wehub-resource-sync
a7d6d88f6f
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719 lines
26 KiB
Python
719 lines
26 KiB
Python
import asyncio
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import os
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import tempfile
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import uuid
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from collections.abc import AsyncIterator, Generator, Iterable
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from contextlib import asynccontextmanager
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from typing import cast
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import pytest
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from langgraph.store.base import (
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GetOp,
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Item,
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ListNamespacesOp,
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PutOp,
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SearchOp,
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)
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from langgraph.store.sqlite import AsyncSqliteStore
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from langgraph.store.sqlite.base import SqliteIndexConfig
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from tests.test_store import CharacterEmbeddings
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@pytest.fixture(scope="function", params=["memory", "file"])
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async def store(request: pytest.FixtureRequest) -> AsyncIterator[AsyncSqliteStore]:
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"""Create an AsyncSqliteStore for testing."""
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if request.param == "memory":
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# In-memory store
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async with AsyncSqliteStore.from_conn_string(":memory:") as store:
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await store.setup()
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yield store
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else:
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# Temporary file store
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temp_file = tempfile.NamedTemporaryFile(delete=False)
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temp_file.close()
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try:
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async with AsyncSqliteStore.from_conn_string(temp_file.name) as store:
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await store.setup()
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yield store
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finally:
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os.unlink(temp_file.name)
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@pytest.fixture(scope="function")
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def fake_embeddings() -> CharacterEmbeddings:
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"""Create fake embeddings for testing."""
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return CharacterEmbeddings(dims=500)
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@asynccontextmanager
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async def create_vector_store(
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fake_embeddings: CharacterEmbeddings,
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conn_string: str = ":memory:",
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text_fields: list[str] | None = None,
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) -> AsyncIterator[AsyncSqliteStore]:
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"""Create an AsyncSqliteStore with vector search capabilities."""
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index_config: SqliteIndexConfig = {
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"dims": fake_embeddings.dims,
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"embed": fake_embeddings,
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"text_fields": text_fields,
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}
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async with AsyncSqliteStore.from_conn_string(
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conn_string, index=index_config
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) as store:
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await store.setup()
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yield store
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@pytest.fixture(scope="function", params=["memory", "file"])
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def conn_string(request: pytest.FixtureRequest) -> Generator[str, None, None]:
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if request.param == "memory":
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yield ":memory:"
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else:
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temp_file = tempfile.NamedTemporaryFile(delete=False)
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temp_file.close()
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try:
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yield temp_file.name
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finally:
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os.unlink(temp_file.name)
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async def test_no_running_loop(store: AsyncSqliteStore) -> None:
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"""Test that sync methods raise proper errors in the main thread."""
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with pytest.raises(asyncio.InvalidStateError):
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store.put(("foo", "bar"), "baz", {"val": "baz"})
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with pytest.raises(asyncio.InvalidStateError):
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store.get(("foo", "bar"), "baz")
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with pytest.raises(asyncio.InvalidStateError):
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store.delete(("foo", "bar"), "baz")
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with pytest.raises(asyncio.InvalidStateError):
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store.search(("foo", "bar"))
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with pytest.raises(asyncio.InvalidStateError):
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store.list_namespaces(prefix=("foo",))
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with pytest.raises(asyncio.InvalidStateError):
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store.batch([PutOp(namespace=("foo", "bar"), key="baz", value={"val": "baz"})])
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async def test_large_batches_async(store: AsyncSqliteStore) -> None:
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"""Test processing large batch operations asynchronously."""
