feat(chart-data): add rowcount, timegrain and column result types (#13271)

* feat(chart-data): add rowcount, timegrain and column result types

* break out actions from query_context

* rename module

superset/utils/core.py

@@ -83,6 +83,7 @@ from sqlalchemy.engine import Connection, Engine
 from sqlalchemy.engine.reflection import Inspector
 from sqlalchemy.sql.type_api import Variant
 from sqlalchemy.types import TEXT, TypeDecorator
+from typing_extensions import TypedDict
 
 import _thread  # pylint: disable=C0411
 from superset.errors import ErrorLevel, SupersetErrorType
@@ -100,7 +101,7 @@ except ImportError:
     pass
 
 if TYPE_CHECKING:
-    from superset.connectors.base.models import BaseDatasource
+    from superset.connectors.base.models import BaseColumn, BaseDatasource
     from superset.models.core import Database
 
 
@@ -163,10 +164,17 @@ class ChartDataResultType(str, Enum):
     Chart data response type
     """
 
+    COLUMNS = "columns"
     FULL = "full"
     QUERY = "query"
     RESULTS = "results"
     SAMPLES = "samples"
+    TIMEGRAINS = "timegrains"
+
+
+class DatasourceDict(TypedDict):
+    type: str
+    id: int
 
 
 class ExtraFiltersTimeColumnType(str, Enum):
@@ -1490,6 +1498,15 @@ def extract_dataframe_dtypes(df: pd.DataFrame) -> List[GenericDataType]:
     return generic_types
 
 
+def extract_column_dtype(col: "BaseColumn") -> GenericDataType:
+    if col.is_temporal:
+        return GenericDataType.TEMPORAL
+    if col.is_numeric:
+        return GenericDataType.NUMERIC
+    # TODO: add check for boolean data type when proper support is added
+    return GenericDataType.STRING
+
+
 def indexed(
     items: List[Any], key: Union[str, Callable[[Any], Any]]
 ) -> Dict[Any, List[Any]]: