Properly retain types of Mapping subclasses

changes/2325-ofek.md

@@ -0,0 +1 @@
+Prevent `Mapping` subclasses from always being coerced to `dict`

pydantic/fields.py

@@ -1,9 +1,10 @@
 import warnings
-from collections import deque
+from collections import defaultdict, deque
 from collections.abc import Iterable as CollectionsIterable
 from typing import (
     TYPE_CHECKING,
     Any,
+    DefaultDict,
     Deque,
     Dict,
     FrozenSet,
@@ -211,6 +212,8 @@ def Schema(default: Any, **kwargs: Any) -> Any:
 SHAPE_ITERABLE = 9
 SHAPE_GENERIC = 10
 SHAPE_DEQUE = 11
+SHAPE_DICT = 12
+SHAPE_DEFAULTDICT = 13
 SHAPE_NAME_LOOKUP = {
     SHAPE_LIST: 'List[{}]',
     SHAPE_SET: 'Set[{}]',
@@ -219,8 +222,12 @@ def Schema(default: Any, **kwargs: Any) -> Any:
     SHAPE_FROZENSET: 'FrozenSet[{}]',
     SHAPE_ITERABLE: 'Iterable[{}]',
     SHAPE_DEQUE: 'Deque[{}]',
+    SHAPE_DICT: 'Dict[{}]',
+    SHAPE_DEFAULTDICT: 'DefaultDict[{}]',
 }
 
+MAPPING_LIKE_SHAPES: Set[int] = {SHAPE_DEFAULTDICT, SHAPE_DICT, SHAPE_MAPPING}
+
 
 class ModelField(Representation):
     __slots__ = (
@@ -492,6 +499,14 @@ def _type_analysis(self) -> None:  # noqa: C901 (ignore complexity)
         elif issubclass(origin, Sequence):
             self.type_ = get_args(self.type_)[0]
             self.shape = SHAPE_SEQUENCE
+        elif issubclass(origin, DefaultDict):
+            self.key_field = self._create_sub_type(get_args(self.type_)[0], 'key_' + self.name, for_keys=True)
+            self.type_ = get_args(self.type_)[1]
+            self.shape = SHAPE_DEFAULTDICT
+        elif issubclass(origin, Dict):
+            self.key_field = self._create_sub_type(get_args(self.type_)[0], 'key_' + self.name, for_keys=True)
+            self.type_ = get_args(self.type_)[1]
+            self.shape = SHAPE_DICT
         elif issubclass(origin, Mapping):
             self.key_field = self._create_sub_type(get_args(self.type_)[0], 'key_' + self.name, for_keys=True)
             self.type_ = get_args(self.type_)[1]
@@ -608,8 +623,8 @@ def validate(
 
         if self.shape == SHAPE_SINGLETON:
             v, errors = self._validate_singleton(v, values, loc, cls)
-        elif self.shape == SHAPE_MAPPING:
-            v, errors = self._validate_mapping(v, values, loc, cls)
+        elif self.shape in MAPPING_LIKE_SHAPES:
+            v, errors = self._validate_mapping_like(v, values, loc, cls)
         elif self.shape == SHAPE_TUPLE:
             v, errors = self._validate_tuple(v, values, loc, cls)
         elif self.shape == SHAPE_ITERABLE:
@@ -726,7 +741,7 @@ def _validate_tuple(
         else:
             return tuple(result), None
 
-    def _validate_mapping(
+    def _validate_mapping_like(
         self, v: Any, values: Dict[str, Any], loc: 'LocStr', cls: Optional['ModelOrDc']
     ) -> 'ValidateReturn':
         try:
@@ -752,8 +767,31 @@ def _validate_mapping(
             result[key_result] = value_result
         if errors:
             return v, errors
-        else:
+        elif self.shape == SHAPE_DICT:
             return result, None
+        elif self.shape == SHAPE_DEFAULTDICT:
+            return defaultdict(self.type_, result), None
+        else:
+            return self._get_mapping_value(v, result), None
+
+    def _get_mapping_value(self, original: T, converted: Dict[Any, Any]) -> Union[T, Dict[Any, Any]]:
+        """
+        When type is `Mapping[KT, KV]` (or another unsupported mapping), we try to avoid
+        coercing to `dict` unwillingly.
+        """
+        original_cls = original.__class__
+
+        if original_cls == dict or original_cls == Dict:
+            return converted
+        elif original_cls in {defaultdict, DefaultDict}:
+            return defaultdict(self.type_, converted)
+        else:
+            try:
+                # Counter, OrderedDict, UserDict, ...
+                return original_cls(converted)  # type: ignore
+            except TypeError:
+                warnings.warn(f'Could not convert dictionary to {original_cls.__name__!r}', UserWarning)
+                return converted
 
     def _validate_singleton(
         self, v: Any, values: Dict[str, Any], loc: 'LocStr', cls: Optional['ModelOrDc']
@@ -796,7 +834,7 @@ def _type_display(self) -> PyObjectStr:
         t = display_as_type(self.type_)
 
