Added support for custom timestamp format

src/databricks/sql/backend/sea/result_set.py

@@ -104,6 +104,7 @@ def _convert_json_types(self, row: List[str]) -> List[Any]:
                 column_name=column_name,
                 precision=precision,
                 scale=scale,
+                timestamp_format=self.connection.non_arrow_timestamp_format,
             )
             converted_row.append(converted_value)
 

src/databricks/sql/backend/sea/utils/conversion.py

@@ -11,6 +11,8 @@
 from dateutil import parser
 from typing import Callable, Dict, Optional
 
+from databricks.sql.utils import parse_timestamp
+
 logger = logging.getLogger(__name__)
 
 
@@ -162,6 +164,9 @@ def convert_value(
                 precision = kwargs.get("precision", None)
                 scale = kwargs.get("scale", None)
                 return converter_func(value, precision, scale)
+            elif sql_type == SqlType.TIMESTAMP:
+                timestamp_format = kwargs.get("timestamp_format", None)
+                return parse_timestamp(value, timestamp_format)
             else:
                 return converter_func(value)
         except Exception as e:

src/databricks/sql/backend/thrift_backend.py

@@ -1296,6 +1296,7 @@ def fetch_results(
         description,
         chunk_id: int,
         use_cloud_fetch=True,
+        timestamp_format=None,
     ):
         thrift_handle = command_id.to_thrift_handle()
         if not thrift_handle:
@@ -1336,6 +1337,7 @@ def fetch_results(
             statement_id=command_id.to_hex_guid(),
             chunk_id=chunk_id,
             http_client=self._http_client,
+            timestamp_format=timestamp_format,
         )
 
         return (

src/databricks/sql/client.py

@@ -295,6 +295,7 @@ def read(self) -> Optional[OAuthToken]:
         self.disable_pandas = kwargs.get("_disable_pandas", False)
         self.lz4_compression = kwargs.get("enable_query_result_lz4_compression", True)
         self.use_cloud_fetch = kwargs.get("use_cloud_fetch", True)
+        self.non_arrow_timestamp_format = kwargs.get("non_arrow_timestamp_format", None)
         self._cursors = []  # type: List[Cursor]
         self.telemetry_batch_size = kwargs.get(
             "telemetry_batch_size", TelemetryClientFactory.DEFAULT_BATCH_SIZE

src/databricks/sql/result_set.py

@@ -245,6 +245,7 @@ def __init__(
                 statement_id=execute_response.command_id.to_hex_guid(),
                 chunk_id=self.num_chunks,
                 http_client=connection.http_client,
+                timestamp_format=connection.non_arrow_timestamp_format,
             )
             if t_row_set.resultLinks:
                 self.num_chunks += len(t_row_set.resultLinks)
@@ -281,6 +282,7 @@ def _fill_results_buffer(self):
             description=self.description,
             use_cloud_fetch=self._use_cloud_fetch,
             chunk_id=self.num_chunks,
+            timestamp_format=self.connection.non_arrow_timestamp_format,
         )
         self.results = results
         self.has_more_rows = has_more_rows

src/databricks/sql/utils.py

@@ -10,6 +10,7 @@
 from decimal import Decimal
 from enum import Enum
 import re
+import pytz
 
 import lz4.frame
 
@@ -53,6 +54,32 @@ def get_session_config_value(
     return None
 
 
+def parse_timestamp(
+    value: str, timestamp_format: Optional[str] = None
+) -> datetime.datetime:
+    """Parse a timestamp string into a datetime object.
+
+    If timestamp_format is provided, tries strptime first and falls back to
+    dateutil.parser.parse on ValueError. If timestamp_format is None, uses
+    dateutil.parser.parse directly.
+
+    Args:
+        value: The timestamp string to parse.
+        timestamp_format: An optional strptime-compatible format string.
+
+    Returns:
+        A datetime.datetime object.
+    """
+    if timestamp_format is not None:
+        try:
+            return datetime.datetime.strptime(value, timestamp_format).replace(
+                tzinfo=pytz.UTC
+            )
+        except ValueError:
+            return parser.parse(value)
+    return parser.parse(value)
+
+
 class ResultSetQueue(ABC):
     @abstractmethod
     def next_n_rows(self, num_rows: int):
@@ -81,6 +108,7 @@ def build_queue(
         http_client,
         lz4_compressed: bool = True,
         description: List[Tuple] = [],
+        timestamp_format: Optional[str] = None,
     ) -> ResultSetQueue:
         """
         Factory method to build a result set queue for Thrift backend.
@@ -93,6 +121,7 @@ def build_queue(
             description (List[List[Any]]): Hive table schema description.
             max_download_threads (int): Maximum number of downloader thread pool threads.
             ssl_options (SSLOptions): SSLOptions object for CloudFetchQueue
+            timestamp_format: Optional strptime-compatible format for timestamp parsing.
 
