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feat(semantic layers): cache
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396
tests/unit_tests/semantic_layers/cache_test.py
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396
tests/unit_tests/semantic_layers/cache_test.py
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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import pandas as pd
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import pyarrow as pa
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import pytest
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from superset_core.semantic_layers.types import (
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Dimension,
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Filter,
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Metric,
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Operator,
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OrderDirection,
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PredicateType,
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SemanticQuery,
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SemanticRequest,
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SemanticResult,
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)
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from superset.semantic_layers.cache import (
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_apply_post_processing,
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_implies,
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CachedEntry,
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can_satisfy,
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shape_key,
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value_key,
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ViewMeta,
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)
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# ---------------------------------------------------------------------------
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# Fixtures
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# ---------------------------------------------------------------------------
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def dim(id_: str, name: str | None = None) -> Dimension:
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return Dimension(id=id_, name=name or id_, type=pa.utf8())
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def met(id_: str, name: str | None = None) -> Metric:
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return Metric(id=id_, name=name or id_, type=pa.float64(), definition="x")
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COL_A = dim("col.a", "a")
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COL_B = dim("col.b", "b")
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M_X = met("met.x", "x")
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M_Y = met("met.y", "y")
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VIEW = ViewMeta(uuid="view-1", changed_on_iso="2026-05-01T00:00:00", cache_timeout=None)
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def where(column: Dimension | Metric | None, op: Operator, value: Any) -> Filter:
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return Filter(type=PredicateType.WHERE, column=column, operator=op, value=value)
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def having(column: Metric, op: Operator, value: Any) -> Filter:
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return Filter(type=PredicateType.HAVING, column=column, operator=op, value=value)
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def adhoc(definition: str, type_: PredicateType = PredicateType.WHERE) -> Filter:
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return Filter(type=type_, column=None, operator=Operator.ADHOC, value=definition)
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def query(
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filters: set[Filter] | None = None,
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limit: int | None = None,
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order: Any = None,
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dimensions: list[Dimension] | None = None,
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metrics: list[Metric] | None = None,
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) -> SemanticQuery:
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return SemanticQuery(
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metrics=metrics if metrics is not None else [M_X],
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dimensions=dimensions if dimensions is not None else [COL_A, COL_B],
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filters=filters,
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order=order,
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limit=limit,
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)
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def entry_from(q: SemanticQuery, value_key_: str = "vk") -> CachedEntry:
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from superset.semantic_layers.cache import _group_limit_key, _order_key
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return CachedEntry(
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filters=frozenset(q.filters or set()),
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limit=q.limit,
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offset=q.offset or 0,
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order_key=_order_key(q.order),
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group_limit_key=_group_limit_key(q.group_limit),
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value_key=value_key_,
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)
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# ---------------------------------------------------------------------------
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# _implies: scalar range pairs
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize(
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"new_op,new_val,cached_op,cached_val,expected",
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[
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# narrower lower bound
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(Operator.GREATER_THAN, 20, Operator.GREATER_THAN, 10, True),
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(Operator.GREATER_THAN, 10, Operator.GREATER_THAN, 20, False),
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(Operator.GREATER_THAN_OR_EQUAL, 11, Operator.GREATER_THAN, 10, True),
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(Operator.GREATER_THAN_OR_EQUAL, 10, Operator.GREATER_THAN, 10, False),
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(Operator.GREATER_THAN, 10, Operator.GREATER_THAN_OR_EQUAL, 10, True),
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(Operator.GREATER_THAN, 9, Operator.GREATER_THAN_OR_EQUAL, 10, False),
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# narrower upper bound
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(Operator.LESS_THAN, 5, Operator.LESS_THAN, 10, True),
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(Operator.LESS_THAN_OR_EQUAL, 9, Operator.LESS_THAN, 10, True),
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(Operator.LESS_THAN_OR_EQUAL, 10, Operator.LESS_THAN, 10, False),
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# cross-direction — never implies
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(Operator.LESS_THAN, 5, Operator.GREATER_THAN, 10, False),
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(Operator.GREATER_THAN, 5, Operator.LESS_THAN, 10, False),
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# equals fits in range
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(Operator.EQUALS, 15, Operator.GREATER_THAN, 10, True),
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(Operator.EQUALS, 10, Operator.GREATER_THAN, 10, False),
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(Operator.EQUALS, 10, Operator.GREATER_THAN_OR_EQUAL, 10, True),
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],
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)
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def test_implies_range(
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new_op: Operator,
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new_val: Any,
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cached_op: Operator,
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cached_val: Any,
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expected: bool,
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) -> None:
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assert (
