Repository: samuelcolvin/pydantic (python)

Issue:
mypy "error: <nothing> not callable" when passing config to validate_arguments
# Bug

Output of `python -c "import pydantic.utils; print(pydantic.utils.version_info())"`:
```
             pydantic version: 1.7
            pydantic compiled: True
                 install path: /home/brian/repos/medigator/venv/lib/python3.6/site-packages/pydantic
               python version: 3.6.9 (default, Oct  8 2020, 12:12:24)  [GCC 8.4.0]
                     platform: Linux-4.15.0-121-generic-x86_64-with-Ubuntu-18.04-bionic
     optional deps. installed: ['typing-extensions', 'email-validator']
```

The example code from the docs demonstrating the use of passing a config to `validate_arguments` causes an error when running mypy (version 0.790):

```py
from pydantic import ValidationError, validate_arguments


class Foobar:
    def __init__(self, v: str):
        self.v = v

    def __add__(self, other: 'Foobar') -> str:
        return f'{self} + {other}'

    def __str__(self) -> str:
        return f'Foobar({self.v})'


@validate_arguments(config=dict(arbitrary_types_allowed=True))
def add_foobars(a: Foobar, b: Foobar):
    return a + b
```

```
test.py:15: error: <nothing> not callable
```

If I remove the `config` parameter but still call `validate_arguments` it still occurs.
If I remove the call and just decorate with `@validate_arguments` then mypy is happy.

I assume it has something to do with the type annotation of `validate_arguments`.

Pull request description:
Add two overload variants to `validate_arguments`
<!-- Thank you for your contribution! -->
<!-- Unless your change is trivial, please create an issue to discuss the change before creating a PR -->
<!-- See https://pydantic-docs.helpmanual.io/contributing/ for help on Contributing -->

## Change Summary

Added two overload variants to `validate_arguments` for the nested decorator signature.

## Related issue number

fix #2052

## Checklist

* [x] Unit tests for the changes exist
* [x] Tests pass on CI and coverage remains at 100%
* [x] ~~Documentation reflects the changes where applicable~~
* [x] `changes/<pull request or issue id>-<github username>.md` file added describing change
  (see [changes/README.md](https://github.com/samuelcolvin/pydantic/blob/master/changes/README.md) for details)


Patch:
diff --git a/Makefile b/Makefile
index 8aa686f4b..cc5d66bcb 100644
--- a/Makefile
+++ b/Makefile
@@ -134,5 +134,5 @@ docs-serve:
 .PHONY: publish-docs
 publish-docs:
 	zip -r site.zip site
-	@curl -f -H "Content-Type: application/zip" -H "Authorization: Bearer ${NETLIFY}" \
+	@curl -H "Content-Type: application/zip" -H "Authorization: Bearer ${NETLIFY}" \
 	      --data-binary "@site.zip" https://api.netlify.com/api/v1/sites/pydantic-docs.netlify.com/deploys
diff --git a/changes/2047-samuelcolvin.md b/changes/2047-samuelcolvin.md
new file mode 100644
index 000000000..6c4c31cf3
--- /dev/null
+++ b/changes/2047-samuelcolvin.md
@@ -0,0 +1,1 @@
+fix `underscore_attrs_are_private` causing `TypeError` when overriding `__init__`
diff --git a/changes/2048-aphedges.md b/changes/2048-aphedges.md
new file mode 100644
index 000000000..0407f2367
--- /dev/null
+++ b/changes/2048-aphedges.md
@@ -0,0 +1,1 @@
+Fix mypy assignment error when using `PrivateAttr`
diff --git a/changes/2055-layday.md b/changes/2055-layday.md
new file mode 100644
index 000000000..047960511
--- /dev/null
+++ b/changes/2055-layday.md
@@ -0,0 +1,1 @@
+fix annotation of `validate_arguments` when passing configuration as argument
diff --git a/docs/datamodel_code_generator.md b/docs/datamodel_code_generator.md
index d96a11c28..dec9cbcb5 100644
--- a/docs/datamodel_code_generator.md
+++ b/docs/datamodel_code_generator.md
@@ -1,18 +1,18 @@
-[datamodel-code-generator](https://github.com/koxudaxi/datamodel-code-generator/) is a command to generate pydantic models from other data types.
+The [datamodel-code-generator](https://github.com/koxudaxi/datamodel-code-generator/) project is a library and command-line utility to generate pydantic models from just about any data source, including:
 
+* OpenAPI 3 (YAML/JSON)
+* JSON Schema
+* JSON/YAML Data (which will converted to JSON Schema)
 
-* Supported source types
-    * OpenAPI 3 (YAML/JSON)
-    * JSON Schema
-    * JSON/YAML Data (It will be converted to JSON Schema)
+Whenever you find yourself with any data convertible JSON but without pydantic models, this tool will allow you to generate type-safe model hierarchies on demand.
 
-## Install
+## Installation
 ```bash
 pip install datamodel-code-generator
 ```
 
 ## Example
-In this case, The datamodel-code-generator creates pydantic models from JSON Schema.
+In this case, datamodel-code-generator creates pydantic models from a JSON Schema file.
 ```bash
 datamodel-codegen  --input person.json --input-file-type jsonschema --output model.py
 ```
diff --git a/pydantic/decorator.py b/pydantic/decorator.py
index 589baaaca..0d7ca8822 100644
--- a/pydantic/decorator.py
+++ b/pydantic/decorator.py
@@ -1,5 +1,19 @@
 from functools import wraps
-from typing import TYPE_CHECKING, Any, Dict, List, Mapping, Tuple, Type, TypeVar, Union, cast, get_type_hints
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Dict,
+    List,
+    Mapping,
+    Optional,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+    get_type_hints,
+    overload,
+)
 
 from . import validator
 from .errors import ConfigError
@@ -11,16 +25,26 @@ __all__ = ('validate_arguments',)
 if TYPE_CHECKING:
     from .typing import AnyCallable
 
-    Callable = TypeVar('Callable', bound=AnyCallable)
+    AnyCallableT = TypeVar('AnyCallableT', bound=AnyCallable)
     ConfigType = Union[None, Type[Any], Dict[str, Any]]
 
 
-def validate_arguments(func: 'Callable' = None, *, config: 'ConfigType' = None) -> 'Callable':
+@overload
+def validate_arguments(func: None = None, *, config: 'ConfigType' = None) -> Callable[['AnyCallableT'], 'AnyCallableT']:
+    ...
+
+
+@overload
+def validate_arguments(func: 'AnyCallableT') -> 'AnyCallableT':
+    ...
+
+
+def validate_arguments(func: Optional['AnyCallableT'] = None, *, config: 'ConfigType' = None) -> Any:
     """
     Decorator to validate the arguments passed to a function.
     """
 
-    def validate(_func: 'Callable') -> 'Callable':
+    def validate(_func: 'AnyCallable') -> 'AnyCallable':
         vd = ValidatedFunction(_func, config)
 
         @wraps(_func)
@@ -30,12 +54,12 @@ def validate_arguments(func: 'Callable' = None, *, config: 'ConfigType' = None)
         wrapper_function.vd = vd  # type: ignore
         wrapper_function.raw_function = vd.raw_function  # type: ignore
         wrapper_function.model = vd.model  # type: ignore
-        return cast('Callable', wrapper_function)
+        return wrapper_function
 
     if func:
         return validate(func)
     else:
-        return cast('Callable', validate)
+        return validate
 
 
 ALT_V_ARGS = 'v__args'
@@ -44,7 +68,7 @@ V_POSITIONAL_ONLY_NAME = 'v__positional_only'
 
 
 class ValidatedFunction:
-    def __init__(self, function: 'Callable', config: 'ConfigType'):  # noqa C901
+    def __init__(self, function: 'AnyCallableT', config: 'ConfigType'):  # noqa C901
         from inspect import Parameter, signature
 
         parameters: Mapping[str, Parameter] = signature(function).parameters
diff --git a/pydantic/fields.py b/pydantic/fields.py
index c451770c0..36ea690a2 100644
--- a/pydantic/fields.py
+++ b/pydantic/fields.py
@@ -799,21 +799,10 @@ class ModelField(Representation):
         return args
 
 
-class PrivateAttr(Representation):
-    """
-    Indicates that attribute is only used internally and never mixed with regular fields.
-
-    Types or values of private attrs are not checked by pydantic and it's up to you to keep them relevant.
-
-    Private attrs are stored in model __slots__.
-    """
-
+class ModelPrivateAttr(Representation):
     __slots__ = ('default', 'default_factory')
 
     def __init__(self, default: Any = Undefined, *, default_factory: Optional[NoArgAnyCallable] = None) -> None:
-        if default is not Undefined and default_factory is not None:
-            raise TypeError('default and default_factory args can not be used together')
-
         self.default = default
         self.default_factory = default_factory
 
@@ -825,3 +814,28 @@ class PrivateAttr(Representation):
             other.default,
             other.default_factory,
         )
+
+
+def PrivateAttr(
+    default: Any = Undefined,
+    *,
+    default_factory: Optional[NoArgAnyCallable] = None,
+) -> Any:
+    """
+    Indicates that attribute is only used internally and never mixed with regular fields.
+
+    Types or values of private attrs are not checked by pydantic and it's up to you to keep them relevant.
+
+    Private attrs are stored in model __slots__.
+
+    :param default: the attribute’s default value
+    :param default_factory: callable that will be called when a default value is needed for this attribute
+      If both `default` and `default_factory` are set, an error is raised.
+    """
+    if default is not Undefined and default_factory is not None:
+        raise ValueError('cannot specify both default and default_factory')
+
+    return ModelPrivateAttr(
+        default,
+        default_factory=default_factory,
+    )
diff --git a/pydantic/main.py b/pydantic/main.py
index bc5444a70..bc0b5be5d 100644
--- a/pydantic/main.py
+++ b/pydantic/main.py
@@ -29,7 +29,7 @@ from typing import (
 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, PrivateAttr, Undefined
+from .fields import SHAPE_MAPPING, 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
@@ -215,7 +215,7 @@ class ModelMetaclass(ABCMeta):
         validators: 'ValidatorListDict' = {}
 
         pre_root_validators, post_root_validators = [], []
-        private_attributes: Dict[str, PrivateAttr] = {}
+        private_attributes: Dict[str, ModelPrivateAttr] = {}
         slots: Set[str] = namespace.get('__slots__', ())
         slots = {slots} if isinstance(slots, str) else set(slots)
 
@@ -271,7 +271,7 @@ class ModelMetaclass(ABCMeta):
 
             for var_name, value in namespace.items():
                 can_be_changed = var_name not in class_vars and not isinstance(value, untouched_types)
-                if isinstance(value, PrivateAttr):
+                if isinstance(value, ModelPrivateAttr):
                     if not is_valid_private_name(var_name):
                         raise NameError(
                             f'Private attributes "{var_name}" must not be a valid field name; '
diff --git a/pydantic/utils.py b/pydantic/utils.py
index 96b792fbe..4592223d1 100644
--- a/pydantic/utils.py
+++ b/pydantic/utils.py
@@ -631,4 +631,4 @@ def is_valid_field(name: str) -> bool:
 
 
 def is_valid_private_name(name: str) -> bool:
-    return not is_valid_field(name) and name not in {'__annotations__', '__module__', '__annotations__', '__qualname__'}
+    return not is_valid_field(name) and name not in {'__annotations__', '__classcell__', '__module__', '__qualname__'}


Test patch:
diff --git a/tests/mypy/modules/success.py b/tests/mypy/modules/success.py
index 202184c93..35c2ba3c2 100644
--- a/tests/mypy/modules/success.py
+++ b/tests/mypy/modules/success.py
@@ -9,7 +9,7 @@ from datetime import date, datetime
 from typing import Any, Dict, Generic, List, Optional, TypeVar
 
 from pydantic import BaseModel, NoneStr, PyObject, StrictBool, root_validator, validate_arguments, validator
-from pydantic.fields import Field
+from pydantic.fields import Field, PrivateAttr
 from pydantic.generics import GenericModel
 from pydantic.typing import ForwardRef
 
@@ -121,6 +121,7 @@ class WithField(BaseModel):
     first_name: str = Field('John', const=True)
 
 
+# simple decorator
 @validate_arguments
 def foo(a: int, *, c: str = 'x') -> str:
     return c * a
@@ -130,6 +131,16 @@ foo(1, c='thing')
 foo(1)
 
 
+# nested decorator should not produce an error
+@validate_arguments(config={'arbitrary_types_allowed': True})
+def bar(a: int, *, c: str = 'x') -> str:
+    return c * a
+
+
+bar(1, c='thing')
+bar(1)
+
+
 class Foo(BaseModel):
     a: int
 
@@ -145,3 +156,7 @@ class MyConf(BaseModel):
 conf = MyConf()
 var1: date = conf.str_pyobject(2020, 12, 20)
 var2: date = conf.callable_pyobject(2111, 1, 1)
+
+
+class MyPrivateAttr(BaseModel):
+    _private_field: str = PrivateAttr()
diff --git a/tests/test_private_attributes.py b/tests/test_private_attributes.py
index 07f702c7f..48be872e2 100644
--- a/tests/test_private_attributes.py
+++ b/tests/test_private_attributes.py
@@ -158,5 +158,22 @@ def test_slots_are_ignored():
 
 
 def test_default_and_default_factory_used_error():
-    with pytest.raises(TypeError, match='default and default_factory args can not be used together'):
+    with pytest.raises(ValueError, match='cannot specify both default and default_factory'):
         PrivateAttr(default=123, default_factory=lambda: 321)
+
+
+def test_config_override_init():
+    class MyModel(BaseModel):
+        x: str
+        _private_attr: int
+
+        def __init__(self, **data) -> None:
+            super().__init__(**data)
+            self._private_attr = 123
+
+        class Config:
+            underscore_attrs_are_private = True
+
+    m = MyModel(x='hello')
+    assert m.dict() == {'x': 'hello'}
+    assert m._private_attr == 123