STYLE: fix pylint unnecessary-comprehension warnings (#49674)

* STYLE: fix pylint unnecessary-comprehension warnings

* fixup! STYLE: fix pylint unnecessary-comprehension warnings

* fixup! fixup! STYLE: fix pylint unnecessary-comprehension warnings

Author: Moisan

asv_bench/benchmarks/reshape.py

@@ -112,9 +112,7 @@ def setup(self, dtype):
             values = np.take(list(string.ascii_letters), indices)
             values = [pd.Categorical(v) for v in values.T]
 
-            self.df = DataFrame(
-                {i: cat for i, cat in enumerate(values)}, index, columns
-            )
+            self.df = DataFrame(dict(enumerate(values)), index, columns)
 
         self.df2 = self.df.iloc[:-1]
 

doc/source/conf.py

@@ -374,7 +374,7 @@
 
 
 html_context = {
-    "redirects": {old: new for old, new in moved_api_pages},
+    "redirects": dict(moved_api_pages),
     "header": header,
 }
 

doc/sphinxext/announce.py

@@ -88,7 +88,7 @@ def get_authors(revision_range):
     pre.discard("Homu")
 
     # Append '+' to new authors.
-    authors = [s + " +" for s in cur - pre] + [s for s in cur & pre]
+    authors = [s + " +" for s in cur - pre] + list(cur & pre)
     authors.sort()
     return authors
 

pandas/core/computation/expr.py

@@ -382,7 +382,7 @@ class BaseExprVisitor(ast.NodeVisitor):
 
     unary_ops = UNARY_OPS_SYMS
     unary_op_nodes = "UAdd", "USub", "Invert", "Not"
-    unary_op_nodes_map = {k: v for k, v in zip(unary_ops, unary_op_nodes)}
+    unary_op_nodes_map = dict(zip(unary_ops, unary_op_nodes))
 
     rewrite_map = {
         ast.Eq: ast.In,

pandas/io/xml.py

@@ -283,7 +283,7 @@ def _parse_nodes(self, elems: list[Any]) -> list[dict[str, str | None]]:
         dicts = [{k: d[k] if k in d.keys() else None for k in keys} for d in dicts]
 
         if self.names:
-            dicts = [{nm: v for nm, v in zip(self.names, d.values())} for d in dicts]
+            dicts = [dict(zip(self.names, d.values())) for d in dicts]
 
         return dicts
 
@@ -380,7 +380,7 @@ def _iterparse_nodes(self, iterparse: Callable) -> list[dict[str, str | None]]:
         dicts = [{k: d[k] if k in d.keys() else None for k in keys} for d in dicts]
 
         if self.names:
-            dicts = [{nm: v for nm, v in zip(self.names, d.values())} for d in dicts]
+            dicts = [dict(zip(self.names, d.values())) for d in dicts]
 
         return dicts
 

pandas/tests/frame/constructors/test_from_records.py

@@ -151,7 +151,7 @@ def test_from_records_dictlike(self):
         for b in blocks.values():
             columns.extend(b.columns)
 
-        asdict = {x: y for x, y in df.items()}
+        asdict = dict(df.items())
         asdict2 = {x: y.values for x, y in df.items()}
 
         # dict of series & dict of ndarrays (have dtype info)

pandas/tests/frame/test_constructors.py

@@ -344,7 +344,7 @@ def test_constructor_mixed_dtypes(self, typ, ad):
 
         for d, a in zip(dtypes, arrays):
             assert a.dtype == d
-        ad.update({d: a for d, a in zip(dtypes, arrays)})
+        ad.update(dict(zip(dtypes, arrays)))
         df = DataFrame(ad)
 
         dtypes = MIXED_FLOAT_DTYPES + MIXED_INT_DTYPES

pandas/tests/groupby/test_apply.py

@@ -930,7 +930,7 @@ def test_apply_index_has_complex_internals(index):
         (lambda x: set(x.index.to_list()), [{0, 1}, {2, 3}]),
         (lambda x: tuple(x.index.to_list()), [(0, 1), (2, 3)]),
         (
-            lambda x: {n: i for (n, i) in enumerate(x.index.to_list())},
+            lambda x: dict(enumerate(x.index.to_list())),
             [{0: 0, 1: 1}, {0: 2, 1: 3}],
         ),
         (

pandas/tests/groupby/test_grouping.py

@@ -946,6 +946,9 @@ def test_multi_iter_frame(self, three_group):
         df["k1"] = np.array(["b", "b", "b", "a", "a", "a"])
         df["k2"] = np.array(["1", "1", "1", "2", "2", "2"])
         grouped = df.groupby(["k1", "k2"])
+        # calling `dict` on a DataFrameGroupBy leads to a TypeError,
+        # we need to use a dictionary comprehension here
+        # pylint: disable-next=unnecessary-comprehension
         groups = {key: gp for key, gp in grouped}
         assert len(groups) == 2
 

pandas/tests/indexes/categorical/test_map.py

@@ -109,7 +109,7 @@ def test_map_with_dict_or_series(self):
         # Order of categories in result can be different
         tm.assert_index_equal(result, expected)
 
-        mapper = {o: n for o, n in zip(orig_values[:-1], new_values[:-1])}
+        mapper = dict(zip(orig_values[:-1], new_values[:-1]))
         result = cur_index.map(mapper)
         # Order of categories in result can be different
         tm.assert_index_equal(result, expected)

pandas/tests/io/test_sql.py

@@ -152,7 +152,7 @@ def create_and_load_iris(conn, iris_file: Path, dialect: str):
     with iris_file.open(newline=None) as csvfile:
         reader = csv.reader(csvfile)
         header = next(reader)
-        params = [{key: value for key, value in zip(header, row)} for row in reader]
+        params = [dict(zip(header, row)) for row in reader]
         stmt = insert(iris).values(params)
         if isinstance(conn, Engine):
             with conn.connect() as conn:

pandas/tests/series/methods/test_replace.py

@@ -661,7 +661,7 @@ def test_replace_different_int_types(self, any_int_numpy_dtype):
         labs = pd.Series([1, 1, 1, 0, 0, 2, 2, 2], dtype=any_int_numpy_dtype)
 
         maps = pd.Series([0, 2, 1], dtype=any_int_numpy_dtype)
-        map_dict = {old: new for (old, new) in zip(maps.values, maps.index)}
+        map_dict = dict(zip(maps.values, maps.index))
 
         result = labs.replace(map_dict)
         expected = labs.replace({0: 0, 2: 1, 1: 2})

pyproject.toml

@@ -120,7 +120,6 @@ disable = [
   "too-many-public-methods",
   "too-many-return-statements",
   "too-many-statements",
-  "unnecessary-comprehension",
   "unnecessary-list-index-lookup",
 
   # pylint type "W": warning, for python specific problems