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perf(classification): cache repeated fact reads

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jxxghp
2026-09-03 12:54:37 +08:00
parent 516687f0de
commit cda109492a
1 changed files with 25 additions and 9 deletions
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34
app/domain/classification/evaluator.py
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@@ -98,6 +98,7 @@ class ClassificationEvaluator:
labels: list[str] = []
traces: list[ClassificationRuleTrace] = []
missing_fields: set[str] = set()
fact_cache: dict[str, tuple[Any, bool]] = {}
for rule_index, rule in enumerate(policy.rules):
if not rule.enabled:
@@ -113,8 +114,9 @@ class ClassificationEvaluator:
rule.when,
facts,
policy.field_aliases,
fact_cache,
trace,
["rules", rule_index, "when"],
["rules", rule_index, "when"] if trace else [],
)
missing_fields.update(outcome.missing_fields)
if outcome.matched:
@@ -185,7 +187,7 @@ class ClassificationEvaluator:
facts: ClassificationFacts,
) -> bool:
"""返回单个条件树是否匹配，不构造解释轨迹。"""
return cls._evaluate_node(condition, facts, {}, False, []).matched
return cls._evaluate_node(condition, facts, {}, {}, False, []).matched
@classmethod
def trace_condition(
@@ -194,7 +196,7 @@ class ClassificationEvaluator:
facts: ClassificationFacts,
) -> list[ClassificationConditionTrace]:
"""执行单个条件树并返回短路后实际求值到的叶子轨迹。"""
return list(cls._evaluate_node(condition, facts, {}, True, []).traces)
return list(cls._evaluate_node(condition, facts, {}, {}, True, []).traces)
@classmethod
def _evaluate_node(
@@ -202,24 +204,34 @@ class ClassificationEvaluator:
node: ClassificationConditionNode,
facts: ClassificationFacts,
field_aliases: Mapping[str, Mapping[str, str]],
fact_cache: dict[str, tuple[Any, bool]],
trace: bool,
path: list[str | int],
) -> _ConditionOutcome:
"""递归求值条件叶子或条件组。"""
if isinstance(node, ClassificationCondition):
return cls._evaluate_leaf(node, facts, field_aliases, trace, path)
return cls._evaluate_group(node, facts, field_aliases, trace, path)
return cls._evaluate_leaf(
node, facts, field_aliases, fact_cache, trace, path
)
return cls._evaluate_group(
node, facts, field_aliases, fact_cache, trace, path
)
@staticmethod
def _evaluate_leaf(
condition: ClassificationCondition,
facts: ClassificationFacts,
field_aliases: Mapping[str, Mapping[str, str]],
fact_cache: dict[str, tuple[Any, bool]],
trace: bool,
path: list[str | int],
) -> _ConditionOutcome:
"""执行叶子条件并应用统一缺失值语义。"""
actual, missing = read_fact(facts, condition.field)
fact = fact_cache.get(condition.field)
if fact is None:
fact = read_fact(facts, condition.field)
fact_cache[condition.field] = fact
actual, missing = fact
if condition.operator == "not_exists":
matched = missing
elif condition.operator == "exists":
@@ -263,6 +275,7 @@ class ClassificationEvaluator:
group: ClassificationConditionGroup,
facts: ClassificationFacts,
field_aliases: Mapping[str, Mapping[str, str]],
fact_cache: dict[str, tuple[Any, bool]],
trace: bool,
path: list[str | int],
) -> _ConditionOutcome:
@@ -276,8 +289,9 @@ class ClassificationEvaluator:
children[0],
facts,
field_aliases,
fact_cache,
trace,
[*path, "not"],
[*path, "not"] if trace else path,
)
# not 不能把普通字段缺失反转成命中；匹配缺失必须显式使用 not_exists。
matched = False if outcome.missing_fields else not outcome.matched
@@ -290,8 +304,9 @@ class ClassificationEvaluator:
child,
facts,
field_aliases,
fact_cache,
trace,
[*path, "all", index],
[*path, "all", index] if trace else path,
)
traces.extend(outcome.traces)
missing_fields.update(outcome.missing_fields)
@@ -310,8 +325,9 @@ class ClassificationEvaluator:
child,
facts,
field_aliases,
fact_cache,
trace,
[*path, "any", index],
[*path, "any", index] if trace else path,
)
traces.extend(outcome.traces)
missing_fields.update(outcome.missing_fields)