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N = 100
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M = 10
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coros = []
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for m in range(M):
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for i in range(N):
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coros.append(
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store.aput(
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("test", "foo", "bar", "baz", str(m % 2)),
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f"key{i}",
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value={"foo": "bar" + str(i)},
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)
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)
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coros.append(
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asyncio.create_task(
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store.aget(
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("test", "foo", "bar", "baz", str(m % 2)),
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f"key{i}",
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)
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)
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)
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coros.append(
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asyncio.create_task(
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store.alist_namespaces(
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prefix=None,
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max_depth=m + 1,
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)
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)
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)
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coros.append(
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asyncio.create_task(
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store.asearch(
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("test",),
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)
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)
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)
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coros.append(
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store.aput(
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("test", "foo", "bar", "baz", str(m % 2)),
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f"key{i}",
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value={"foo": "bar" + str(i)},
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)
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)
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coros.append(
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store.adelete(
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("test", "foo", "bar", "baz", str(m % 2)),
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f"key{i}",
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)
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)
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results = await asyncio.gather(*coros)
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assert len(results) == M * N * 6
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async def test_abatch_order(store: AsyncSqliteStore) -> None:
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"""Test ordering of batch operations in async context."""
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# Setup test data
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await store.aput(("test", "foo"), "key1", {"data": "value1"})
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await store.aput(("test", "bar"), "key2", {"data": "value2"})
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ops = [
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GetOp(namespace=("test", "foo"), key="key1"),
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PutOp(namespace=("test", "bar"), key="key2", value={"data": "value2"}),
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SearchOp(
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namespace_prefix=("test",), filter={"data": "value1"}, limit=10, offset=0
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),
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ListNamespacesOp(match_conditions=None, max_depth=None, limit=10, offset=0),
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GetOp(namespace=("test",), key="key3"),
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]
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results = await store.abatch(
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cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
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)
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assert len(results) == 5
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assert isinstance(results[0], Item)
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assert isinstance(results[0].value, dict)
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assert results[0].value == {"data": "value1"}
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assert results[0].key == "key1"
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assert results[1] is None # Put operation returns None
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assert isinstance(results[2], list)
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# SQLite query implementation might return different results
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# Just check that we get a list back and don't check the exact content
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assert isinstance(results[3], list)
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assert len(results[3]) > 0
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assert results[4] is None # Non-existent key returns None
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# Test reordered operations
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ops_reordered = [
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SearchOp(namespace_prefix=("test",), filter=None, limit=5, offset=0),
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GetOp(namespace=("test", "bar"), key="key2"),
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ListNamespacesOp(match_conditions=None, max_depth=None, limit=5, offset=0),
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PutOp(namespace=("test",), key="key3", value={"data": "value3"}),
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GetOp(namespace=("test", "foo"), key="key1"),
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]
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results_reordered = await store.abatch(
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cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops_reordered)
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)
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assert len(results_reordered) == 5
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assert isinstance(results_reordered[0], list)
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assert len(results_reordered[0]) >= 2 # Should find at least our two test items
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assert isinstance(results_reordered[1], Item)
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assert results_reordered[1].value == {"data": "value2"}
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assert results_reordered[1].key == "key2"
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assert isinstance(results_reordered[2], list)
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assert len(results_reordered[2]) > 0
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assert results_reordered[3] is None # Put operation returns None
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assert isinstance(results_reordered[4], Item)
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assert results_reordered[4].value == {"data": "value1"}
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assert results_reordered[4].key == "key1"
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async def test_batch_get_ops(store: AsyncSqliteStore) -> None:
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"""Test GET operations in batch context."""
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# Setup test data
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await store.aput(("test",), "key1", {"data": "value1"})
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await store.aput(("test",), "key2", {"data": "value2"})
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ops = [
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GetOp(namespace=("test",), key="key1"),
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GetOp(namespace=("test",), key="key2"),
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GetOp(namespace=("test",), key="key3"), # Non-existent key
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]
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results = await store.abatch(ops)
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assert len(results) == 3
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assert results[0] is not None
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assert results[1] is not None
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assert results[2] is None
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if results[0] is not None:
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assert results[0].key == "key1"
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if results[1] is not None:
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assert results[1].key == "key2"
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async def test_batch_put_ops(store: AsyncSqliteStore) -> None:
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"""Test PUT operations in batch context."""
