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pandas/_libs/index.pyx

@@ -447,7 +447,6 @@ cdef class DatetimeEngine(Int64Engine):
                 conv = maybe_datetimelike_to_i8(val)
                 loc = values.searchsorted(conv, side='left')
             except TypeError:
-                self._date_check_type(val)
                 raise KeyError(val)
 
             if loc == len(values) or values[loc] != conv:
@@ -470,12 +469,6 @@ cdef class DatetimeEngine(Int64Engine):
             val = maybe_datetimelike_to_i8(val)
             return self.mapping.get_item(val)
         except (TypeError, ValueError):
-            self._date_check_type(val)
-            raise KeyError(val)
-
-    cdef inline _date_check_type(self, object val):
-        hash(val)
-        if not util.is_integer_object(val):
             raise KeyError(val)
 
     def get_indexer(self, values):

pandas/conftest.py

@@ -65,25 +65,28 @@ def pytest_runtest_setup(item):
         pytest.skip("skipping high memory test since --run-high-memory was not set")
 
 
-# Configurations for all tests and all test modules
-
-
 @pytest.fixture(autouse=True)
 def configure_tests():
+    """
+    Configure settings for all tests and test modules.
+    """
     pd.set_option("chained_assignment", "raise")
 
 
-# For running doctests: make np and pd names available
-
-
 @pytest.fixture(autouse=True)
 def add_imports(doctest_namespace):
+    """
+    Make `np` and `pd` names available for doctests.
+    """
     doctest_namespace["np"] = np
     doctest_namespace["pd"] = pd
 
 
 @pytest.fixture(params=["bsr", "coo", "csc", "csr", "dia", "dok", "lil"])
 def spmatrix(request):
+    """
+    Yields scipy sparse matrix classes.
+    """
     from scipy import sparse
 
     return getattr(sparse, request.param + "_matrix")
@@ -92,8 +95,8 @@ def spmatrix(request):
 @pytest.fixture(params=[0, 1, "index", "columns"], ids=lambda x: f"axis {repr(x)}")
 def axis(request):
     """
-     Fixture for returning the axis numbers of a DataFrame.
-     """
+    Fixture for returning the axis numbers of a DataFrame.
+    """
     return request.param
 
 
@@ -237,6 +240,10 @@ def all_boolean_reductions(request):
 
 @pytest.fixture(params=list(_cython_table))
 def cython_table_items(request):
+    """
+    Yields a tuple of a function and its corresponding name. Correspond to
+    the list of aggregator "Cython functions" used on selected table items.
+    """
     return request.param
 
 
@@ -337,6 +344,9 @@ def writable(request):
 
 @pytest.fixture(scope="module")
 def datetime_tz_utc():
+    """
+    Yields the UTC timezone object from the datetime module.
+    """
     return timezone.utc
 
 
@@ -358,6 +368,9 @@ def join_type(request):
 
 @pytest.fixture
 def strict_data_files(pytestconfig):
+    """
+    Returns the configuration for the test setting `--strict-data-files`.
+    """
     return pytestconfig.getoption("--strict-data-files")
 
 

pandas/core/arrays/period.py

@@ -298,11 +298,11 @@ def __arrow_array__(self, type=None):
                 if self.freqstr != type.freq:
                     raise TypeError(
                         "Not supported to convert PeriodArray to array with different"
-                        " 'freq' ({0} vs {1})".format(self.freqstr, type.freq)
+                        f" 'freq' ({self.freqstr} vs {type.freq})"
                     )
             else:
                 raise TypeError(
-                    "Not supported to convert PeriodArray to '{0}' type".format(type)
+                    f"Not supported to convert PeriodArray to '{type}' type"
                 )
 
         period_type = ArrowPeriodType(self.freqstr)

pandas/core/arrays/timedeltas.py

@@ -43,8 +43,6 @@
 from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import Tick
 
-_BAD_DTYPE = "dtype {dtype} cannot be converted to timedelta64[ns]"
-
 
 def _is_convertible_to_td(key):
     return isinstance(key, (Tick, timedelta, np.timedelta64, str))
@@ -1064,7 +1062,7 @@ def _validate_td64_dtype(dtype):
         raise ValueError(msg)
 
     if not is_dtype_equal(dtype, _TD_DTYPE):
-        raise ValueError(_BAD_DTYPE.format(dtype=dtype))
+        raise ValueError(f"dtype {dtype} cannot be converted to timedelta64[ns]")
 
     return dtype
 

pandas/core/dtypes/common.py

@@ -194,12 +194,11 @@ def ensure_python_int(value: Union[int, np.integer]) -> int:
     """
     if not is_scalar(value):
         raise TypeError(f"Value needs to be a scalar value, was type {type(value)}")
-    msg = "Wrong type {} for value {}"
     try:
         new_value = int(value)
         assert new_value == value
     except (TypeError, ValueError, AssertionError):
-        raise TypeError(msg.format(type(value), value))
+        raise TypeError(f"Wrong type {type(value)} for value {value}")
     return new_value
 
 

pandas/core/dtypes/dtypes.py

@@ -435,12 +435,11 @@ def __eq__(self, other: Any) -> bool:
             return hash(self) == hash(other)
 
     def __repr__(self) -> str_type:
-        tpl = "CategoricalDtype(categories={data}ordered={ordered})"
         if self.categories is None:
             data = "None, "
         else:
             data = self.categories._format_data(name=type(self).__name__)
-        return tpl.format(data=data, ordered=self.ordered)
+        return f"CategoricalDtype(categories={data}ordered={self.ordered})"
 
     @staticmethod
     def _hash_categories(categories, ordered: Ordered = True) -> int:

pandas/core/frame.py

@@ -2431,7 +2431,7 @@ def _verbose_repr():
                 dtype = self.dtypes.iloc[i]
                 col = pprint_thing(col)
 
-                line_no = _put_str(" {num}".format(num=i), space_num)
+                line_no = _put_str(f" {i}", space_num)
                 count = ""
                 if show_counts:
                     count = counts.iloc[i]