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sync_client_test.py
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312 lines (287 loc) · 10.5 KB
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import uuid
from datetime import datetime, timedelta
import numpy as np
import pytest
from timescale_vector.client import (
SEARCH_RESULT_CONTENTS_IDX,
SEARCH_RESULT_DISTANCE_IDX,
SEARCH_RESULT_ID_IDX,
SEARCH_RESULT_METADATA_IDX,
DiskAnnIndex,
DiskAnnIndexParams,
HNSWIndex,
IvfflatIndex,
Predicates,
Sync,
UUIDTimeRange,
uuid_from_time,
)
@pytest.mark.parametrize("schema", ["tschema", None])
def test_sync_client(service_url: str, schema: str) -> None:
vec = Sync(service_url, "data_table", 2, schema_name=schema)
vec.create_tables()
empty = vec.table_is_empty()
assert empty
vec.upsert([(uuid.uuid4(), {"key": "val"}, "the brown fox", [1.0, 1.2])])
empty = vec.table_is_empty()
assert not empty
vec.upsert(
[
(uuid.uuid4(), """{"key":"val"}""", "the brown fox", [1.0, 1.3]),
(uuid.uuid4(), """{"key":"val2"}""", "the brown fox", [1.0, 1.4]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.5]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.6]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.6]),
(uuid.uuid4(), """{"key2":"val2"}""", "the brown fox", [1.0, 1.7]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.8]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.9]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 100.8]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 101.8]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.8]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.8]),
(
uuid.uuid4(),
"""{"key_1":"val_1", "key_2":"val_2"}""",
"the brown fox",
[1.0, 1.8],
),
(uuid.uuid4(), """{"key0": [1,2,3,4]}""", "the brown fox", [1.0, 1.8]),
(
uuid.uuid4(),
"""{"key0": [5,6,7], "key3": 3}""",
"the brown fox",
[1.0, 1.8],
),
]
)
vec.create_embedding_index(IvfflatIndex())
vec.drop_embedding_index()
vec.create_embedding_index(IvfflatIndex(100))
vec.drop_embedding_index()
vec.create_embedding_index(HNSWIndex())
vec.drop_embedding_index()
vec.create_embedding_index(HNSWIndex(20, 125))
vec.drop_embedding_index()
vec.create_embedding_index(DiskAnnIndex())
vec.drop_embedding_index()
vec.create_embedding_index(DiskAnnIndex(50, 50, 1.5))
rec = vec.search([1.0, 2.0])
assert len(rec) == 10
rec = vec.search(np.array([1.0, 2.0]))
assert len(rec) == 10
rec = vec.search([1.0, 2.0], limit=4)
assert len(rec) == 4
rec = vec.search(limit=4)
assert len(rec) == 4
rec = vec.search([1.0, 2.0], limit=4, filter={"key2": "val2"})
assert len(rec) == 1
rec = vec.search([1.0, 2.0], limit=4, filter={"key2": "does not exist"})
assert len(rec) == 0
rec = vec.search(limit=4, filter={"key2": "does not exist"})
assert len(rec) == 0
rec = vec.search([1.0, 2.0], limit=4, filter={"key_1": "val_1"})
assert len(rec) == 1
rec = vec.search([1.0, 2.0], filter={"key_1": "val_1", "key_2": "val_2"})
assert len(rec) == 1
rec = vec.search([1.0, 2.0], limit=4, filter={"key_1": "val_1", "key_2": "val_3"})
assert len(rec) == 0
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key_1": "val_1"}, {"key2": "val2"}])
assert len(rec) == 2
rec = vec.search(
[1.0, 2.0],
limit=4,
filter=[
{"key_1": "val_1"},
{"key2": "val2"},
{"no such key": "no such val"},
],
)
assert len(rec) == 2
raised = False
try:
# can't upsert using both keys and dictionaries
vec.upsert(
[
(uuid.uuid4(), {"key": "val"}, "the brown fox", [1.0, 1.2]),
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.2]),
]
)
except ValueError:
raised = True
assert raised
raised = False
try:
# can't upsert using both keys and dictionaries opposite order
vec.upsert(
[
(uuid.uuid4(), """{"key2":"val"}""", "the brown fox", [1.0, 1.2]),
(uuid.uuid4(), {"key": "val"}, "the brown fox", [1.0, 1.2]),
]
)
except BaseException:
raised = True
assert raised
rec = vec.search([1.0, 2.0], filter={"key_1": "val_1", "key_2": "val_2"})
assert rec[0][SEARCH_RESULT_CONTENTS_IDX] == "the brown fox"
assert rec[0]["contents"] == "the brown fox"
assert rec[0][SEARCH_RESULT_METADATA_IDX] == {
"key_1": "val_1",
"key_2": "val_2",
}
assert rec[0]["metadata"] == {"key_1": "val_1", "key_2": "val_2"}
assert isinstance(rec[0][SEARCH_RESULT_METADATA_IDX], dict)
assert rec[0][SEARCH_RESULT_DISTANCE_IDX] == 0.0009438353921149556
assert rec[0]["distance"] == 0.0009438353921149556
rec = vec.search([1.0, 2.0], limit=4, predicates=Predicates("key", "==", "val2"))
assert len(rec) == 1