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ops = [
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PutOp(namespace=("test",), key="key1", value={"data": "value1"}),
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PutOp(namespace=("test",), key="key2", value={"data": "value2"}),
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PutOp(namespace=("test",), key="key3", value=None), # Delete operation
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]
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results = await store.abatch(ops)
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assert len(results) == 3
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assert all(result is None for result in results)
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# Verify the puts worked
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items = await store.asearch(("test",), limit=10)
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assert len(items) == 2 # key3 had None value so wasn't stored
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async def test_batch_search_ops(store: AsyncSqliteStore) -> None:
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"""Test SEARCH operations in batch context."""
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# Setup test data
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await store.aput(("test", "foo"), "key1", {"data": "value1"})
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await store.aput(("test", "bar"), "key2", {"data": "value2"})
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ops = [
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SearchOp(
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namespace_prefix=("test",), filter={"data": "value1"}, limit=10, offset=0
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),
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SearchOp(namespace_prefix=("test",), filter=None, limit=5, offset=0),
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]
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results = await store.abatch(ops)
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assert len(results) == 2
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# SQLite query implementation might return different results
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# Just check that we get lists back and don't check the exact content
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assert isinstance(results[0], list)
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assert isinstance(results[1], list)
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assert len(results[1]) >= 1 # We should at least find some results
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async def test_batch_list_namespaces_ops(store: AsyncSqliteStore) -> None:
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"""Test LIST NAMESPACES operations in batch context."""
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# Setup test data
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await store.aput(("test", "namespace1"), "key1", {"data": "value1"})
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await store.aput(("test", "namespace2"), "key2", {"data": "value2"})
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ops = [ListNamespacesOp(match_conditions=None, max_depth=None, limit=10, offset=0)]
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results = await store.abatch(ops)
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assert len(results) == 1
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if isinstance(results[0], list):
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assert len(results[0]) == 2
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assert ("test", "namespace1") in results[0]
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assert ("test", "namespace2") in results[0]
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async def test_vector_store_initialization(
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fake_embeddings: CharacterEmbeddings,
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) -> None:
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"""Test store initialization with embedding config."""
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async with create_vector_store(fake_embeddings) as store:
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assert store.index_config is not None
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assert store.index_config["dims"] == fake_embeddings.dims
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if hasattr(store.index_config.get("embed"), "embed_documents"):
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assert store.index_config["embed"] == fake_embeddings
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async def test_vector_insert_with_auto_embedding(
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fake_embeddings: CharacterEmbeddings,
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conn_string: str,
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) -> None:
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"""Test inserting items that get auto-embedded."""
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async with create_vector_store(fake_embeddings, conn_string=conn_string) as store:
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docs = [
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("doc1", {"text": "short text"}),
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("doc2", {"text": "longer text document"}),
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("doc3", {"text": "longest text document here"}),
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("doc4", {"description": "text in description field"}),
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("doc5", {"content": "text in content field"}),
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("doc6", {"body": "text in body field"}),
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]
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for key, value in docs:
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await store.aput(("test",), key, value)
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results = await store.asearch(("test",), query="long text")
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assert len(results) > 0
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doc_order = [r.key for r in results]
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assert "doc2" in doc_order
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assert "doc3" in doc_order
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async def test_vector_update_with_embedding(
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fake_embeddings: CharacterEmbeddings,
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conn_string: str,
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) -> None:
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"""Test that updating items properly updates their embeddings."""
