SNOW-1374013: local testing fix dataframe time parse precision error (#…

…1599)

CHANGELOG.md

@@ -1,5 +1,13 @@
 # Release History
 
+## 1.18.0 (TBD)
+
+### Snowpark Local Testing Updates
+
+#### Bug Fixes
+
+- Fixed a bug that when processing time format, fractional second part is not handled properly.
+
 ## 1.17.0 (2024-05-21)
 
 ### Snowpark Python API Updates

src/snowflake/snowpark/mock/_functions.py

@@ -536,6 +536,7 @@ def mock_to_time(
         [x] For this timestamp, the function gets the number of seconds after the start of the Unix epoch. The function performs a modulo operation to get the remainder from dividing this number by the number of seconds in a day (86400): number_of_seconds % 86400
 
     """
+    import dateutil.parser
 
     def convert_int_string_to_time(d: str):
         return datetime.datetime.utcfromtimestamp(
@@ -549,14 +550,18 @@ def convert_string_to_time(_data: str, _time_format: str, _fractional_seconds: i
             seconds_part = data_parts[1]
             # find the idx that the seconds part ends
             idx = 0
-            while seconds_part[idx].isdigit():
+            while idx < len(seconds_part) and seconds_part[idx].isdigit():
                 idx += 1
             # truncate to precision
             seconds_part = (
                 seconds_part[: min(idx, _fractional_seconds)] + seconds_part[idx:]
             )
             _data = f"{data_parts[0]}.{seconds_part}"
 
+        # %f is optional if fractional seconds part doesn't show up in the input which means it is 0 nanoseconds
+        if len(data_parts) == 1 and ".%f" in _time_format:
+            _time_format = _time_format.replace(".%f", "")
+
         target_datetime = datetime.datetime.strptime(
             process_string_time_with_fractional_seconds(_data, _fractional_seconds),
             _time_format,
@@ -578,13 +583,15 @@ def convert_string_to_time(_data: str, _time_format: str, _fractional_seconds: i
                 time_fmt,
                 fractional_seconds,
             ) = convert_snowflake_datetime_format(_fmt, default_format="%H:%M:%S")
-
+            auto_detect = _fmt is None or str(_fmt).lower() == "auto"
             if isinstance(datatype, StringType):
                 if data.isdigit():
                     res.append(convert_int_string_to_time(data))
                 else:
                     res.append(
-                        convert_string_to_time(data, time_fmt, fractional_seconds)
+                        dateutil.parser.parse(data).time()
+                        if auto_detect
+                        else convert_string_to_time(data, time_fmt, fractional_seconds)
                     )
             elif isinstance(datatype, TimestampType):
                 res.append(data.time())
@@ -593,9 +600,8 @@ def convert_string_to_time(_data: str, _time_format: str, _fractional_seconds: i
                     if data.isdigit():
                         res.append(convert_int_string_to_time(data))
                     else:
-                        res.append(
-                            convert_string_to_time(data, time_fmt, fractional_seconds)
-                        )
+                        # variant type does not support format input
+                        res.append(dateutil.parser.parse(data).time())
                 elif isinstance(data, datetime.time):
                     res.append(data)
                 else:
@@ -915,10 +921,9 @@ def convert_char(row):
             return try_convert(convert_numeric_to_str, try_cast, data)
         elif isinstance(source_datatype, (DateType, TimeType)):
             default_format = _DEFAULT_OUTPUT_FORMAT.get(type(source_datatype))
-            (
-                format,
-                _,
-            ) = convert_snowflake_datetime_format(_fmt, default_format=default_format)
+            (format, _,) = convert_snowflake_datetime_format(
+                _fmt, default_format=default_format, is_input_format=False
+            )
             convert_date_time_to_str = (
                 datetime.datetime.strftime
                 if isinstance(source_datatype, DateType)
@@ -929,10 +934,9 @@ def convert_char(row):
             )
         elif isinstance(source_datatype, TimestampType):
             default_format = _DEFAULT_OUTPUT_FORMAT.get(TimestampType)
-            (
-                format,
-                fractional_seconds,
-            ) = convert_snowflake_datetime_format(_fmt, default_format)
+            (format, fractional_seconds,) = convert_snowflake_datetime_format(
+                _fmt, default_format, is_input_format=False
+            )
             # handle 3f, can use str index
             time_str = try_convert(
                 lambda x: datetime.date.strftime(x, format), try_cast, data

src/snowflake/snowpark/mock/_util.py

@@ -120,10 +120,19 @@ def array_custom_comparator(ascend: bool, null_first: bool, a: Any, b: Any):
     return ret if ascend else -1 * ret
 
 
-def convert_snowflake_datetime_format(format, default_format) -> Tuple[str, int]:
+def convert_snowflake_datetime_format(
+    format, default_format, is_input_format=True
+) -> Tuple[str, int]:
     """
     unified processing of the time format
     converting snowflake date/time/timestamp format into python datetime format
+
+    usage notes on the returning fractional seconds:
+        fractional seconds does not come into effect when parsing input, see following sql
+            alter session set TIME_OUTPUT_FORMAT = 'HH:MI:SS.FF9';
+            select to_time('11:22:44.333333', 'HH:MI:SS.FF1');
+         it still returns '11:22:44.333333' not '11:22:44.3'
+         however fractional seconds is used in controlling the output format
     """
 
     format_to_use = format or default_format
@@ -155,7 +164,9 @@ def convert_snowflake_datetime_format(format, default_format) -> Tuple[str, int]
             # 'FF' is not in the fmt
             pass
 
