Dealing with constrained types

Author: Val Brodsky

libs/labelbox/src/labelbox/data/annotation_types/metrics/base.py

@@ -1,9 +1,9 @@
 from abc import ABC
-from typing import Dict, Optional, Any, Union
+from typing import Annotated, Dict, Optional, Any, Union
 
-from pydantic import BaseModel, field_validator
+from pydantic import BaseModel, field_validator, Field
 
-ConfidenceValue = pydantic_compat.confloat(ge=0, le=1)
+ConfidenceValue = Annotated[float, Field(ge=0, le=1)]
 
 MIN_CONFIDENCE_SCORES = 2
 MAX_CONFIDENCE_SCORES = 15

libs/labelbox/src/labelbox/data/annotation_types/metrics/confusion_matrix.py

@@ -1,11 +1,11 @@
 from enum import Enum
-from typing import Tuple, Dict, Union
+from typing import Tuple, Dict, Union, Annotated
 
 from pydantic import Field
 
 from .base import ConfidenceValue, BaseMetric
 
-Count = pydantic_compat.conint(ge=0, le=1e10)
+Count = Annotated[int, Field(ge=0, le=1e10)]
 
 ConfusionMatrixMetricValue = Tuple[Count, Count, Count, Count]
 ConfusionMatrixMetricConfidenceValue = Dict[ConfidenceValue,

libs/labelbox/src/labelbox/data/annotation_types/metrics/scalar.py

@@ -1,12 +1,12 @@
 from dataclasses import field
-from typing import Dict, Optional, Union
+from typing import Annotated, Dict, Optional, Union
 from enum import Enum
 
 from .base import ConfidenceValue, BaseMetric
 
-from pydantic import BaseModel
+from pydantic import Field
 
-ScalarMetricValue = pydantic_compat.confloat(ge=0, le=100_000_000)
+ScalarMetricValue = Annotated[float, Field(ge=0, le=100_000_000)]
 ScalarMetricConfidenceValue = Dict[ConfidenceValue, ScalarMetricValue]
 
 

libs/labelbox/src/labelbox/schema/data_row_metadata.py

@@ -7,7 +7,7 @@
 
 from typing import List, Optional, Dict, Union, Callable, Type, Any, Generator, overload, Annotated
 
-from pydantic import StringConstraints
+from pydantic import StringConstraints, Field
 
 from pydantic import BaseModel
 from labelbox.schema.identifiables import DataRowIdentifiers, UniqueIds
@@ -29,9 +29,9 @@ class DataRowMetadataKind(Enum):
 # Metadata schema
 class DataRowMetadataSchema(BaseModel):
     uid: SchemaId
-    name: pydantic_compat.constr(strip_whitespace=True,
-                                 min_length=1,
-                                 max_length=100)
+    name: Annotated[
+        str,
+        StringConstraints(strip_whitespace=True, min_length=1, max_length=100)]
     reserved: bool
     kind: DataRowMetadataKind
     options: Optional[List["DataRowMetadataSchema"]]
@@ -40,10 +40,10 @@ class DataRowMetadataSchema(BaseModel):
 
 DataRowMetadataSchema.update_forward_refs()
 
-Embedding: Type[List[float]] = pydantic_compat.conlist(float,
+Embedding: Type[List[float]] = Annotated[List[float], Field(
                                                        min_items=128,
-                                                       max_items=128)
-String: Type[str] = pydantic_compat.constr(max_length=4096)
+                                                       max_items=128)]
+String: Type[str] = Annotated[List[str], Field(max_length=4096)]
 
 
 # Metadata base class