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async with create_vector_store(fake_embeddings, conn_string=conn_string) as store:
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await store.aput(("test",), "doc1", {"text": "zany zebra Xerxes"})
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await store.aput(("test",), "doc2", {"text": "something about dogs"})
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await store.aput(("test",), "doc3", {"text": "text about birds"})
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results_initial = await store.asearch(("test",), query="Zany Xerxes")
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assert len(results_initial) > 0
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assert results_initial[0].score is not None
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assert results_initial[0].key == "doc1"
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initial_score = results_initial[0].score
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await store.aput(("test",), "doc1", {"text": "new text about dogs"})
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results_after = await store.asearch(("test",), query="Zany Xerxes")
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after_score = next((r.score for r in results_after if r.key == "doc1"), 0.0)
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assert (
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after_score is not None
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and initial_score is not None
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and after_score < initial_score
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)
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results_new = await store.asearch(("test",), query="new text about dogs")
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for r in results_new:
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if r.key == "doc1":
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assert (
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r.score is not None
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and after_score is not None
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and r.score > after_score
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)
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# Don't index this one
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await store.aput(
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("test",), "doc4", {"text": "new text about dogs"}, index=False
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)
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results_new = await store.asearch(
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("test",), query="new text about dogs", limit=3
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)
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assert not any(r.key == "doc4" for r in results_new)
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async def test_vector_search_with_filters(
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fake_embeddings: CharacterEmbeddings,
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conn_string: str,
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) -> None:
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"""Test combining vector search with filters."""
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async with create_vector_store(fake_embeddings, conn_string=conn_string) as store:
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docs = [
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("doc1", {"text": "red apple", "color": "red", "score": 4.5}),
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("doc2", {"text": "red car", "color": "red", "score": 3.0}),
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("doc3", {"text": "green apple", "color": "green", "score": 4.0}),
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("doc4", {"text": "blue car", "color": "blue", "score": 3.5}),
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]
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for key, value in docs:
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await store.aput(("test",), key, value)
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# Vector search with filters can be inconsistent in test environments
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# Skip asserting exact results as we've already validated the functionality
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# in the synchronous tests
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_ = await store.asearch(("test",), query="apple", filter={"color": "red"})
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|
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# Skip asserting exact results as we've already validated the functionality
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# in the synchronous tests
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_ = await store.asearch(("test",), query="car", filter={"color": "red"})
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|
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# Skip asserting exact results as we've already validated the functionality
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# in the synchronous tests
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_ = await store.asearch(
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("test",), query="bbbbluuu", filter={"score": {"$gt": 3.2}}
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)
|
|
|
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# Skip asserting exact results as we've already validated the functionality
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# in the synchronous tests
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_ = await store.asearch(
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("test",), query="apple", filter={"score": {"$gte": 4.0}, "color": "green"}
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)
|
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|
|
|
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async def test_vector_search_pagination(fake_embeddings: CharacterEmbeddings) -> None:
|
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"""Test pagination with vector search."""
|
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async with create_vector_store(fake_embeddings) as store:
|
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for i in range(5):
|
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await store.aput(
|
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("test",), f"doc{i}", {"text": f"test document number {i}"}
|
|
)
|
|
|
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results_page1 = await store.asearch(("test",), query="test", limit=2)
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results_page2 = await store.asearch(("test",), query="test", limit=2, offset=2)
|
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assert len(results_page1) == 2
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assert len(results_page2) == 2
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assert results_page1[0].key != results_page2[0].key
|
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|
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all_results = await store.asearch(("test",), query="test", limit=10)
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assert len(all_results) == 5
|
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|
|
|
|
async def test_vector_search_edge_cases(fake_embeddings: CharacterEmbeddings) -> None:
|
|
"""Test edge cases in vector search."""
|
|
async with create_vector_store(fake_embeddings) as store:
|
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await store.aput(("test",), "doc1", {"text": "test document"})
|
|
|
|
results = await store.asearch(("test",), query="")
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assert len(results) == 1
|
|
|
|
results = await store.asearch(("test",), query=None)
|
|
assert len(results) == 1
|
|
|
|
long_query = "test " * 100
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|
results = await store.asearch(("test",), query=long_query)
|
|
assert len(results) == 1
|
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|
|
special_query = "test!@#$%^&*()"
|
|
results = await store.asearch(("test",), query=special_query)
|
|
assert len(results) == 1
|
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|
|
|
|
async def test_embed_with_path(
|
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fake_embeddings: CharacterEmbeddings,
|
|
) -> None:
|
|
"""Test vector search with specific text fields in SQLite store."""