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_implies(where(COL_A, new_op, new_val), where(COL_A, cached_op, cached_val))
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is expected
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)
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def test_implies_in_subset() -> None:
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cached = where(COL_A, Operator.IN, frozenset({"a", "b", "c"}))
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assert _implies(where(COL_A, Operator.IN, frozenset({"a", "b"})), cached) is True
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assert _implies(where(COL_A, Operator.IN, frozenset({"a", "d"})), cached) is False
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# equals to a value in the cached IN set
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assert _implies(where(COL_A, Operator.EQUALS, "b"), cached) is True
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assert _implies(where(COL_A, Operator.EQUALS, "z"), cached) is False
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def test_implies_in_all_in_range() -> None:
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cached = where(COL_A, Operator.GREATER_THAN, 10)
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assert _implies(where(COL_A, Operator.IN, frozenset({11, 12})), cached) is True
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assert _implies(where(COL_A, Operator.IN, frozenset({10, 12})), cached) is False
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def test_implies_equals_exact() -> None:
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cached = where(COL_A, Operator.EQUALS, 5)
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assert _implies(where(COL_A, Operator.EQUALS, 5), cached) is True
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assert _implies(where(COL_A, Operator.EQUALS, 6), cached) is False
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def test_implies_is_not_null() -> None:
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cached = where(COL_A, Operator.IS_NOT_NULL, None)
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assert _implies(where(COL_A, Operator.GREATER_THAN, 0), cached) is True
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assert _implies(where(COL_A, Operator.IS_NOT_NULL, None), cached) is True
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assert _implies(where(COL_A, Operator.IS_NULL, None), cached) is False
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def test_implies_like_exact_match_only() -> None:
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a = where(COL_A, Operator.LIKE, "foo%")
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b = where(COL_A, Operator.LIKE, "foo%")
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c = where(COL_A, Operator.LIKE, "bar%")
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assert _implies(a, b) is True
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assert _implies(c, b) is False
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assert _implies(where(COL_A, Operator.EQUALS, "fooz"), b) is False
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# ---------------------------------------------------------------------------
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# can_satisfy
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# ---------------------------------------------------------------------------
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def test_can_satisfy_empty_cached_returns_all_as_leftovers() -> None:
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cached_q = query(filters=None)
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new_q = query(filters={where(COL_A, Operator.GREATER_THAN, 5)})
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ok, leftovers = can_satisfy(entry_from(cached_q), new_q)
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assert ok is True
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assert leftovers == {where(COL_A, Operator.GREATER_THAN, 5)}
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def test_can_satisfy_narrower_filter() -> None:
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cached_q = query(filters={where(COL_A, Operator.GREATER_THAN, 1)})
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new_q = query(filters={where(COL_A, Operator.GREATER_THAN, 2)})
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ok, leftovers = can_satisfy(entry_from(cached_q), new_q)
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assert ok is True
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assert leftovers == {where(COL_A, Operator.GREATER_THAN, 2)}
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def test_can_satisfy_broader_filter_fails() -> None:
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cached_q = query(filters={where(COL_A, Operator.GREATER_THAN, 2)})
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new_q = query(filters={where(COL_A, Operator.GREATER_THAN, 1)})
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ok, leftovers = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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assert leftovers == set()
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def test_can_satisfy_missing_constraint_fails() -> None:
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cached_q = query(filters={where(COL_A, Operator.GREATER_THAN, 1)})
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new_q = query(filters=None)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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def test_can_satisfy_new_filter_on_extra_column() -> None:
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cached_q = query(filters={where(COL_A, Operator.GREATER_THAN, 1)})
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new_q = query(
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filters={
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where(COL_A, Operator.GREATER_THAN, 2),
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where(COL_B, Operator.EQUALS, "x"),
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}
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)
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ok, leftovers = can_satisfy(entry_from(cached_q), new_q)
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assert ok is True
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assert leftovers == {
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where(COL_A, Operator.GREATER_THAN, 2),
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where(COL_B, Operator.EQUALS, "x"),
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}
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def test_can_satisfy_leftover_on_non_projected_column_fails() -> None:
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other = dim("col.other", "other")
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cached_q = query(filters=None)
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new_q = query(
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filters={where(other, Operator.EQUALS, "x")},
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dimensions=[COL_A, COL_B],
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)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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def test_can_satisfy_having_requires_exact_set() -> None:
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cached_q = query(filters={having(M_X, Operator.GREATER_THAN, 100)})
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same = query(filters={having(M_X, Operator.GREATER_THAN, 100)})
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tighter = query(filters={having(M_X, Operator.GREATER_THAN, 200)})
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ok_same, _ = can_satisfy(entry_from(cached_q), same)
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ok_tight, _ = can_satisfy(entry_from(cached_q), tighter)
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assert ok_same is True
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assert ok_tight is False
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def test_can_satisfy_adhoc_requires_exact_set() -> None:
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cached_q = query(filters={adhoc("col_a > 1")})
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same = query(filters={adhoc("col_a > 1")})
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different = query(filters={adhoc("col_a > 2")})
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ok_same, _ = can_satisfy(entry_from(cached_q), same)
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ok_diff, _ = can_satisfy(entry_from(cached_q), different)
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assert ok_same is True
