CLN: changed .format to f-string in pandas/core/dtypes

Author: DorAmram

pandas/core/dtypes/common.py

@@ -194,7 +194,7 @@ def ensure_python_int(value: Union[int, np.integer]) -> int:
     """
     if not is_scalar(value):
         raise TypeError(
-            "Value needs to be a scalar value, was type {}".format(type(value))
+            f"Value needs to be a scalar value, was type {type(value)}"
         )
     msg = "Wrong type {} for value {}"
     try:
@@ -1859,7 +1859,7 @@ def _validate_date_like_dtype(dtype) -> None:
     try:
         typ = np.datetime_data(dtype)[0]
     except ValueError as e:
-        raise TypeError("{error}".format(error=e))
+        raise TypeError(e)
     if typ != "generic" and typ != "ns":
         raise ValueError(
             f"{repr(dtype.name)} is too specific of a frequency, "
@@ -1900,7 +1900,9 @@ def pandas_dtype(dtype):
         npdtype = np.dtype(dtype)
     except SyntaxError:
         # np.dtype uses `eval` which can raise SyntaxError
-        raise TypeError("data type '{}' not understood".format(dtype))
+        raise TypeError(
+            f"data type '{dtype}' not understood"
+        )
 
     # Any invalid dtype (such as pd.Timestamp) should raise an error.
     # np.dtype(invalid_type).kind = 0 for such objects. However, this will
@@ -1912,6 +1914,8 @@ def pandas_dtype(dtype):
         # here and `dtype` is an array
         return npdtype
     elif npdtype.kind == "O":
-        raise TypeError("dtype '{}' not understood".format(dtype))
+        raise TypeError(
+            f"dtype '{dtype}' not understood"
+        )
 
     return npdtype

pandas/core/dtypes/dtypes.py

@@ -749,7 +749,7 @@ def construct_from_string(cls, string: str_type):
         raise TypeError("Cannot construct a 'DatetimeTZDtype'")
 
     def __str__(self) -> str_type:
-        return "datetime64[{unit}, {tz}]".format(unit=self.unit, tz=self.tz)
+        return f"datetime64[{self.unit}, {self.tz}]"
 
     @property
     def name(self) -> str_type:
@@ -890,7 +890,7 @@ def __str__(self) -> str_type:
 
     @property
     def name(self) -> str_type:
-        return "period[{freq}]".format(freq=self.freq.freqstr)
+        return f"period[{self.freq.freqstr}]"
 
     @property
     def na_value(self):
@@ -1054,8 +1054,7 @@ def construct_from_string(cls, string):
         if its not possible
         """
         if not isinstance(string, str):
-            msg = "a string needs to be passed, got type {typ}"
-            raise TypeError(msg.format(typ=type(string)))
+            raise TypeError(f"a string needs to be passed, got type {type(string)}")
 
         if string.lower() == "interval" or cls._match.search(string) is not None:
             return cls(string)
@@ -1075,7 +1074,7 @@ def type(self):
     def __str__(self) -> str_type:
         if self.subtype is None:
             return "interval"
-        return "interval[{subtype}]".format(subtype=self.subtype)
+        return f"interval[{self.subtype}]"
 
     def __hash__(self) -> int:
         # make myself hashable