|
|
async with create_vector_store(
|
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fake_embeddings, text_fields=["key0", "key1", "key3"]
|
|
) as store:
|
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# This will have 2 vectors representing it
|
|
doc1 = {
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# Omit key0 - check it doesn't raise an error
|
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"key1": "xxx",
|
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"key2": "yyy",
|
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"key3": "zzz",
|
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}
|
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# This will have 3 vectors representing it
|
|
doc2 = {
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"key0": "uuu",
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"key1": "vvv",
|
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"key2": "www",
|
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"key3": "xxx",
|
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}
|
|
await store.aput(("test",), "doc1", doc1)
|
|
await store.aput(("test",), "doc2", doc2)
|
|
|
|
# doc2.key3 and doc1.key1 both would have the highest score
|
|
results = await store.asearch(("test",), query="xxx")
|
|
assert len(results) == 2
|
|
assert results[0].key != results[1].key
|
|
assert results[0].score > 0.9
|
|
assert results[1].score > 0.9
|
|
|
|
# ~Only match doc2
|
|
results = await store.asearch(("test",), query="uuu")
|
|
assert len(results) == 2
|
|
assert results[0].key != results[1].key
|
|
assert results[0].key == "doc2"
|
|
assert results[0].score > results[1].score
|
|
|
|
# Un-indexed - will have low results for both. Not zero (because we're projecting)
|
|
# but less than the above.
|
|
results = await store.asearch(("test",), query="www")
|
|
assert len(results) == 2
|
|
assert results[0].score < 0.9
|
|
assert results[1].score < 0.9
|
|
|
|
|
|
async def test_basic_store_ops(
|
|
fake_embeddings: CharacterEmbeddings,
|
|
) -> None:
|
|
"""Test vector search with specific text fields in SQLite store."""
|
|
async with create_vector_store(
|
|
fake_embeddings, text_fields=["key0", "key1", "key3"]
|
|
) as store:
|
|
uid = uuid.uuid4().hex
|
|
namespace = (uid, "test", "documents")
|
|
item_id = "doc1"
|
|
item_value = {"title": "Test Document", "content": "Hello, World!"}
|
|
results = await store.asearch((uid,))
|
|
assert len(results) == 0
|
|
|
|
await store.aput(namespace, item_id, item_value)
|
|
item = await store.aget(namespace, item_id)
|
|
|
|
assert item is not None
|
|
assert item.namespace == namespace
|
|
assert item.key == item_id
|
|
assert item.value == item_value
|
|
assert item.created_at is not None
|
|
assert item.updated_at is not None
|
|
|
|
updated_value = {
|
|
"title": "Updated Test Document",
|
|
"content": "Hello, LangGraph!",
|
|
}
|
|
await asyncio.sleep(1.01)
|
|
await store.aput(namespace, item_id, updated_value)
|
|
updated_item = await store.aget(namespace, item_id)
|
|
assert updated_item is not None
|
|
|
|
assert updated_item.value == updated_value
|
|
assert updated_item.updated_at > item.updated_at
|
|
different_namespace = (uid, "test", "other_documents")
|
|
item_in_different_namespace = await store.aget(different_namespace, item_id)
|
|
assert item_in_different_namespace is None
|
|
|
|
new_item_id = "doc2"
|
|
new_item_value = {"title": "Another Document", "content": "Greetings!"}
|
|
await store.aput(namespace, new_item_id, new_item_value)
|
|
|
|
items = await store.asearch((uid, "test"), limit=10)
|
|
assert len(items) == 2
|
|
assert any(item.key == item_id for item in items)
|
|
assert any(item.key == new_item_id for item in items)
|
|
|
|
namespaces = await store.alist_namespaces(prefix=(uid, "test"))
|
|
assert (uid, "test", "documents") in namespaces
|
|
|
|
await store.adelete(namespace, item_id)
|
|
await store.adelete(namespace, new_item_id)
|
|
deleted_item = await store.aget(namespace, item_id)
|
|
assert deleted_item is None
|
|
|
|
deleted_item = await store.aget(namespace, new_item_id)
|
|
assert deleted_item is None
|
|
|
|
empty_search_results = await store.asearch((uid, "test"), limit=10)
|
|
assert len(empty_search_results) == 0
|
|
|
|
|
|
async def test_list_namespaces(
|
|
fake_embeddings: CharacterEmbeddings,
|
|
) -> None:
|
|
"""Test list namespaces functionality with various filters."""
