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refactor(api): Separate SegmentType for Integer/Float to Enable Pydantic Serialization (#22025)

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refactor(api): Separate SegmentType for Integer/Float to Enable Pydantic Serialization (#22025)

This PR addresses serialization issues in the VariablePool model by separating the `value_type` tags for `IntegerSegment`/`FloatSegment` and `IntegerVariable`/`FloatVariable`. Previously, both Integer and Float types shared the same `SegmentType.NUMBER` tag, causing conflicts during serialization.

Key changes:
- Introduce distinct `value_type` tags for Integer and Float segments/variables
- Add `VariableUnion` and `SegmentUnion` types for proper type discrimination
- Leverage Pydantic's discriminated union feature for seamless serialization/deserialization
- Enable accurate serialization of data structures containing these types

Closes #22024.
This commit is contained in:
QuantumGhost
2025-07-16 12:31:37 +08:00
committed by GitHub
parent 229b4d621e
commit 2c1ab4879f
58 changed files with 2325 additions and 328 deletions
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67
api/factories/variable_factory.py
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@@ -91,9 +91,13 @@ def _build_variable_from_mapping(*, mapping: Mapping[str, Any], selector: Sequen
result = StringVariable.model_validate(mapping)
case SegmentType.SECRET:
result = SecretVariable.model_validate(mapping)
case SegmentType.NUMBER if isinstance(value, int):
case SegmentType.NUMBER | SegmentType.INTEGER if isinstance(value, int):
mapping = dict(mapping)
mapping["value_type"] = SegmentType.INTEGER
result = IntegerVariable.model_validate(mapping)
case SegmentType.NUMBER if isinstance(value, float):
case SegmentType.NUMBER | SegmentType.FLOAT if isinstance(value, float):
mapping = dict(mapping)
mapping["value_type"] = SegmentType.FLOAT
result = FloatVariable.model_validate(mapping)
case SegmentType.NUMBER if not isinstance(value, float | int):
raise VariableError(f"invalid number value {value}")
@@ -119,6 +123,8 @@ def infer_segment_type_from_value(value: Any, /) -> SegmentType:
def build_segment(value: Any, /) -> Segment:
# NOTE: If you have runtime type information available, consider using the `build_segment_with_type`
# below
if value is None:
return NoneSegment()
if isinstance(value, str):
@@ -134,12 +140,17 @@ def build_segment(value: Any, /) -> Segment:
if isinstance(value, list):
items = [build_segment(item) for item in value]
types = {item.value_type for item in items}
if len(types) != 1 or all(isinstance(item, ArraySegment) for item in items):
if all(isinstance(item, ArraySegment) for item in items):
return ArrayAnySegment(value=value)
elif len(types) != 1:
if types.issubset({SegmentType.NUMBER, SegmentType.INTEGER, SegmentType.FLOAT}):
return ArrayNumberSegment(value=value)
return ArrayAnySegment(value=value)
match types.pop():
case SegmentType.STRING:
return ArrayStringSegment(value=value)
case SegmentType.NUMBER:
case SegmentType.NUMBER | SegmentType.INTEGER | SegmentType.FLOAT:
return ArrayNumberSegment(value=value)
case SegmentType.OBJECT:
return ArrayObjectSegment(value=value)
@@ -153,6 +164,22 @@ def build_segment(value: Any, /) -> Segment:
raise ValueError(f"not supported value {value}")
_segment_factory: Mapping[SegmentType, type[Segment]] = {
SegmentType.NONE: NoneSegment,
SegmentType.STRING: StringSegment,
SegmentType.INTEGER: IntegerSegment,
SegmentType.FLOAT: FloatSegment,
SegmentType.FILE: FileSegment,
SegmentType.OBJECT: ObjectSegment,
# Array types
SegmentType.ARRAY_ANY: ArrayAnySegment,
SegmentType.ARRAY_STRING: ArrayStringSegment,
SegmentType.ARRAY_NUMBER: ArrayNumberSegment,
SegmentType.ARRAY_OBJECT: ArrayObjectSegment,
SegmentType.ARRAY_FILE: ArrayFileSegment,
}
def build_segment_with_type(segment_type: SegmentType, value: Any) -> Segment:
"""
Build a segment with explicit type checking.
@@ -190,7 +217,7 @@ def build_segment_with_type(segment_type: SegmentType, value: Any) -> Segment:
if segment_type == SegmentType.NONE:
return NoneSegment()
else:
raise TypeMismatchError(f"Expected {segment_type}, but got None")
raise TypeMismatchError(f"Type mismatch: expected {segment_type}, but got None")
# Handle empty list special case for array types
if isinstance(value, list) and len(value) == 0:
@@ -205,21 +232,25 @@ def build_segment_with_type(segment_type: SegmentType, value: Any) -> Segment:
elif segment_type == SegmentType.ARRAY_FILE:
return ArrayFileSegment(value=value)
else:
raise TypeMismatchError(f"Expected {segment_type}, but got empty list")
# Build segment using existing logic to infer actual type
inferred_segment = build_segment(value)
inferred_type = inferred_segment.value_type
raise TypeMismatchError(f"Type mismatch: expected {segment_type}, but got empty list")
inferred_type = SegmentType.infer_segment_type(value)
# Type compatibility checking
if inferred_type is None:
raise TypeMismatchError(
f"Type mismatch: expected {segment_type}, but got python object, type={type(value)}, value={value}"
)
if inferred_type == segment_type:
return inferred_segment
# Type mismatch - raise error with descriptive message
raise TypeMismatchError(
f"Type mismatch: expected {segment_type}, but value '{value}' "
f"(type: {type(value).__name__}) corresponds to {inferred_type}"
)
segment_class = _segment_factory[segment_type]
return segment_class(value_type=segment_type, value=value)
elif segment_type == SegmentType.NUMBER and inferred_type in (
SegmentType.INTEGER,
SegmentType.FLOAT,
):
segment_class = _segment_factory[inferred_type]
return segment_class(value_type=inferred_type, value=value)
else:
raise TypeMismatchError(f"Type mismatch: expected {segment_type}, but got {inferred_type}, value={value}")
def segment_to_variable(
@@ -247,6 +278,6 @@ def segment_to_variable(
name=name,
description=description,
value=segment.value,
selector=selector,
selector=list(selector),
),
)