Support annotated dataclasses

src/py_avro_schema/_schemas.py

@@ -835,6 +835,7 @@ class DataclassSchema(RecordSchema):
     @classmethod
     def handles_type(cls, py_type: Type) -> bool:
         """Whether this schema class can represent a given Python class"""
+        py_type = _type_from_annotated(py_type)
         return dataclasses.is_dataclass(py_type)
 
     def __init__(self, py_type: Type, namespace: Optional[str] = None, options: Option = Option(0)):
@@ -846,6 +847,7 @@ def __init__(self, py_type: Type, namespace: Optional[str] = None, options: Opti
         :param options:   Schema generation options.
         """
         super().__init__(py_type, namespace=namespace, options=options)
+        py_type = _type_from_annotated(py_type)
         self.py_fields = dataclasses.fields(py_type)
         self.record_fields = [self._record_field(field) for field in self.py_fields]
 

tests/test_dataclass.py

@@ -14,7 +14,7 @@
 import decimal
 import enum
 import re
-from typing import Dict, List, Optional
+from typing import Annotated, Dict, List, Optional
 
 import pytest
 import typeguard
@@ -41,6 +41,24 @@ class PyType:
     assert_schema(PyType, expected)
 
 
+def test_class_annotated():
+    @dataclasses.dataclass
+    class PyType:
+        field_a: str
+
+    expected = {
+        "type": "record",
+        "name": "PyType",
+        "fields": [
+            {
+                "name": "field_a",
+                "type": "string",
+            }
+        ],
+    }
+    assert_schema(Annotated[PyType, ...], expected)
+
+
 def test_string_field_mandatory_default():
     @dataclasses.dataclass
     class PyType: