Enabled stricter type checking (#27097)

Author: WillAyd

mypy.ini

@@ -1,5 +1,6 @@
 [mypy]
 ignore_missing_imports=True
+no_implicit_optional=True
 
 [mypy-pandas.conftest,pandas.tests.*]
 ignore_errors=True

pandas/core/arrays/period.py

@@ -195,7 +195,7 @@ def _simple_new(cls, values, freq=None, **kwargs):
     def _from_sequence(
             cls,
             scalars: Sequence[Optional[Period]],
-            dtype: PeriodDtype = None,
+            dtype: Optional[PeriodDtype] = None,
             copy: bool = False,
     ) -> ABCPeriodArray:
         if dtype:

pandas/core/dtypes/dtypes.py

@@ -214,13 +214,13 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
     _metadata = ('categories', 'ordered')
     _cache = {}  # type: Dict[str_type, PandasExtensionDtype]
 
-    def __init__(self, categories=None, ordered: bool = None):
+    def __init__(self, categories=None, ordered: Optional[bool] = None):
         self._finalize(categories, ordered, fastpath=False)
 
     @classmethod
     def _from_fastpath(cls,
                        categories=None,
-                       ordered: bool = None
+                       ordered: Optional[bool] = None
                        ) -> 'CategoricalDtype':
         self = cls.__new__(cls)
         self._finalize(categories, ordered, fastpath=True)
@@ -230,7 +230,7 @@ def _from_fastpath(cls,
     def _from_categorical_dtype(cls,
                                 dtype: 'CategoricalDtype',
                                 categories=None,
-                                ordered: bool = None,
+                                ordered: Optional[bool] = None,
                                 ) -> 'CategoricalDtype':
         if categories is ordered is None:
             return dtype
@@ -244,8 +244,8 @@ def _from_categorical_dtype(cls,
     def _from_values_or_dtype(cls,
                               values=None,
                               categories=None,
-                              ordered: bool = None,
-                              dtype: 'CategoricalDtype' = None,
+                              ordered: Optional[bool] = None,
+                              dtype: Optional['CategoricalDtype'] = None,
                               ) -> 'CategoricalDtype':
         """
         Construct dtype from the input parameters used in :class:`Categorical`.

pandas/core/nanops.py

@@ -228,7 +228,8 @@ def _maybe_get_mask(values: np.ndarray, skipna: bool,
 
 
 def _get_values(values: np.ndarray, skipna: bool, fill_value: Any = None,
-                fill_value_typ: str = None, mask: Optional[np.ndarray] = None
+                fill_value_typ: Optional[str] = None,
+                mask: Optional[np.ndarray] = None
                 ) -> Tuple[np.ndarray, Optional[np.ndarray], np.dtype,
                            np.dtype, Any]:
     """ Utility to get the values view, mask, dtype, dtype_max, and fill_value.