New dict call fixings #38138

pandas/core/arrays/base.py

@@ -49,7 +49,7 @@
 from pandas.core.missing import get_fill_func
 from pandas.core.sorting import nargminmax, nargsort
 
-_extension_array_shared_docs: Dict[str, str] = dict()
+_extension_array_shared_docs: Dict[str, str] = {}
 
 ExtensionArrayT = TypeVar("ExtensionArrayT", bound="ExtensionArray")
 
@@ -952,7 +952,7 @@ def factorize(self, na_sentinel: int = -1) -> Tuple[np.ndarray, ExtensionArray]:
     @Substitution(klass="ExtensionArray")
     @Appender(_extension_array_shared_docs["repeat"])
     def repeat(self, repeats, axis=None):
-        nv.validate_repeat(tuple(), dict(axis=axis))
+        nv.validate_repeat(tuple(), {"axis": axis})
         ind = np.arange(len(self)).repeat(repeats)
         return self.take(ind)
 

pandas/core/computation/pytables.py

@@ -35,7 +35,7 @@ def __init__(
         queryables: Optional[Dict[str, Any]] = None,
     ):
         super().__init__(level + 1, global_dict=global_dict, local_dict=local_dict)
-        self.queryables = queryables or dict()
+        self.queryables = queryables or {}
 
 
 class Term(ops.Term):

pandas/core/indexes/base.py

@@ -106,15 +106,15 @@
 
 _unsortable_types = frozenset(("mixed", "mixed-integer"))
 
-_index_doc_kwargs = dict(
-    klass="Index",
-    inplace="",
-    target_klass="Index",
-    raises_section="",
-    unique="Index",
-    duplicated="np.ndarray",
-)
-_index_shared_docs = dict()
+_index_doc_kwargs = {
+    "klass": "Index",
+    "inplace": "",
+    "target_klass": "Index",
+    "raises_section": "",
+    "unique": "Index",
+    "duplicated": "np.ndarray",
+}
+_index_shared_docs = {}
 str_t = str
 
 
@@ -817,7 +817,7 @@ def _maybe_disallow_fill(self, allow_fill: bool, fill_value, indices) -> bool:
     @Appender(_index_shared_docs["repeat"] % _index_doc_kwargs)
     def repeat(self, repeats, axis=None):
         repeats = ensure_platform_int(repeats)
-        nv.validate_repeat(tuple(), dict(axis=axis))
+        nv.validate_repeat(tuple(), {"axis": axis})
         return self._shallow_copy(self._values.repeat(repeats))
 
     # --------------------------------------------------------------------
@@ -2155,7 +2155,7 @@ def is_all_dates(self):
     # Pickle Methods
 
     def __reduce__(self):
-        d = dict(data=self._data)
+        d = {"data": self._data}
         d.update(self._get_attributes_dict())
         return _new_Index, (type(self), d), None
 

pandas/core/ops/methods.py

@@ -62,11 +62,11 @@ def add_flex_arithmetic_methods(cls):
     flex_arith_method, flex_comp_method = _get_method_wrappers(cls)
     new_methods = _create_methods(cls, flex_arith_method, flex_comp_method)
     new_methods.update(
-        dict(
-            multiply=new_methods["mul"],
-            subtract=new_methods["sub"],
-            divide=new_methods["div"],
-        )
+        {
+            "multiply": new_methods["mul"],
+            "subtract": new_methods["sub"],
+            "divide": new_methods["div"],
+        }
     )
     # opt out of bool flex methods for now
     assert not any(kname in new_methods for kname in ("ror_", "rxor", "rand_"))
@@ -84,22 +84,22 @@ def _create_methods(cls, arith_method, comp_method):
     new_methods = {}
 