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key_1": "val_1"}, {"key2": "val2"}])
assert len(rec) == 2
vec.delete_by_ids([rec[0][SEARCH_RESULT_ID_IDX]])
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key_1": "val_1"}, {"key2": "val2"}])
assert len(rec) == 1
vec.delete_by_metadata([{"key_1": "val_1"}, {"key2": "val2"}])
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key_1": "val_1"}, {"key2": "val2"}])
assert len(rec) == 0
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key2": "val"}])
assert len(rec) == 4
vec.delete_by_metadata([{"key2": "val"}])
rec = vec.search([1.0, 2.0], limit=4, filter=[{"key2": "val"}])
assert len(rec) == 0
assert not vec.table_is_empty()
vec.delete_all()
assert vec.table_is_empty()
vec.drop_table()
vec.close()
vec = Sync(service_url, "data_table", 2, id_type="TEXT", schema_name=schema)
vec.create_tables()
assert vec.table_is_empty()
vec.upsert([("Not a valid UUID", {"key": "val"}, "the brown fox", [1.0, 1.2])])
assert not vec.table_is_empty()
vec.delete_by_ids(["Not a valid UUID"])
assert vec.table_is_empty()
vec.drop_table()
vec.close()
vec = Sync(
service_url,
"data_table",
2,
time_partition_interval=timedelta(seconds=60),
schema_name=schema,
)
vec.create_tables()
assert vec.table_is_empty()
id = uuid.uuid1()
vec.upsert([(id, {"key": "val"}, "the brown fox", [1.0, 1.2])])
assert not vec.table_is_empty()
vec.delete_by_ids([id])
assert vec.table_is_empty()
raised = False
try:
# can't upsert with uuid type 4 in time partitioned table
vec.upsert([(uuid.uuid4(), {"key": "val"}, "the brown fox", [1.0, 1.2])])
# pass
except BaseException:
raised = True
assert raised
specific_datetime = datetime(2018, 8, 10, 15, 30, 0)
vec.upsert(
[
# current time
(uuid.uuid1(), {"key": "val"}, "the brown fox", [1.0, 1.2]),
# time in 2018
(
uuid_from_time(specific_datetime),
{"key": "val"},
"the brown fox",
[1.0, 1.2],
),
]
)
def search_date(start_date, end_date, expected):
# using uuid_time_filter
rec = vec.search(
[1.0, 2.0],
limit=4,
uuid_time_filter=UUIDTimeRange(start_date, end_date),
)
assert len(rec) == expected
rec = vec.search(
[1.0, 2.0],
limit=4,
uuid_time_filter=UUIDTimeRange(str(start_date), str(end_date)),
)
assert len(rec) == expected
# using filters
filter = {}
if start_date is not None:
filter["__start_date"] = start_date
if end_date is not None:
filter["__end_date"] = end_date
rec = vec.search([1.0, 2.0], limit=4, filter=filter)
assert len(rec) == expected
# using filters with string dates
filter = {}
if start_date is not None:
filter["__start_date"] = str(start_date)
if end_date is not None:
filter["__end_date"] = str(end_date)
rec = vec.search([1.0, 2.0], limit=4, filter=filter)
assert len(rec) == expected
# using predicates
predicates = []
if start_date is not None:
predicates.append(("__uuid_timestamp", ">=", start_date))
if end_date is not None:
predicates.append(("__uuid_timestamp", "<", end_date))
rec = vec.search([1.0, 2.0], limit=4, predicates=Predicates(*predicates))
assert len(rec) == expected
# using predicates with string dates
predicates = []
if start_date is not None:
predicates.append(("__uuid_timestamp", ">=", str(start_date)))
if end_date is not None:
predicates.append(("__uuid_timestamp", "<", str(end_date)))
rec = vec.search([1.0, 2.0], limit=4, predicates=Predicates(*predicates))
assert len(rec) == expected
assert not vec.table_is_empty()
search_date(
specific_datetime - timedelta(days=7),
specific_datetime + timedelta(days=7),
1,
)
search_date(specific_datetime - timedelta(days=7), None, 2)
search_date(None, specific_datetime + timedelta(days=7), 1)
search_date(
specific_datetime - timedelta(days=7),
specific_datetime - timedelta(days=2),
0,
)
# check timedelta handling
rec = vec.search(
[1.0, 2.0],
limit=4,
uuid_time_filter=UUIDTimeRange(start_date=specific_datetime, time_delta=timedelta(days=7)),
)
assert len(rec) == 1
# end is exclusive
rec = vec.search(
[1.0, 2.0],
limit=4,
uuid_time_filter=UUIDTimeRange(end_date=specific_datetime, time_delta=timedelta(days=7)),
)
assert len(rec) == 0
rec = vec.search(
[1.0, 2.0],
limit=4,
uuid_time_filter=UUIDTimeRange(
end_date=specific_datetime + timedelta(seconds=1),
time_delta=timedelta(days=7),
),
)
assert len(rec) == 1
rec = vec.search([1.0, 2.0], limit=4, query_params=DiskAnnIndexParams(10, 5))
assert len(rec) == 2
rec = vec.search([1.0, 2.0], limit=4, query_params=DiskAnnIndexParams(100, rescore=2))
assert len(rec) == 2
vec.drop_table()
vec.close()