Ready for PR

Author: tasfia8

pandas/core/arrays/string_arrow.py

@@ -190,7 +190,7 @@ def _from_sequence(
 
         _chk_pyarrow_available()
 
-        # Bug fix handle explicit dtype "string" or "str"
+        # handle explicit dtype "string" or "str"
         if dtype:
             if isinstance(dtype, str) and dtype == "str":
             # Use StringDtype with Python storage explicitly
@@ -211,7 +211,7 @@ def _from_sequence(
             return cls(pc.cast(scalars, pa.large_string()))
 
 
-        elif isinstance(scalars, KeysView): #Bug Fix
+        elif isinstance(scalars, KeysView): 
             #Convert dict_keys to a NumPy array. Note dict_keys is a type alias for KeysView.
             scalars = list(scalars)
 

pandas/core/construction.py

@@ -666,11 +666,11 @@ def sanitize_array(
         subarr = _sanitize_str_dtypes(subarr, data, dtype, copy)
 
     from pandas.core.arrays.string_ import StringDtype
-    if dtype == "str": #Bug fix
+    if dtype == "str": 
         # Use StringDtype explicitly when dtype="str"
         dtype = StringDtype(storage="python")
 
-    if isinstance(data, KeysView): #Bug fix
+    if isinstance(data, KeysView): 
         # Convert dict_keys to a list for processing
         data = list(data)
 

pandas/core/indexes/base.py

@@ -483,16 +483,15 @@ def __new__(
         tupleize_cols: bool = True,
     ) -> Self:
         from pandas.core.indexes.range import RangeIndex
-        from pandas.core.arrays.string_ import StringDtype #Bug fix
+        from pandas.core.arrays.string_ import StringDtype 
 
         name = maybe_extract_name(name, data, cls)
 
         if dtype is not None:
-            if dtype == "str": #Bug fix
+            if dtype == "str": 
                 dtype = StringDtype(storage="python")
             dtype = pandas_dtype(dtype)
 
-
         data_dtype = getattr(data, "dtype", None)
 
         refs = None
@@ -570,7 +569,7 @@ def __new__(
 
         try:
             arr = sanitize_array(data, None, dtype=dtype, copy=copy)
-            #print(f"sanitize_array received dtype: {dtype}")
+            #print(f"sanitize_array received dtype: {dtype}") 
         except ValueError as err:
             if "index must be specified when data is not list-like" in str(err):
                 raise cls._raise_scalar_data_error(data) from err

pandas/tests/indexes/test_base.py

@@ -69,7 +69,6 @@ def test_constructor_casting(self, index):
         arr = np.array(index)
         new_index = Index(arr)
         tm.assert_contains_all(arr, new_index)
-        #tm.assert_index_equal(index, new_index)
 
         if index.dtype.name == "string":
         # Allow conversion to object when casting back through NumPy array
@@ -1744,7 +1743,7 @@ def test_is_monotonic_pyarrow_list_type():
     assert not idx.is_monotonic_increasing
     assert not idx.is_monotonic_decreasing
 
-def test_index_from_dict_keys_with_dtype():  # Bug fix
+def test_index_from_dict_keys_with_dtype():  
     d = {"a": 1, "b": 2}
 
     # Test without dtype (default inference)