     new_methods.update(
-        dict(
-            add=arith_method(operator.add),
-            radd=arith_method(radd),
-            sub=arith_method(operator.sub),
-            mul=arith_method(operator.mul),
-            truediv=arith_method(operator.truediv),
-            floordiv=arith_method(operator.floordiv),
-            mod=arith_method(operator.mod),
-            pow=arith_method(operator.pow),
-            rmul=arith_method(rmul),
-            rsub=arith_method(rsub),
-            rtruediv=arith_method(rtruediv),
-            rfloordiv=arith_method(rfloordiv),
-            rpow=arith_method(rpow),
-            rmod=arith_method(rmod),
-        )
+        {
+            "add": arith_method(operator.add),
+            "radd": arith_method(radd),
+            "sub": arith_method(operator.sub),
+            "mul": arith_method(operator.mul),
+            "truediv": arith_method(operator.truediv),
+            "floordiv": arith_method(operator.floordiv),
+            "mod": arith_method(operator.mod),
+            "pow": arith_method(operator.pow),
+            "rmul": arith_method(rmul),
+            "rsub": arith_method(rsub),
+            "rtruediv": arith_method(rtruediv),
+            "rfloordiv": arith_method(rfloordiv),
+            "rpow": arith_method(rpow),
+            "rmod": arith_method(rmod),
+        }
     )
     new_methods["div"] = new_methods["truediv"]
     new_methods["rdiv"] = new_methods["rtruediv"]
@@ -109,14 +109,14 @@ def _create_methods(cls, arith_method, comp_method):
         new_methods["rdivmod"] = arith_method(rdivmod)
 
     new_methods.update(
-        dict(
-            eq=comp_method(operator.eq),
-            ne=comp_method(operator.ne),
-            lt=comp_method(operator.lt),
-            gt=comp_method(operator.gt),
-            le=comp_method(operator.le),
-            ge=comp_method(operator.ge),
-        )
+        {
+            "eq": comp_method(operator.eq),
+            "ne": comp_method(operator.ne),
+            "lt": comp_method(operator.lt),
+            "gt": comp_method(operator.gt),
+            "le": comp_method(operator.le),
+            "ge": comp_method(operator.ge),
+        }
     )
 
     new_methods = {k.strip("_"): v for k, v in new_methods.items()}

pandas/io/pytables.py

@@ -2037,7 +2037,7 @@ def convert(self, values: np.ndarray, nan_rep, encoding: str, errors: str):
         val_kind = _ensure_decoded(self.kind)
         values = _maybe_convert(values, val_kind, encoding, errors)
 
-        kwargs = dict()
+        kwargs = {}
         kwargs["name"] = _ensure_decoded(self.index_name)
 
         if self.freq is not None:
@@ -3237,7 +3237,7 @@ def __init__(
         self.non_index_axes = non_index_axes or []
         self.values_axes = values_axes or []
         self.data_columns = data_columns or []
-        self.info = info or dict()
+        self.info = info or {}
         self.nan_rep = nan_rep
 
     @property
@@ -3446,7 +3446,7 @@ def get_attrs(self):
         """ retrieve our attributes """
         self.non_index_axes = getattr(self.attrs, "non_index_axes", None) or []
         self.data_columns = getattr(self.attrs, "data_columns", None) or []
-        self.info = getattr(self.attrs, "info", None) or dict()
+        self.info = getattr(self.attrs, "info", None) or {}
         self.nan_rep = getattr(self.attrs, "nan_rep", None)
         self.encoding = _ensure_encoding(getattr(self.attrs, "encoding", None))
         self.errors = _ensure_decoded(getattr(self.attrs, "errors", "strict"))
@@ -3596,7 +3596,7 @@ def create_index(self, columns=None, optlevel=None, kind: Optional[str] = None):
         if not isinstance(columns, (tuple, list)):
             columns = [columns]
 
-        kw = dict()
+        kw = {}
         if optlevel is not None:
             kw["optlevel"] = optlevel
         if kind is not None:
@@ -3689,7 +3689,7 @@ def validate_data_columns(self, data_columns, min_itemsize, non_index_axes):
             return []
 
         axis, axis_labels = non_index_axes[0]
-        info = self.info.get(axis, dict())
+        info = self.info.get(axis, {})
         if info.get("type") == "MultiIndex" and data_columns:
             raise ValueError(
                 f"cannot use a multi-index on axis [{axis}] with "
@@ -4071,7 +4071,7 @@ def create_description(
         if expectedrows is None:
             expectedrows = max(self.nrows_expected, 10000)
 
-        d = dict(name="table", expectedrows=expectedrows)
+        d = {"name": "table", "expectedrows": expectedrows}
 
         # description from the axes & values
         d["description"] = {a.cname: a.typ for a in self.axes}
@@ -4458,9 +4458,9 @@ def read(
         result = self._read_axes(where=where, start=start, stop=stop)
 
         info = (
-            self.info.get(self.non_index_axes[0][0], dict())
+            self.info.get(self.non_index_axes[0][0], {})
             if len(self.non_index_axes)
-            else dict()
+            else {}
         )
 
         inds = [i for i, ax in enumerate(self.axes) if ax is self.index_axes[0]]