         Returns:
             ResultSetQueue
@@ -112,7 +141,7 @@ def build_queue(
             )
 
             converted_column_table = convert_to_assigned_datatypes_in_column_table(
-                column_table, description
+                column_table, description, timestamp_format=timestamp_format
             )
 
             return ColumnQueue(ColumnTable(converted_column_table, column_names))
@@ -760,7 +789,9 @@ def convert_decimals_in_arrow_table(table, description) -> "pyarrow.Table":
     return pyarrow.Table.from_arrays(new_columns, schema=new_schema)
 
 
-def convert_to_assigned_datatypes_in_column_table(column_table, description):
+def convert_to_assigned_datatypes_in_column_table(
+    column_table, description, timestamp_format=None
+):
 
     converted_column_table = []
     for i, col in enumerate(column_table):
@@ -774,7 +805,10 @@ def convert_to_assigned_datatypes_in_column_table(column_table, description):
             )
         elif description[i][1] == "timestamp":
             converted_column_table.append(
-                tuple((v if v is None else parser.parse(v)) for v in col)
+                tuple(
+                    (v if v is None else parse_timestamp(v, timestamp_format))
+                    for v in col
+                )
             )
         else:
             converted_column_table.append(col)

tests/unit/test_fetches.py

@@ -80,6 +80,7 @@ def fetch_results(
             description,
             use_cloud_fetch=True,
             chunk_id=0,
+            timestamp_format=None,
         ):
             nonlocal batch_index
             results = FetchTests.make_arrow_queue(batch_list[batch_index])

tests/unit/test_sea_conversion.py

@@ -7,6 +7,7 @@
 import pytest
 import datetime
 import decimal
+import pytz
 from unittest.mock import Mock, patch
 
 from databricks.sql.backend.sea.utils.conversion import SqlType, SqlTypeConverter
@@ -147,3 +148,37 @@ def test_convert_unsupported_type(self):
             SqlTypeConverter.convert_value("complex_value", SqlType.STRUCT, None)
             == "complex_value"
         )
+
+    def test_convert_timestamp_with_format(self):
+        """Test converting timestamp with an explicit strptime format."""
+        fmt = "%Y-%m-%d %H:%M:%S.%f"
+        result = SqlTypeConverter.convert_value(
+            "2023-12-31 12:30:00.123000",
+            SqlType.TIMESTAMP,
+            None,
+            timestamp_format=fmt,
+        )
+        assert isinstance(result, datetime.datetime)
+        assert result == datetime.datetime(2023, 12, 31, 12, 30, 0, 123000, tzinfo=pytz.UTC)
+
+    def test_convert_timestamp_with_format_fallback(self):
+        """Test that non-matching format falls back to dateutil."""
+        fmt = "%Y-%m-%d %H:%M:%S.%f"
+        result = SqlTypeConverter.convert_value(
+            "08-Mar-2024 14:30:15",
+            SqlType.TIMESTAMP,
+            None,
+            timestamp_format=fmt,
+        )
+        assert isinstance(result, datetime.datetime)
+        assert result == datetime.datetime(2024, 3, 8, 14, 30, 15)
+
+    def test_convert_timestamp_without_format(self):
+        """Test converting timestamp without explicit format uses dateutil."""
+        result = SqlTypeConverter.convert_value(
+            "2023-01-15T12:30:45",
+            SqlType.TIMESTAMP,
+            None,
+        )
+        assert isinstance(result, datetime.datetime)
+        assert result == datetime.datetime(2023, 1, 15, 12, 30, 45)

tests/unit/test_util.py

@@ -2,8 +2,10 @@
 import datetime
 from datetime import timezone, timedelta
 import pytest
+import pytz
 from databricks.sql.utils import (
     convert_to_assigned_datatypes_in_column_table,
+    parse_timestamp,
     ColumnTable,
     concat_table_chunks,
     serialize_query_tags,
@@ -224,3 +226,41 @@ def test_serialize_query_tags_all_none_values(self):
         query_tags = {"key1": None, "key2": None, "key3": None}
         result = serialize_query_tags(query_tags)
         assert result == "key1,key2,key3"
+
+
+class TestParseTimestamp:
+    def test_no_format_uses_dateutil(self):
+        result = parse_timestamp("2023-12-31 12:30:00")
+        assert result == datetime.datetime(2023, 12, 31, 12, 30, 0)
+
+    def test_matching_format_uses_strptime(self):
+        fmt = "%Y-%m-%d %H:%M:%S.%f"
+        result = parse_timestamp("2023-12-31 12:30:00.123000", fmt)
+        assert result == datetime.datetime(2023, 12, 31, 12, 30, 0, 123000, tzinfo=pytz.UTC)
+
+    def test_non_matching_format_falls_back_to_dateutil(self):
+        fmt = "%Y-%m-%d %H:%M:%S.%f"
+        # This doesn't match the format, so should fall back to dateutil
+        result = parse_timestamp("08-Mar-2024 14:30:15", fmt)
+        assert result == datetime.datetime(2024, 3, 8, 14, 30, 15)
+
+    def test_convert_column_table_with_timestamp_format(self):
+        description = [
+            ("ts_col", "timestamp", None, None, None, None, None),
+        ]
+        column_table = [("2023-12-31 12:30:00.000000",)]
+        fmt = "%Y-%m-%d %H:%M:%S.%f"
+        result = convert_to_assigned_datatypes_in_column_table(
+            column_table, description, timestamp_format=fmt
+        )
+        assert result[0][0] == datetime.datetime(2023, 12, 31, 12, 30, 0, tzinfo=pytz.UTC)
+
+    def test_convert_column_table_without_timestamp_format(self):
+        description = [
+            ("ts_col", "timestamp", None, None, None, None, None),
+        ]
+        column_table = [("2023-12-31 12:30:00",)]
+        result = convert_to_assigned_datatypes_in_column_table(
+            column_table, description
+        )
+        assert result[0][0] == datetime.datetime(2023, 12, 31, 12, 30, 0)