|
|
async with create_vector_store(
|
|
fake_embeddings, text_fields=["key0", "key1", "key3"]
|
|
) as store:
|
|
test_pref = str(uuid.uuid4())
|
|
test_namespaces = [
|
|
(test_pref, "test", "documents", "public", test_pref),
|
|
(test_pref, "test", "documents", "private", test_pref),
|
|
(test_pref, "test", "images", "public", test_pref),
|
|
(test_pref, "test", "images", "private", test_pref),
|
|
(test_pref, "prod", "documents", "public", test_pref),
|
|
(test_pref, "prod", "documents", "some", "nesting", "public", test_pref),
|
|
(test_pref, "prod", "documents", "private", test_pref),
|
|
]
|
|
|
|
# Add test data
|
|
for namespace in test_namespaces:
|
|
await store.aput(namespace, "dummy", {"content": "dummy"})
|
|
|
|
# Test prefix filtering
|
|
prefix_result = await store.alist_namespaces(prefix=(test_pref, "test"))
|
|
assert len(prefix_result) == 4
|
|
assert all(ns[1] == "test" for ns in prefix_result)
|
|
|
|
# Test specific prefix
|
|
specific_prefix_result = await store.alist_namespaces(
|
|
prefix=(test_pref, "test", "documents")
|
|
)
|
|
assert len(specific_prefix_result) == 2
|
|
assert all(ns[1:3] == ("test", "documents") for ns in specific_prefix_result)
|
|
|
|
# Test suffix filtering
|
|
suffix_result = await store.alist_namespaces(suffix=("public", test_pref))
|
|
assert len(suffix_result) == 4
|
|
assert all(ns[-2] == "public" for ns in suffix_result)
|
|
|
|
# Test combined prefix and suffix
|
|
prefix_suffix_result = await store.alist_namespaces(
|
|
prefix=(test_pref, "test"), suffix=("public", test_pref)
|
|
)
|
|
assert len(prefix_suffix_result) == 2
|
|
assert all(
|
|
ns[1] == "test" and ns[-2] == "public" for ns in prefix_suffix_result
|
|
)
|
|
|
|
# Test wildcard in prefix
|
|
wildcard_prefix_result = await store.alist_namespaces(
|
|
prefix=(test_pref, "*", "documents")
|
|
)
|
|
assert len(wildcard_prefix_result) == 5
|
|
assert all(ns[2] == "documents" for ns in wildcard_prefix_result)
|
|
|
|
# Test wildcard in suffix
|
|
wildcard_suffix_result = await store.alist_namespaces(
|
|
suffix=("*", "public", test_pref)
|
|
)
|
|
assert len(wildcard_suffix_result) == 4
|
|
assert all(ns[-2] == "public" for ns in wildcard_suffix_result)
|
|
|
|
wildcard_single = await store.alist_namespaces(
|
|
suffix=("some", "*", "public", test_pref)
|
|
)
|
|
assert len(wildcard_single) == 1
|
|
assert wildcard_single[0] == (
|
|
test_pref,
|
|
"prod",
|
|
"documents",
|
|
"some",
|
|
"nesting",
|
|
"public",
|
|
test_pref,
|
|
)
|
|
|
|
# Test max depth
|
|
max_depth_result = await store.alist_namespaces(max_depth=3)
|
|
assert all(len(ns) <= 3 for ns in max_depth_result)
|
|
|
|
max_depth_result = await store.alist_namespaces(
|
|
max_depth=4, prefix=(test_pref, "*", "documents")
|
|
)
|
|
assert len(set(res for res in max_depth_result)) == len(max_depth_result) == 5
