CLN: use f-strings where possible

Mechanically transformed with `flynt -tc -a -v`

Author: akx

pandas/_config/config.py

@@ -499,7 +499,7 @@ def register_option(
     path = key.split(".")
 
     for k in path:
-        if not re.match("^" + tokenize.Name + "$", k):
+        if not re.match(f"^{tokenize.Name}$", k):
             raise ValueError(f"{k} is not a valid identifier")
         if keyword.iskeyword(k):
             raise ValueError(f"{k} is a python keyword")
@@ -707,7 +707,7 @@ def pp_options_list(keys: Iterable[str], width: int = 80, _print: bool = False):
     from textwrap import wrap
 
     def pp(name: str, ks: Iterable[str]) -> list[str]:
-        pfx = "- " + name + ".[" if name else ""
+        pfx = f"- {name}.[" if name else ""
         ls = wrap(
             ", ".join(ks),
             width,
@@ -716,7 +716,7 @@ def pp(name: str, ks: Iterable[str]) -> list[str]:
             break_long_words=False,
         )
         if ls and ls[-1] and name:
-            ls[-1] = ls[-1] + "]"
+            ls[-1] = f"{ls[-1]}]"
         return ls
 
     ls: list[str] = []

pandas/conftest.py

@@ -1773,7 +1773,7 @@ def spmatrix(request):
     """
     from scipy import sparse
 
-    return getattr(sparse, request.param + "_matrix")
+    return getattr(sparse, f"{request.param}_matrix")
 
 
 @pytest.fixture(

pandas/core/arraylike.py

@@ -304,8 +304,7 @@ def array_ufunc(self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any)
             # well. Previously this raised an internal ValueError. We might
             # support it someday, so raise a NotImplementedError.
             raise NotImplementedError(
-                "Cannot apply ufunc {} to mixed DataFrame and Series "
-                "inputs.".format(ufunc)
+                f"Cannot apply ufunc {ufunc} to mixed DataFrame and Series inputs."
             )
         axes = self.axes
         for obj in alignable[1:]:

pandas/core/arrays/categorical.py

@@ -2166,7 +2166,7 @@ def _repr_categories_info(self) -> str:
         start = True
         cur_col_len = len(levheader)  # header
         sep_len, sep = (3, " < ") if self.ordered else (2, ", ")
-        linesep = sep.rstrip() + "\n"  # remove whitespace
+        linesep = f"{sep.rstrip()}\n"  # remove whitespace
         for val in category_strs:
             if max_width != 0 and cur_col_len + sep_len + len(val) > max_width:
                 levstring += linesep + (" " * (len(levheader) + 1))
@@ -2177,7 +2177,7 @@ def _repr_categories_info(self) -> str:
             levstring += val
             start = False
         # replace to simple save space by
-        return levheader + "[" + levstring.replace(" < ... < ", " ... ") + "]"
+        return f"{levheader}[{levstring.replace(' < ... < ', ' ... ')}]"
 
     def _repr_footer(self) -> str:
         info = self._repr_categories_info()

pandas/core/arrays/masked.py

@@ -1058,7 +1058,7 @@ def _reduce(self, name: str, *, skipna: bool = True, **kwargs):
             data = self.to_numpy("float64", na_value=np.nan)
 
         # median, var, std, skew, kurt, idxmin, idxmax
-        op = getattr(nanops, "nan" + name)
+        op = getattr(nanops, f"nan{name}")
         result = op(data, axis=0, skipna=skipna, mask=mask, **kwargs)
 
         if np.isnan(result):

pandas/core/arrays/string_arrow.py

@@ -317,11 +317,11 @@ def _str_contains(
         return result
 
     def _str_startswith(self, pat: str, na=None):
-        pat = "^" + re.escape(pat)
+        pat = f"^{re.escape(pat)}"
         return self._str_contains(pat, na=na, regex=True)
 
     def _str_endswith(self, pat: str, na=None):
-        pat = re.escape(pat) + "$"
+        pat = f"{re.escape(pat)}$"
         return self._str_contains(pat, na=na, regex=True)
 
     def _str_replace(
@@ -345,14 +345,14 @@ def _str_match(
         self, pat: str, case: bool = True, flags: int = 0, na: Scalar | None = None
     ):
         if not pat.startswith("^"):
-            pat = "^" + pat
+            pat = f"^{pat}"
         return self._str_contains(pat, case, flags, na, regex=True)
 
     def _str_fullmatch(
         self, pat, case: bool = True, flags: int = 0, na: Scalar | None = None
     ):
         if not pat.endswith("$") or pat.endswith("//$"):
-            pat = pat + "$"
+            pat = f"{pat}$"
         return self._str_match(pat, case, flags, na)
 
     def _str_isalnum(self):

pandas/core/computation/expr.py

@@ -410,7 +410,7 @@ def visit(self, node, **kwargs):
                     e.msg = "Python keyword not valid identifier in numexpr query"
                 raise e
 
-        method = "visit_" + type(node).__name__
+        method = f"visit_{type(node).__name__}"
         visitor = getattr(self, method)
         return visitor(node, **kwargs)
 

pandas/core/computation/parsing.py

@@ -59,7 +59,7 @@ def create_valid_python_identifier(name: str) -> str:
     )
 
     name = "".join([special_characters_replacements.get(char, char) for char in name])
-    name = "BACKTICK_QUOTED_STRING_" + name
+    name = f"BACKTICK_QUOTED_STRING_{name}"
 
     if not name.isidentifier():
         raise SyntaxError(f"Could not convert '{name}' to a valid Python identifier.")

pandas/core/computation/scope.py

@@ -250,7 +250,7 @@ def _get_vars(self, stack, scopes: list[str]) -> None:
         variables = itertools.product(scopes, stack)
         for scope, (frame, _, _, _, _, _) in variables:
             try:
-                d = getattr(frame, "f_" + scope)
+                d = getattr(frame, f"f_{scope}")
                 self.scope = DeepChainMap(self.scope.new_child(d))
             finally:
                 # won't remove it, but DECREF it

pandas/core/dtypes/dtypes.py

@@ -804,7 +804,7 @@ def __hash__(self) -> int:
     def __eq__(self, other: Any) -> bool:
         if isinstance(other, str):
             if other.startswith("M8["):
-                other = "datetime64[" + other[3:]
+                other = f"datetime64[{other[3:]}"
             return other == self.name
 
         return (