Fixes #45506 Catch overflow error when converting to datetime

Exception is raised when year is greater than 32 bit signed integer

Added tests for this issue

TODO: Remove this when its fixed in Python

Author: Compro-Prasad

pandas/core/arrays/datetimes.py

@@ -2215,6 +2215,10 @@ def objects_to_datetime64ns(
             return values.view("i8"), tz_parsed
         except (ValueError, TypeError):
             raise err
+    except OverflowError as err:
+        # Exception is raised when year is greater than 32 bit signed integer
+        # TODO: Remove this when its fixed in Python
+        raise ValueError("year out of range") from err
 
     if tz_parsed is not None:
         # We can take a shortcut since the datetime64 numpy array

pandas/tests/arrays/test_array.py

@@ -393,6 +393,21 @@ def test_array_not_registered(registry_without_decimal):
     tm.assert_equal(result, expected)
 
 
+def test_datetime64_eq_string(self):
+    # Issue https://github.com/pandas-dev/pandas/issues/45506
+    # Catch OverflowError when comparing datetime64 and string
+    data = [
+        {"f_0": "2015-07-01", "f_2": "08335394550"},
+        {"f_0": "2015-07-02", "f_2": "+49 (0) 0345 300033"},
+        {"f_0": "2015-07-03", "f_2": "+49(0)2598 04457"},
+        {"f_0": "2015-07-04", "f_2": "0741470003"},
+        {"f_0": "2015-07-05", "f_2": "04181 83668"},
+    ]
+    dtypes = dict(f_0='datetime64[ns]', f_2='string')
+    df = pd.DataFrame(data=data).astype(dtypes)
+    assert df['f_0'].eq(df['f_2']).any() == False
+
+
 class TestArrayAnalytics:
     def test_searchsorted(self, string_dtype):
         arr = pd.array(["a", "b", "c"], dtype=string_dtype)