Fix formatting errors

Author: prazian

pandas/io/formats/csvs.py

@@ -11,6 +11,7 @@
     Sequence,
 )
 import csv as csvlib
+from datetime import datetime as _pydatetime
 import os
 from typing import (
     TYPE_CHECKING,
@@ -20,15 +21,12 @@
 
 import numpy as np
 
-from datetime import datetime as _pydatetime
-
-from pandas.core.dtypes.dtypes import DatetimeTZDtype
-from pandas.core.dtypes.common import is_object_dtype
-
 from pandas._libs import writers as libwriters
 from pandas._typing import SequenceNotStr
 from pandas.util._decorators import cache_readonly
 
+from pandas.core.dtypes.common import is_object_dtype
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas.core.dtypes.generic import (
     ABCDatetimeIndex,
     ABCIndex,
@@ -317,7 +315,6 @@ def _save_body(self) -> None:
                 break
             self._save_chunk(start_i, end_i)
 
-
     # tz-aware CSV formatting helper
     @staticmethod
     def _csv_format_datetime_tz_ea(ser, na_rep: str):
@@ -344,21 +341,24 @@ def _csv_format_py_tz_aware_obj(ser, na_rep: str):
 
         def _is_tzaware_dt(x: object) -> bool:
             return (
-                    isinstance(x, _pydatetime)
-                    and getattr(x, "tzinfo", None) is not None
-                    and x.tzinfo.utcoffset(x) is not None
+                isinstance(x, _pydatetime)
+                and getattr(x, "tzinfo", None) is not None
+                and x.tzinfo.utcoffset(x) is not None
             )
 
-        mask = np.fromiter((_is_tzaware_dt(x) for x in vals), dtype=bool, count=len(vals))
+        mask = np.fromiter(
+            (_is_tzaware_dt(x) for x in vals), dtype=bool, count=len(vals)
+        )
         if mask.any():
             out = vals.copy()
             # isoformat gives 'YYYY-MM-DD HH:MM:SS.ffffff+HH:MM'
-            out[mask] = [x.isoformat(sep=" ", timespec="microseconds") for x in out[mask]]
+            out[mask] = [
+                x.isoformat(sep=" ", timespec="microseconds") for x in out[mask]
+            ]
             ser = ser._constructor(out, index=ser.index, name=ser.name)
 
         return ser.fillna(na_rep)
 
-
     def _save_chunk(self, start_i: int, end_i: int) -> None:
         # create the data for a chunk
         slicer = slice(start_i, end_i)

pandas/tests/io/formats/test_to_csv.py

@@ -1,8 +1,12 @@
+from datetime import (
+    datetime,
+    timedelta,
+    timezone,
+)
 import io
 import os
 import sys
 from zipfile import ZipFile
-from datetime import datetime, timezone, timedelta
 
 from _csv import Error
 import numpy as np
@@ -713,37 +717,43 @@ def test_to_csv_encoding_binary_handle(self, mode):
                 handle.seek(0)
                 assert handle.read().startswith(b'\xef\xbb\xbf""')
 
-
     """
     tz-aware timestamps with/without microseconds should be written consistently
     Checks if the .ffffff format is consistent, even when microseconds==0
 
     GH 62111
     """
+
     def test_to_csv_tz_aware_consistent_microseconds_formatting_python_datetime(self):
-        df = DataFrame({"timestamp": [
-            datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
-            datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
-        ]})
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
+                ]
+            }
+        )
         with tm.ensure_clean("test.csv") as path:
             df.to_csv(path, index=False, lineterminator="\n")
             with open(path, encoding="utf-8") as f:
                 contents = f.read()
 
-        #
         expected = (
             "timestamp\n"
             "2025-08-14 12:34:56.000000+00:00\n"
             "2025-08-14 12:34:56.000001+00:00\n"
         )
         assert contents == expected
 
-
     def test_to_csv_tz_aware_consistent_microseconds_formatting_timestamp(self):
-        df = DataFrame({"timestamp": [
-            pd.Timestamp("2025-08-14 12:34:56+00:00"),
-            pd.Timestamp("2025-08-14 12:34:56.000001+00:00"),
-        ]})
+        df = DataFrame(
+            {
+                "timestamp": [
+                    pd.Timestamp("2025-08-14 12:34:56+00:00"),
+                    pd.Timestamp("2025-08-14 12:34:56.000001+00:00"),
+                ]
+            }
+        )
         with tm.ensure_clean("test.csv") as path:
             df.to_csv(path, index=False, lineterminator="\n")
             with open(path, encoding="utf-8") as f:
@@ -756,41 +766,50 @@ def test_to_csv_tz_aware_consistent_microseconds_formatting_timestamp(self):
         )
         assert contents == expected
 
-
     def test_to_csv_tz_aware_respects_date_format_python_datetime(self):
         # No microseconds in date_format; %z produces +0000 (no colon) by design.
-        df = DataFrame({"timestamp": [
-            datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
-            datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
-        ]})
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
+                ]
+            }
+        )
         with tm.ensure_clean("test.csv") as path:
-            df.to_csv(path, index=False, lineterminator="\n", date_format="%Y-%m-%d %H:%M:%S%z")
+            df.to_csv(
+                path,
+                index=False,
+                lineterminator="\n",
+                date_format="%Y-%m-%d %H:%M:%S%z",
+            )
             with open(path, encoding="utf-8") as f:
                 contents = f.read()
 
-        expected = (
-            "timestamp\n"
-            "2025-08-14 12:34:56+0000\n"
-            "2025-08-14 12:34:56+0000\n"
-        )
+        expected = "timestamp\n2025-08-14 12:34:56+0000\n2025-08-14 12:34:56+0000\n"
         assert contents == expected
 
-
-    def test_to_csv_tz_aware_consistent_microseconds_non_utc_offset_python_datetime(self):
-        ist = timezone(timedelta(hours=5, minutes=30))  # +05:30
-        df = DataFrame({"timestamp": [
-            datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=ist),
-            datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=ist),
-        ]})
+    def test_to_csv_tz_aware_consistent_microseconds_non_utc_offset_python_datetime(
+        self,
+    ):
+        am_tz = timezone(timedelta(hours=4))  # +04:00 (Armenia / Asia/Yerevan)
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=am_tz),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=am_tz),
+                ]
+            }
+        )
         with tm.ensure_clean("test.csv") as path:
             df.to_csv(path, index=False, lineterminator="\n")
             with open(path, encoding="utf-8") as f:
                 contents = f.read()
 
         expected = (
             "timestamp\n"
-            "2025-08-14 12:34:56.000000+05:30\n"
-            "2025-08-14 12:34:56.000001+05:30\n"
+            "2025-08-14 12:34:56.000000+04:00\n"
+            "2025-08-14 12:34:56.000001+04:00\n"
         )
         assert contents == expected