
+            match_pattern = r"(can't set attribute|has no setter|readonly attribute)"
+        else:
+            match_pattern = r"can't set attribute"
+        with pytest.raises(AttributeError, match=match_pattern):
+            field.index_param = InvertIndexParam(enable_range_optimization=True)
+
+
+# ----------------------------
+# VectorSchema Test Case
+# ----------------------------
+class TestVectorSchema:
+    def test_default(self):
+        field = VectorSchema("vector", data_type=DataType.VECTOR_FP32, dimension=128)
+        assert field.name == "vector"
+        assert field.data_type == DataType.VECTOR_FP32
+        assert field.dimension == 128
+        assert field.index_param is not None
+        assert field.index_param.type == IndexType.FLAT
+        assert field.index_param.metric_type == MetricType.IP
+
+    def test_custom(self):
+        field = VectorSchema(
+            name="vector",
+            data_type=DataType.VECTOR_INT8,
+            dimension=512,
+            index_param=HnswIndexParam(
+                metric_type=MetricType.COSINE, m=15, ef_construction=300
+            ),
+        )
+        assert field.name == "vector"
+        assert field.data_type == DataType.VECTOR_INT8
+        assert field.index_param.metric_type == MetricType.COSINE
+        assert field.index_param.m == 15
+        assert field.index_param.ef_construction == 300
+
+    def test_readonly(self):
+        field = VectorSchema(
+            name="vector",
+            dimension=128,
+            data_type=DataType.VECTOR_INT8,
+        )
+
+        import sys
+
+        if sys.version_info >= (3, 11):
+            match_pattern = r"(can't set attribute|has no setter|readonly attribute)"
+        else:
+            match_pattern = r"can't set attribute"
+        with pytest.raises(AttributeError, match=match_pattern):
+            field.dimension = 4
+
+
+# ----------------------------
+# CollectionSchema Test Case
+# ----------------------------
+class TestCollectionSchema:
+    def test_collection_schema_with_single_field(self):
+        collection_schema = CollectionSchema(
+            name="test_collection",
+            fields=FieldSchema(
+                name="id",
+                data_type=DataType.INT64,
+                index_param=InvertIndexParam(),
+                nullable=False,
+            ),
+            vectors=VectorSchema(
+                name="vector",
+                data_type=DataType.VECTOR_INT8,
+                dimension=128,
+                index_param=HnswIndexParam(),
+            ),
+        )
+
+        assert collection_schema is not None
+        assert collection_schema.name == "test_collection"
+        assert len(collection_schema.fields) == 1
+        assert len(collection_schema.vectors) == 1
+
+        field = collection_schema.field("id")
+        assert field is not None
+        assert field.name == "id"
+        assert field.data_type == DataType.INT64
+        assert not field.nullable
+        assert field.index_param.type == IndexType.INVERT
+        assert not field.index_param.enable_range_optimization
+
+        vector = collection_schema.vector("vector")
+        assert vector is not None
+        assert vector.name == "vector"
+        assert vector.data_type == DataType.VECTOR_INT8
+        assert vector.dimension == 128
+        assert vector.index_param.type == IndexType.HNSW
+        assert vector.index_param.m == 50
+        assert vector.index_param.ef_construction == 500
+        assert vector.index_param.metric_type == MetricType.IP
+
+    def test_collection_schema_with_multi_fields(self):
+        collection_schema = CollectionSchema(
+            name="test_collection",
+            fields=[
+                FieldSchema(
+                    "id",
+                    DataType.INT64,
+                    nullable=False,
+                    index_param=InvertIndexParam(enable_range_optimization=True),
+                ),
+                FieldSchema(
+                    "name",
+                    DataType.STRING,
+                    nullable=False,
+                    index_param=InvertIndexParam(),
+                ),
+                FieldSchema(
+                    "weight",
+                    DataType.INT32,
+                    nullable=True,
+                ),
+            ],
+            vectors=[
+                VectorSchema(
+                    "dense",
+                    DataType.VECTOR_FP32,
+                    dimension=128,
+                    index_param=HnswIndexParam(),
+                ),
+                VectorSchema(
+                    "sparse", DataType.SPARSE_VECTOR_FP32, index_param=HnswIndexParam()
+                ),
+            ],
+        )
+        assert collection_schema is not None
+        assert collection_schema.name == "test_collection"
+        assert len(collection_schema.fields) == 3
+        assert len(collection_schema.vectors) == 2
+
+        field_id = collection_schema.field("id")
+        assert field_id is not None
+        assert field_id.name == "id"
+        assert field_id.data_type == DataType.INT64
+        assert not field_id.nullable
+        assert field_id.index_param.type == IndexType.INVERT
+
+        dense = collection_schema.vector("dense")
+        assert dense is not None
+        assert dense.name == "dense"
+        assert dense.data_type == DataType.VECTOR_FP32
+        assert dense.dimension == 128
+        assert dense.index_param.type == IndexType.HNSW
+
+        sparse = collection_schema.vector("sparse")
+        assert sparse is not None
+        assert sparse.name == "sparse"
+        assert sparse.data_type == DataType.SPARSE_VECTOR_FP32
+        assert sparse.dimension == 0
+        assert sparse.index_param.type == IndexType.HNSW
+
+        assert str(collection_schema) is not None
+
+
+# ----------------------------
+# CollectionStats Test Case
+# ----------------------------
+class TestCollectionStats:
+    """
+    The constructor of CollectionStats is not provided.
+    It can only be obtained through collection.stats()
+    """
+
+    def test_collection_stats(self):
+        stats = CollectionStats()
+        assert stats is not None