fix: pydantic dataclass can inherit from stdlib dataclass and arbitrary_types_allowed is supported (#2051)

* fix: pydantic dataclasses can inherit from stdlib dataclasses

closes #2042

* docs: add some documentation

* fix: support arbitrary_types_allowed with stdlib dataclass

closes #2054

* docs: add documentation for custom types

docs/usage/dataclasses.md

@@ -49,6 +49,8 @@ Dataclasses attributes can be populated by tuples, dictionaries or instances of
 
 ## Stdlib dataclasses and _pydantic_ dataclasses
 
+### Convert stdlib dataclasses into _pydantic_ dataclasses
+
 Stdlib dataclasses (nested or not) can be easily converted into _pydantic_ dataclasses by just decorating
 them with `pydantic.dataclasses.dataclass`.
 
@@ -57,6 +59,18 @@ them with `pydantic.dataclasses.dataclass`.
 ```
 _(This script is complete, it should run "as is")_
 
+### Inherit from stdlib dataclasses
+
+Stdlib dataclasses (nested or not) can also be inherited and _pydantic_ will automatically validate
+all the inherited fields.
+
+```py
+{!.tmp_examples/dataclasses_stdlib_inheritance.py!}
+```
+_(This script is complete, it should run "as is")_
+
+### Use of stdlib dataclasses with `BaseModel`
+
 Bear in mind that stdlib dataclasses (nested or not) are **automatically converted** into _pydantic_ dataclasses
 when mixed with `BaseModel`!
 
@@ -65,6 +79,17 @@ when mixed with `BaseModel`!
 ```
 _(This script is complete, it should run "as is")_
 
+### Use custom types
+
+Since stdlib dataclasses are automatically converted to add validation using
+custom types may cause some unexpected behaviour.
+In this case you can simply add `arbitrary_types_allowed` in the config!
+
+```py
+{!.tmp_examples/dataclasses_arbitrary_types_allowed.py!}
+```
+_(This script is complete, it should run "as is")_
+
 ## Initialize hooks
 
 When you initialize a dataclass, it is possible to execute code *after* validation