Distinguishing annotated types from non-annotated ones in serialization_strategy

README.md

@@ -74,6 +74,7 @@ Table of contents
       * [Subclasses without a common field](#subclasses-without-a-common-field)
       * [Class level discriminator](#class-level-discriminator)
       * [Working with union of classes](#working-with-union-of-classes)
+    * [Extending existing types](#extending-existing-types)
     * [Code generation options](#code-generation-options)
         * [Add `omit_none` keyword argument](#add-omit_none-keyword-argument)
         * [Add `by_alias` keyword argument](#add-by_alias-keyword-argument)
@@ -1127,6 +1128,10 @@ dictionary = instance.to_dict()
 # {'x': '2021', 'y': '2021-01-01'}
 ```
 
+Note that you can register different methods for multiple logical types which
+are based on the same type using `NewType` and `Annotated`.
+See [Extending existing types](#extending-existing-types) for details.
+
 #### `aliases` config option
 
 Sometimes it's better to write the field aliases in one place. You can mix
@@ -1800,7 +1805,7 @@ of all classes and an attempt to deserialize each of them.
 Usually this approach can be used when you have multiple classes without a
 common superclass or when you only need to deserialize some of the subclasses.
 In the following example we will use `include_supertypes=True` to
-deserialize 2 subclasses out of 3:
+deserialize two subclasses out of three:
 
