STY: Add strict=True in zip() in \core

Author: invain01

pandas/core/reshape/concat.py

@@ -422,12 +422,15 @@ def concat(
             intersect
             or any(not isinstance(index, DatetimeIndex) for index in non_concat_axis)
             or all(
-                prev is curr for prev, curr in zip(non_concat_axis, non_concat_axis[1:])
+                prev is curr
+                for prev, curr in zip(non_concat_axis, non_concat_axis[1:], strict=True)
             )
             or (
                 all(
                     prev[-1] <= curr[0] and prev.is_monotonic_increasing
-                    for prev, curr in zip(non_concat_axis, non_concat_axis[1:])
+                    for prev, curr in zip(
+                        non_concat_axis, non_concat_axis[1:], strict=True
+                    )
                     if not prev.empty and not curr.empty
                 )
                 and non_concat_axis[-1].is_monotonic_increasing

pandas/core/reshape/encoding.py

@@ -211,7 +211,9 @@ def check_len(item, name: str) -> None:
             # columns to prepend to result.
             with_dummies = [data.select_dtypes(exclude=dtypes_to_encode)]
 
-        for col, pre, sep in zip(data_to_encode.items(), prefix, prefix_sep):
+        for col, pre, sep in zip(
+            data_to_encode.items(), prefix, prefix_sep, strict=True
+        ):
             # col is (column_name, column), use just column data here
             dummy = _get_dummies_1d(
                 col[1],

pandas/core/reshape/melt.py

@@ -199,7 +199,7 @@ def melt(
         missing = idx == -1
         if missing.any():
             missing_labels = [
-                lab for lab, not_found in zip(labels, missing) if not_found
+                lab for lab, not_found in zip(labels, missing, strict=True) if not_found
             ]
             raise KeyError(
                 "The following id_vars or value_vars are not present in "

pandas/core/reshape/pivot.py

@@ -1098,8 +1098,8 @@ def crosstab(
     from pandas import DataFrame
 
     data = {
-        **dict(zip(unique_rownames, index)),
-        **dict(zip(unique_colnames, columns)),
+        **dict(zip(unique_rownames, index, strict=True)),
+        **dict(zip(unique_colnames, columns, strict=True)),
     }
     df = DataFrame(data, index=common_idx)