         # have to do this since display_as_type(self.outer_type_) is different (and wrong) on python 3.6
-        if self.shape == SHAPE_MAPPING:
+        if self.shape in MAPPING_LIKE_SHAPES:
             t = f'Mapping[{display_as_type(self.key_field.type_)}, {t}]'  # type: ignore
         elif self.shape == SHAPE_TUPLE:
             t = 'Tuple[{}]'.format(', '.join(display_as_type(f.type_) for f in self.sub_fields))  # type: ignore

pydantic/main.py

@@ -29,7 +29,7 @@
 from .class_validators import ValidatorGroup, extract_root_validators, extract_validators, inherit_validators
 from .error_wrappers import ErrorWrapper, ValidationError
 from .errors import ConfigError, DictError, ExtraError, MissingError
-from .fields import SHAPE_MAPPING, ModelField, ModelPrivateAttr, PrivateAttr, Undefined
+from .fields import MAPPING_LIKE_SHAPES, ModelField, ModelPrivateAttr, PrivateAttr, Undefined
 from .json import custom_pydantic_encoder, pydantic_encoder
 from .parse import Protocol, load_file, load_str_bytes
 from .schema import default_ref_template, model_schema
@@ -524,7 +524,8 @@ def json(
     @classmethod
     def parse_obj(cls: Type['Model'], obj: Any) -> 'Model':
         if cls.__custom_root_type__ and (
-            not (isinstance(obj, dict) and obj.keys() == {ROOT_KEY}) or cls.__fields__[ROOT_KEY].shape == SHAPE_MAPPING
+            not (isinstance(obj, dict) and obj.keys() == {ROOT_KEY})
+            or cls.__fields__[ROOT_KEY].shape in MAPPING_LIKE_SHAPES
         ):
             obj = {ROOT_KEY: obj}
         elif not isinstance(obj, dict):

pydantic/schema.py

@@ -26,10 +26,10 @@
 from uuid import UUID
 
 from .fields import (
+    MAPPING_LIKE_SHAPES,
     SHAPE_FROZENSET,
     SHAPE_ITERABLE,
     SHAPE_LIST,
-    SHAPE_MAPPING,
     SHAPE_SEQUENCE,
     SHAPE_SET,
     SHAPE_SINGLETON,
@@ -446,7 +446,7 @@ def field_type_schema(
         if field.shape in {SHAPE_SET, SHAPE_FROZENSET}:
             f_schema['uniqueItems'] = True
 
-    elif field.shape == SHAPE_MAPPING:
+    elif field.shape in MAPPING_LIKE_SHAPES:
         f_schema = {'type': 'object'}
         key_field = cast(ModelField, field.key_field)
         regex = getattr(key_field.type_, 'regex', None)

tests/test_main.py

@@ -1,6 +1,7 @@
 import sys
+from collections import defaultdict
 from enum import Enum
-from typing import Any, Callable, ClassVar, Dict, List, Mapping, Optional, Type, get_type_hints
+from typing import Any, Callable, ClassVar, DefaultDict, Dict, List, Mapping, Optional, Type, get_type_hints
 from uuid import UUID, uuid4
 
 import pytest
@@ -1472,3 +1473,71 @@ class Item(BaseModel):
 
     assert id(image_1) == id(item.images[0])
     assert id(image_2) == id(item.images[1])
+
+
+def test_mapping_retains_type_subclass():
+    class Map(dict):
+        pass
+
+    class Model(BaseModel):
+        field: Mapping[str, Mapping[str, int]]
+
+    m = Model(field=Map(outer=Map(inner=42)))
+    assert isinstance(m.field, Map)
+    assert isinstance(m.field['outer'], Map)
+    assert m.field['outer']['inner'] == 42
+
+
+def test_mapping_retains_type_defaultdict():
+    class Model(BaseModel):
+        field: Mapping[str, int]
+
+    d = defaultdict(int)
+    d[1] = '2'
+    d['3']
+
+    m = Model(field=d)
+    assert isinstance(m.field, defaultdict)
+    assert m.field['1'] == 2
+    assert m.field['3'] == 0
+
+
+def test_mapping_retains_type_dict_fallback():
+    class Map(dict):
+        def __init__(self, *args, **kwargs):
+            if args or kwargs:
+                raise TypeError('test')
+            super().__init__(*args, **kwargs)
+
+    class Model(BaseModel):
+        field: Mapping[str, int]
+
+    d = Map()
+    d['one'] = 1
+    d['two'] = 2
+
+    with pytest.warns(UserWarning, match="Could not convert dictionary to 'Map'"):
+        m = Model(field=d)
+
+    assert isinstance(m.field, dict)
+    assert m.field['one'] == 1
+    assert m.field['two'] == 2
+
+
+def test_typing_coercion_dict():
+    class Model(BaseModel):
+        x: Dict[str, int]
+
+    m = Model(x={'one': 1, 'two': 2})
+    assert repr(m) == "Model(x={'one': 1, 'two': 2})"
+
+
+def test_typing_coercion_defaultdict():
+    class Model(BaseModel):
+        x: DefaultDict[int, str]
+
+    d = defaultdict(str)
+    d['1']
+    m = Model(x=d)
+    m.x['a']
+    assert repr(m) == "Model(x=defaultdict(<class 'str'>, {1: '', 'a': ''}))"