 ```python
 from dataclasses import dataclass
@@ -1897,6 +1902,60 @@ assert plate == Plate(
 )
 ```
 
+### Extending existing types
+
+There are situations where you might want some values of the same type to be
+treated as their own type. You can create new logical types with
+[`NewType`](https://docs.python.org/3/library/typing.html#newtype) or
+[`Annotated`](https://docs.python.org/3/library/typing.html#typing.Annotated)
+and register serialization strategies for them:
+
+```python
+from typing import Mapping, NewType, Annotated
+from dataclasses import dataclass
+from mashumaro import DataClassDictMixin
+
+SessionID = NewType("SessionID", str)
+AccountID = Annotated[str, "AccountID"]
+
+@dataclass
+class Context(DataClassDictMixin):
+    account_sessions: Mapping[AccountID, SessionID]
+
+    class Config:
+        serialization_strategy = {
+            AccountID: {
+                "deserialize": lambda x: ...,
+                "serialize": lambda x: ...,
+            },
+            SessionID: {
+                "deserialize": lambda x: ...,
+                "serialize": lambda x: ...,
+            }
+        }
+```
+
+Although using `NewType` is usually the most reliable way to avoid logical
+errors, you have to pay for it with notable overhead. If you are creating
+dataclass instances manually, then you know that type checkers will
+enforce you to enclose a value in your `"NewType"` callable, which leads
+to performance degradation:
+
+```python
+python -m timeit -s "from typing import NewType; MyInt = NewType('MyInt', int)" "MyInt(42)"
+10000000 loops, best of 5: 31.1 nsec per loop
+
+python -m timeit -s "from typing import NewType; MyInt = NewType('MyInt', int)" "42"
+50000000 loops, best of 5: 4.35 nsec per loop
+```
+
+However, when you instantiate dataclasses using the `from_*` method, there will
+be no performance degradation, because the value won't be enclosed in the
+callable in the generated code. Therefore, if performance is more important
+to you than catching logical errors by type checkers in case you are actively
+creating or changing dataclasses manually, then you should take a closer look
+at using `Annotated`.
+
 ### Code generation options
 
 #### Add `omit_none` keyword argument

mashumaro/core/meta/code/builder.py

@@ -159,10 +159,6 @@ def get_field_resolved_type_params(
         cls = self._get_field_class(field_name)
         return self.resolved_type_params[cls]
 
-    @property
-    def field_types(self) -> typing.Dict[str, typing.Any]:
-        return self.__get_field_types()
-
     def get_field_types(
         self, include_extras: bool = False
     ) -> typing.Dict[str, typing.Any]:
@@ -697,7 +693,7 @@ def get_pack_method_name(
     def _add_pack_method_lines(self, method_name: str) -> None:
         config = self.get_config()
         try:
-            field_types = self.field_types
+            field_types = self.get_field_types(include_extras=True)
         except UnresolvedTypeReferenceError:
             if (
                 not self.allow_postponed_evaluation

mashumaro/core/meta/types/pack.py

@@ -107,7 +107,10 @@ def get_overridden_serialization_method(
     serialize_option = spec.field_ctx.metadata.get("serialize")
     if serialize_option is not None:
         return serialize_option
-    for typ in (spec.type, spec.origin_type):
+    checking_types = [spec.type, spec.origin_type]
+    if spec.annotated_type:
+        checking_types.insert(0, spec.annotated_type)
+    for typ in checking_types:
         for strategy in spec.builder.iter_serialization_strategies(
             spec.field_ctx.metadata, typ
         ):

tests/test_annotated.py

@@ -1,9 +1,10 @@
 from dataclasses import dataclass
-from datetime import date
+from datetime import date, datetime
 
 from typing_extensions import Annotated
 
 from mashumaro import DataClassDictMixin
+from mashumaro.config import BaseConfig
 
 
 def test_annotated():
@@ -14,3 +15,47 @@ class DataClass(DataClassDictMixin):
     obj = DataClass(date(2022, 2, 6))
     assert DataClass.from_dict({"x": "2022-02-06"}) == obj
     assert obj.to_dict() == {"x": "2022-02-06"}
+
+
+def test_annotated_with_overridden_methods():
+    @dataclass
+    class DataClass(DataClassDictMixin):
+        foo: Annotated[date, "foo"]
+        bar: Annotated[date, "bar"]
+        baz: Annotated[date, "baz"]
+
+        class Config(BaseConfig):
+            serialization_strategy = {
+                Annotated[date, "foo"]: {
+                    "serialize": date.toordinal,
+                    "deserialize": date.fromordinal,
+                },
+                Annotated[date, "bar"]: {
+                    "serialize": date.isoformat,
+                    "deserialize": date.fromisoformat,
+                },
+                date: {
+                    "serialize": lambda x: x.strftime("%Y%m%d"),
+                    "deserialize": (
+                        lambda x: datetime.strptime(x, "%Y%m%d").date()
+                    ),
+                },
+            }
+
+    obj = DataClass(
+        foo=date(2023, 6, 12),
+        bar=date(2023, 6, 12),
+        baz=date(2023, 6, 12),
+    )
+    obj.foo.strftime("%Y%M%D")
+    assert (
+        DataClass.from_dict(
+            {"foo": 738683, "bar": "2023-06-12", "baz": "20230612"}
+        )
+        == obj
+    )
+    assert obj.to_dict() == {
+        "foo": 738683,
+        "bar": "2023-06-12",
+        "baz": "20230612",
+    }

tests/test_jsonschema/test_jsonschema_generation.py

@@ -895,7 +895,7 @@ def test_jsonschema_for_unsupported_type():
         build_json_schema(object)
 
 
-def test_overriden_serialization_method_without_signature():
+def test_overridden_serialization_method_without_signature():
     @dataclass
     class DataClass:
         x: datetime.datetime
@@ -921,7 +921,7 @@ class Config(BaseConfig):
         )
 
 
-def test_overriden_serialization_method_without_return_annotation():
+def test_overridden_serialization_method_without_return_annotation():
     def as_timestamp(dt: datetime.datetime):  # pragma no cover
         return dt.timestamp()
 
@@ -939,7 +939,7 @@ class Config(BaseConfig):
     assert build_json_schema(DataClass).properties["y"] == EmptyJSONSchema()
 
 
-def test_overriden_serialization_method_with_return_annotation():
+def test_overridden_serialization_method_with_return_annotation():
     def as_timestamp(dt: datetime.datetime) -> float:
         return dt.timestamp()  # pragma no cover