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fix(python): Fixes a read_database issue loading specific datetime types from SQL Server backends #14627

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Feb 21, 2024
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fix(python): Fixes a read_database issue loading specific datetime types from SQL Server backends #14627

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31 changes: 19 additions & 12 deletions py-polars/polars/io/database.py
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Original file line number Diff line number Diff line change
Expand Up @@ -280,23 +280,29 @@ def _from_rows(

if hasattr(self.result, "fetchall"):
if self.driver_name == "sqlalchemy":
column_names = (
list(self.result._metadata.keys)
if hasattr(self.result, "_metadata")
else [desc[0] for desc in self.result.cursor.description]
)
if hasattr(self.result, "cursor"):
cursor_desc = {d[0]: d[1] for d in self.result.cursor.description}
elif hasattr(self.result, "_metadata"):
cursor_desc = {k: None for k in self.result._metadata.keys}
else:
msg = f"Unable to determine metadata from query result; {self.result!r}"
raise ValueError(msg)
else:
column_names = [desc[0] for desc in self.result.description]
cursor_desc = {d[0]: d[1] for d in self.result.description}

# TODO: refine types based on the cursor description's type_code,
# if/where available? (for now, we just read the column names)
result_columns = list(cursor_desc)

frames = (
DataFrame(
data=rows,
schema=column_names,
schema=result_columns,
schema_overrides=schema_overrides,
orient="row",
)
for rows in (
self._fetchmany_rows(self.result, batch_size)
list(self._fetchmany_rows(self.result, batch_size))
if iter_batches
else [self._fetchall_rows(self.result)] # type: ignore[list-item]
)
Expand Down Expand Up @@ -458,9 +464,10 @@ def read_database( # noqa: D417
be a suitable "Selectable", otherwise it is expected to be a string).
connection
An instantiated connection (or cursor/client object) that the query can be
executed against. Can also pass a valid ODBC connection string, starting with
"Driver=", in which case the `arrow-odbc` package will be used to establish
the connection and return Arrow-native data to Polars.
executed against. Can also pass a valid ODBC connection string, identified as
such if it contains the string "Driver=", in which case the `arrow-odbc`
package will be used to establish the connection and return Arrow-native data
to Polars.
iter_batches
Return an iterator of DataFrames, where each DataFrame represents a batch of
data returned by the query; this can be useful for processing large resultsets
Expand Down Expand Up @@ -560,7 +567,7 @@ def read_database( # noqa: D417
""" # noqa: W505
if isinstance(connection, str):
# check for odbc connection string
if re.sub(r"\s", "", connection[:20]).lower().startswith("driver="):
if re.search(r"\bdriver\s*=\s*{[^}]+?}", connection, re.IGNORECASE):
try:
import arrow_odbc # noqa: F401
except ModuleNotFoundError:
Expand Down
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