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fix(sqla): convert prequery results to native python types (#17195)
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@ -1391,7 +1391,7 @@ class SqlaTable(Model, BaseDatasource): # pylint: disable=too-many-public-metho
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if c not in metrics and c in groupby_series_columns
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]
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top_groups = self._get_top_groups(
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result.df, dimensions, groupby_series_columns
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result.df, dimensions, groupby_series_columns, columns_by_name
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)
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qry = qry.where(top_groups)
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@ -1436,20 +1436,23 @@ class SqlaTable(Model, BaseDatasource): # pylint: disable=too-many-public-metho
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return ob
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def _get_top_groups(
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self, df: pd.DataFrame, dimensions: List[str], groupby_exprs: Dict[str, Any],
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self,
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df: pd.DataFrame,
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dimensions: List[str],
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groupby_exprs: Dict[str, Any],
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columns_by_name: Dict[str, TableColumn],
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) -> ColumnElement:
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column_map = {column.column_name: column for column in self.columns}
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groups = []
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for _unused, row in df.iterrows():
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group = []
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for dimension in dimensions:
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value = row[dimension]
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value = utils.normalize_prequery_result_type(row[dimension])
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# Some databases like Druid will return timestamps as strings, but
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# do not perform automatic casting when comparing these strings to
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# a timestamp. For cases like this we convert the value from a
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# string into a timestamp.
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if column_map[dimension].is_temporal and isinstance(value, str):
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if columns_by_name[dimension].is_temporal and isinstance(value, str):
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dttm = dateutil.parser.parse(value)
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value = text(self.db_engine_spec.convert_dttm("TIMESTAMP", dttm))
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@ -1813,3 +1813,35 @@ def escape_sqla_query_binds(sql: str) -> str:
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sql = sql.replace(bind, bind.replace(":", "\\:"))
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processed_binds.add(bind)
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return sql
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def normalize_prequery_result_type(
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value: Union[str, int, float, bool, np.generic]
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) -> Union[str, int, float, bool]:
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"""
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Convert a value that is potentially a numpy type into its equivalent Python type.
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:param value: primitive datatype in either numpy or python format
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:return: equivalent primitive python type
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>>> normalize_prequery_result_type('abc')
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'abc'
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>>> normalize_prequery_result_type(True)
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True
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>>> normalize_prequery_result_type(123)
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123
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>>> normalize_prequery_result_type(np.int16(123))
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123
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>>> normalize_prequery_result_type(np.uint32(123))
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123
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>>> normalize_prequery_result_type(np.int64(123))
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123
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>>> normalize_prequery_result_type(123.456)
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123.456
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>>> normalize_prequery_result_type(np.float32(123.456))
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123.45600128173828
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>>> normalize_prequery_result_type(np.float64(123.456))
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123.456
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"""
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if isinstance(value, np.generic):
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return value.item()
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return value
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