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assert ok_diff is False
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# ---------------------------------------------------------------------------
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# Limit / order / offset
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# ---------------------------------------------------------------------------
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def test_can_satisfy_unlimited_cached_satisfies_any_limit() -> None:
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cached_q = query(filters=None, limit=None)
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new_q = query(filters=None, limit=10)
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ok, leftovers = can_satisfy(entry_from(cached_q), new_q)
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assert ok is True
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assert leftovers == set()
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def test_can_satisfy_smaller_limit_with_matching_order() -> None:
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order = [(M_X, OrderDirection.DESC)]
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cached_q = query(filters=None, limit=100, order=order)
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new_q = query(filters=None, limit=10, order=order)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is True
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def test_can_satisfy_smaller_limit_different_order_fails() -> None:
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cached_q = query(filters=None, limit=100, order=[(M_X, OrderDirection.DESC)])
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new_q = query(filters=None, limit=10, order=[(M_X, OrderDirection.ASC)])
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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def test_can_satisfy_larger_limit_fails() -> None:
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cached_q = query(filters=None, limit=10)
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new_q = query(filters=None, limit=100)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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def test_can_satisfy_no_new_limit_when_cached_has_one_fails() -> None:
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cached_q = query(filters=None, limit=100)
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new_q = query(filters=None, limit=None)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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def test_can_satisfy_offset_never_reused() -> None:
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cached_q = SemanticQuery(metrics=[M_X], dimensions=[COL_A], offset=5)
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new_q = SemanticQuery(metrics=[M_X], dimensions=[COL_A], offset=5)
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ok, _ = can_satisfy(entry_from(cached_q), new_q)
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assert ok is False
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# ---------------------------------------------------------------------------
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# Post-processing
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# ---------------------------------------------------------------------------
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def test_apply_post_processing_filters_and_limits() -> None:
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df = pd.DataFrame({"a": [1, 3, 5, 7, 9], "x": [10, 20, 30, 40, 50]})
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cached = SemanticResult(
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requests=[SemanticRequest(type="SQL", definition="select ...")],
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results=pa.Table.from_pandas(df, preserve_index=False),
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)
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new_q = query(
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filters={where(COL_A, Operator.GREATER_THAN, 2)},
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limit=2,
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)
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result = _apply_post_processing(
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cached, new_q, {where(COL_A, Operator.GREATER_THAN, 2)}
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)
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result_df = result.results.to_pandas()
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assert list(result_df["a"]) == [3, 5]
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# the cache annotates the requests with a marker
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assert any(req.type == "cache" for req in result.requests)
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def test_apply_post_processing_no_leftovers_no_limit_returns_original() -> None:
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df = pd.DataFrame({"a": [1, 2]})
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cached = SemanticResult(
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requests=[], results=pa.Table.from_pandas(df, preserve_index=False)
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)
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new_q = query(filters=None, limit=None)
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out = _apply_post_processing(cached, new_q, set())
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# same object reference is OK; we explicitly return the input
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assert out is cached
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# ---------------------------------------------------------------------------
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# Hash stability
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# ---------------------------------------------------------------------------
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def test_value_key_stable_across_metric_order() -> None:
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q1 = SemanticQuery(metrics=[M_X, M_Y], dimensions=[COL_A])
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q2 = SemanticQuery(metrics=[M_Y, M_X], dimensions=[COL_A])
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assert value_key(VIEW, q1) == value_key(VIEW, q2)
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def test_shape_key_stable_across_dimension_order() -> None:
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q1 = SemanticQuery(metrics=[M_X], dimensions=[COL_A, COL_B])
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q2 = SemanticQuery(metrics=[M_X], dimensions=[COL_B, COL_A])
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assert shape_key(VIEW, q1) == shape_key(VIEW, q2)
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def test_shape_key_changes_with_changed_on() -> None:
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q = SemanticQuery(metrics=[M_X], dimensions=[COL_A])
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other = ViewMeta(uuid=VIEW.uuid, changed_on_iso="2099-01-01", cache_timeout=None)
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assert shape_key(VIEW, q) != shape_key(other, q)
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def test_value_key_changes_with_filter_value() -> None:
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q1 = SemanticQuery(
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metrics=[M_X],
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dimensions=[COL_A],
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filters={where(COL_A, Operator.GREATER_THAN, 1)},
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)
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q2 = SemanticQuery(
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metrics=[M_X],
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dimensions=[COL_A],
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filters={where(COL_A, Operator.GREATER_THAN, 2)},
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)
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assert value_key(VIEW, q1) != value_key(VIEW, q2)
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def test_value_key_with_datetime_filter() -> None:
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f = where(COL_A, Operator.GREATER_THAN_OR_EQUAL, datetime(2025, 1, 1))
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q = SemanticQuery(metrics=[M_X], dimensions=[COL_A], filters={f})
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# should not raise
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assert value_key(VIEW, q).startswith("sv:val:")
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