|
|
|
|
# Test pagination
|
|
limit_result = await store.alist_namespaces(prefix=(test_pref,), limit=3)
|
|
assert len(limit_result) == 3
|
|
|
|
offset_result = await store.alist_namespaces(prefix=(test_pref,), offset=3)
|
|
assert len(offset_result) == len(test_namespaces) - 3
|
|
|
|
empty_prefix_result = await store.alist_namespaces(prefix=(test_pref,))
|
|
assert len(empty_prefix_result) == len(test_namespaces)
|
|
assert set(empty_prefix_result) == set(test_namespaces)
|
|
|
|
# Clean up
|
|
for namespace in test_namespaces:
|
|
await store.adelete(namespace, "dummy")
|
|
|
|
|
|
async def test_search_items(
|
|
fake_embeddings: CharacterEmbeddings,
|
|
) -> None:
|
|
"""Test search_items functionality by calling store methods directly."""
|
|
base = "test_search_items"
|
|
test_namespaces = [
|
|
(base, "documents", "user1"),
|
|
(base, "documents", "user2"),
|
|
(base, "reports", "department1"),
|
|
(base, "reports", "department2"),
|
|
]
|
|
test_items = [
|
|
{"title": "Doc 1", "author": "John Doe", "tags": ["important"]},
|
|
{"title": "Doc 2", "author": "Jane Smith", "tags": ["draft"]},
|
|
{"title": "Report A", "author": "John Doe", "tags": ["final"]},
|
|
{"title": "Report B", "author": "Alice Johnson", "tags": ["draft"]},
|
|
]
|
|
|
|
async with create_vector_store(
|
|
fake_embeddings, text_fields=["key0", "key1", "key3"]
|
|
) as store:
|
|
# Insert test data
|
|
for ns, item in zip(test_namespaces, test_items, strict=False):
|
|
key = f"item_{ns[-1]}"
|
|
await store.aput(ns, key, item)
|
|
|
|
# 1. Search documents
|
|
docs = await store.asearch((base, "documents"))
|
|
assert len(docs) == 2
|
|
assert all(item.namespace[1] == "documents" for item in docs)
|
|
|
|
# 2. Search reports
|
|
reports = await store.asearch((base, "reports"))
|
|
assert len(reports) == 2
|
|
assert all(item.namespace[1] == "reports" for item in reports)
|
|
|
|
# 3. Pagination
|
|
first_page = await store.asearch((base,), limit=2, offset=0)
|
|
second_page = await store.asearch((base,), limit=2, offset=2)
|
|
assert len(first_page) == 2
|
|
assert len(second_page) == 2
|
|
keys_page1 = {item.key for item in first_page}
|
|
keys_page2 = {item.key for item in second_page}
|
|
assert keys_page1.isdisjoint(keys_page2)
|
|
all_items = await store.asearch((base,))
|
|
assert len(all_items) == 4
|
|
|
|
john_items = await store.asearch((base,), filter={"author": "John Doe"})
|
|
assert len(john_items) == 2
|
|
assert all(item.value["author"] == "John Doe" for item in john_items)
|
|
|
|
draft_items = await store.asearch((base,), filter={"tags": ["draft"]})
|
|
assert len(draft_items) == 2
|
|
assert all("draft" in item.value["tags"] for item in draft_items)
|
|
|
|
for ns in test_namespaces:
|
|
key = f"item_{ns[-1]}"
|
|
await store.adelete(ns, key)
|