-    return time_fmt, fractional_seconds
+    # in live connection, input does not appreciate fractional_seconds in the format,
+    # input always treated as nanoseconds if FF[1-9] is specified
+    return time_fmt, 9 if is_input_format else fractional_seconds
 
 
 def convert_numeric_string_value_to_float_seconds(time: str) -> float:
@@ -189,8 +200,10 @@ def process_string_time_with_fractional_seconds(time: str, fractional_seconds) -
         idx = 0
         while idx < len(seconds_part) and seconds_part[idx].isdigit():
             idx += 1
-        # truncate to precision
-        seconds_part = seconds_part[: min(idx, fractional_seconds)] + seconds_part[idx:]
+        # truncate to precision, python can only handle microsecond which is 6 digits
+        seconds_part = (
+            seconds_part[: min(idx, fractional_seconds, 6)] + seconds_part[idx:]
+        )
         ret = f"{time_parts[0]}.{seconds_part}"
     return ret
 

tests/integ/scala/test_function_suite.py

@@ -1361,6 +1361,18 @@ def test_to_time(session, local_testing_mode):
         [
             Row(time(1, 2, 3)),
             Row(time(22, 33, 44)),
+            Row(time(22, 33, 44, 123000)),
+            Row(time(22, 33, 44, 567890)),
+        ],
+    )
+
+    Utils.check_answer(
+        df.select(*[to_time(column, "HH24:MI:SS.FF4") for column in df.columns]),
+        [
+            Row(time(1, 2, 3)),
+            Row(time(22, 33, 44)),
+            Row(time(22, 33, 44, 123000)),
+            Row(time(22, 33, 44, 567890)),
         ],
     )
 
@@ -1583,7 +1595,9 @@ def test_to_timestamp_fmt_string(to_type, expected, session, local_testing_mode)
             to_timestamp_tz,
             [
                 Row(
-                    datetime(2024, 2, 1, 0, 0, tzinfo=pytz.timezone("Etc/GMT+8")),
+                    datetime(
+                        2024, 2, 1, 0, 0, 0, 123456, tzinfo=pytz.timezone("Etc/GMT+8")
+                    ),
                 ),
                 Row(
                     datetime(2024, 2, 2, 0, 0, tzinfo=pytz.timezone("Etc/GMT+8")),
@@ -1596,7 +1610,7 @@ def test_to_timestamp_fmt_string(to_type, expected, session, local_testing_mode)
         (
             to_timestamp_ntz,
             [
-                Row(datetime(2024, 2, 1, 0, 0)),
+                Row(datetime(2024, 2, 1, 0, 0, 0, 123456)),
                 Row(datetime(2024, 2, 2, 0, 0)),
                 Row(datetime(2024, 2, 3, 0, 0)),
             ],
@@ -1605,7 +1619,9 @@ def test_to_timestamp_fmt_string(to_type, expected, session, local_testing_mode)
             to_timestamp_ltz,
             [
                 Row(
-                    datetime(2024, 2, 1, 0, 0, tzinfo=pytz.timezone("Etc/GMT+8")),
+                    datetime(
+                        2024, 2, 1, 0, 0, 0, 123456, tzinfo=pytz.timezone("Etc/GMT+8")
+                    ),
                 ),
                 Row(
                     datetime(2024, 2, 2, 0, 0, tzinfo=pytz.timezone("Etc/GMT+8")),
@@ -1626,7 +1642,7 @@ def test_to_timestamp_fmt_column(to_type, expected, session, local_testing_mode)
     ):
         LocalTimezone.set_local_timezone(pytz.timezone("Etc/GMT+8"))
         data = [
-            ("2024-02-01 00:00:00.000000", "YYYY-MM-DD HH24:MI:SS.FF"),
+            ("2024-02-01 00:00:00.123456789", "YYYY-MM-DD HH24:MI:SS.FF1"),
             ("20240202000000000000", "YYYYMMDDHH24MISSFF"),
             ("03 Feb 2024 00:00:00", "DD mon YYYY HH24:MI:SS"),
         ]

tests/integ/scala/test_table_suite.py

@@ -260,10 +260,6 @@ def test_table_with_semi_structured_types(session, semi_structured_table):
     )
 
 
-@pytest.mark.skipif(
-    "config.getoption('local_testing_mode', default=False)",
-    reason="SNOW-1374013: Local testing fails to parse time '09:15:29.999999'",
-)
 def test_table_with_time_type(session, table_with_time):
     df = session.table(table_with_time)
     # snowflake time has accuracy to 0.99999999. Python has accuracy to 0.999999.

tests/utils.py

@@ -861,7 +861,7 @@ def datetime_primitives2(cls, session: "Session") -> DataFrame:
     @classmethod
     def time_primitives1(cls, session: "Session") -> DataFrame:
         # simple string data
-        data = [("01:02:03",), ("22:33:44",)]
+        data = [("01:02:03",), ("22:33:44",), ("22:33:44.123",), ("22:33:44.56789",)]
         schema = StructType([StructField("a", StringType())])
         return session.create_dataframe(data, schema)