refactor: decouple pandas postprocessing operator (#18710)

superset/utils/pandas_postprocessing/aggregate.py

@@ -0,0 +1,46 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from typing import Any, Dict, List
+
+from pandas import DataFrame
+
+from superset.utils.pandas_postprocessing.utils import (
+    _get_aggregate_funcs,
+    validate_column_args,
+)
+
+
+@validate_column_args("groupby")
+def aggregate(
+    df: DataFrame, groupby: List[str], aggregates: Dict[str, Dict[str, Any]]
+) -> DataFrame:
+    """
+    Apply aggregations to a DataFrame.
+
+    :param df: Object to aggregate.
+    :param groupby: columns to aggregate
+    :param aggregates: A mapping from metric column to the function used to
+           aggregate values.
+    :raises QueryObjectValidationError: If the request in incorrect
+    """
+    aggregates = aggregates or {}
+    aggregate_funcs = _get_aggregate_funcs(df, aggregates)
+    if groupby:
+        df_groupby = df.groupby(by=groupby)
+    else:
+        df_groupby = df.groupby(lambda _: True)
+    return df_groupby.agg(**aggregate_funcs).reset_index(drop=not groupby)