small fix

pyproject.toml

@@ -37,7 +37,7 @@ dependencies = [
     "scipy>=1.10.0",
     "requests>=2.32.0",
     "PyYAML>=6.0.1",
-    "pydantic>=1.10.16",
+    "pydantic>=2.10",
     "litestar>=2.19.0",
     "typing-inspect>=0.9.0",
     "uvicorn[standard]>=0.22.0",

requirements.min.txt

@@ -8,7 +8,7 @@ nltk==3.6.7
 scipy==1.10.0
 requests==2.32.0
 PyYAML==6.0.1
-pydantic==1.10.16
+pydantic==2.10
 litestar==2.19.0
 typing-inspect==0.9.0
 uvicorn==0.22.0

src/evidently/cli/utils.py

@@ -8,9 +8,10 @@
 from typing import TypeVar
 from typing import Union
 
+from pydantic import BaseModel
+from pydantic import TypeAdapter
+
 from evidently import Dataset
-from evidently._pydantic_compat import BaseModel
-from evidently._pydantic_compat import parse_obj_as
 from evidently.core.report import Snapshot
 from evidently.legacy.ui.type_aliases import DatasetID
 from evidently.legacy.ui.type_aliases import ProjectID
@@ -92,7 +93,7 @@ class _Config(BaseModel):
     @classmethod
     def load(cls: Type[T], path: str) -> "T":
         with open(path) as f:
-            return parse_obj_as(cls, json.load(f))
+            return TypeAdapter(cls).validate_python(json.load(f))
 
     def save(self, path: str) -> None:
         with open(path, "w") as f:

src/evidently/core/base_types.py

@@ -1,5 +1,21 @@
+import math
+from typing import Annotated
 from typing import Union
 
-from evidently._pydantic_compat import StrictBool
+from pydantic import BeforeValidator
+from pydantic import StrictBool
 
-Label = Union[StrictBool, int, str, None]
+
+def label_validator(value):
+    if isinstance(value, bool):
+        return value
+    if isinstance(value, int):
+        return value
+    if isinstance(value, str):
+        return value
+    if isinstance(value, float) and math.isnan(value):
+        return "nan"
+    return value
+
+
+Label = Annotated[Union[StrictBool, int, str, float, None], BeforeValidator(label_validator)]

src/evidently/core/container.py

@@ -32,8 +32,7 @@ class MetricContainer(AutoAliasMixin, EvidentlyBaseModel, abc.ABC):
 
     __alias_type__: ClassVar[str] = "metric_container"
 
-    class Config:
-        is_base_type = True
+    __is_base_type__: ClassVar[bool] = True
 
     include_tests: bool = True
     """Whether to include default tests for generated metrics."""

src/evidently/core/datasets.py

@@ -19,9 +19,9 @@
 
 import numpy as np
 import pandas as pd
+from pydantic import BaseModel
+from pydantic import TypeAdapter
 
-from evidently._pydantic_compat import BaseModel
-from evidently._pydantic_compat import parse_obj_as
 from evidently.core.base_types import Label
 from evidently.core.tests import GenericTest
 from evidently.legacy.base_metric import DisplayName
@@ -321,8 +321,7 @@ class SpecialColumnInfo(AutoAliasMixin, EvidentlyBaseModel):
     __alias_type__: ClassVar = "special_column_info"
     """Alias type for serialization."""
 
-    class Config:
-        is_base_type = True
+    __is_base_type__: ClassVar[bool] = True
 
     def get_metrics(self) -> List["MetricOrContainer"]:
         """Get metrics associated with this special column.
@@ -659,8 +658,7 @@ class ColumnCondition(AutoAliasMixin, EvidentlyBaseModel, abc.ABC):
     __alias_type__: ClassVar[str] = "column_condition"
     """Alias type for serialization."""
 
-    class Config:
-        is_base_type = True
+    __is_base_type__: ClassVar[bool] = True
 
     @abstractmethod
     def check(self, value: Any) -> bool:
@@ -738,8 +736,7 @@ class Descriptor(AutoAliasMixin, EvidentlyBaseModel, abc.ABC):
     computed features for evaluation.
     """
 
-    class Config:
-        is_base_type = True
+    __is_base_type__: ClassVar[bool] = True
 
     __alias_type__: ClassVar = "descriptor_v2"
     """Alias type for serialization."""
@@ -822,7 +819,7 @@ def __init__(
     ) -> None:
         self.column = column
         if isinstance(condition, dict):
-            condition = parse_obj_as(ColumnCondition, condition)  # type: ignore[type-abstract]
+            condition = TypeAdapter(ColumnCondition).validate_python(condition)  # type: ignore[type-abstract]
         descriptor_condition: ColumnCondition = (
             condition if isinstance(condition, ColumnCondition) else condition.for_descriptor().condition
         )
@@ -1082,7 +1079,11 @@ def __init__(
         self, feature: GeneratedFeatures, alias: Optional[str] = None, tests: Optional[List[AnyDescriptorTest]] = None
     ):
         # this is needed because we try to access it before super call
-        feature = feature if isinstance(feature, GeneratedFeatures) else parse_obj_as(GeneratedFeatures, feature)  # type: ignore[type-abstract]
+        feature = (
+            feature
+            if isinstance(feature, GeneratedFeatures)
+            else TypeAdapter(GeneratedFeatures).validate_python(feature)
+        )  # type: ignore[type-abstract]
         feature_columns = feature.list_columns()
         super().__init__(feature=feature, alias=alias or f"{feature_columns[0].display_name}", tests=tests)