ktmud commented on a change in pull request #13271: URL: https://github.com/apache/superset/pull/13271#discussion_r586687878
########## File path: superset/common/query_actions.py ########## @@ -0,0 +1,182 @@ +# 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. +import copy +import math +from typing import Any, Callable, cast, Dict, List, Optional, TYPE_CHECKING + +from flask_babel import _ + +from superset import app +from superset.connectors.base.models import BaseDatasource +from superset.exceptions import QueryObjectValidationError +from superset.utils.core import ( + ChartDataResultType, + extract_column_dtype, + extract_dataframe_dtypes, + get_time_filter_status, + QueryStatus, +) + +if TYPE_CHECKING: + from superset.common.query_context import QueryContext + from superset.common.query_object import QueryObject + +config = app.config + + +def _get_datasource( + query_context: "QueryContext", query_obj: "QueryObject" +) -> BaseDatasource: + return query_obj.datasource or query_context.datasource + + +def _get_columns( + query_context: "QueryContext", query_obj: "QueryObject", _: bool +) -> Dict[str, Any]: + datasource = _get_datasource(query_context, query_obj) + return { + "data": [ + { + "column_name": col.column_name, + "verbose_name": col.verbose_name, + "dtype": extract_column_dtype(col), + } + for col in datasource.columns + ] + } + + +def _get_timegrains( + query_context: "QueryContext", query_obj: "QueryObject", _: bool +) -> Dict[str, Any]: + datasource = _get_datasource(query_context, query_obj) + return { + "data": [ + { + "name": grain.name, + "function": grain.function, + "duration": grain.duration, + } + for grain in datasource.database.grains() + ] + } + + +def _get_query( + query_context: "QueryContext", query_obj: "QueryObject", _: bool, +) -> Dict[str, Any]: + datasource = _get_datasource(query_context, query_obj) + return { + "query": datasource.get_query_str(query_obj.to_dict()), + "language": datasource.query_language, + } + + +def _get_full( + query_context: "QueryContext", + query_obj: "QueryObject", + force_cached: Optional[bool] = False, +) -> Dict[str, Any]: + datasource = _get_datasource(query_context, query_obj) + result_type = query_obj.result_type or query_context.result_type + payload = query_context.get_df_payload(query_obj, force_cached=force_cached) + df = payload["df"] + status = payload["status"] + if status != QueryStatus.FAILED: + payload["colnames"] = list(df.columns) + payload["coltypes"] = extract_dataframe_dtypes(df) + payload["data"] = query_context.get_data(df) + del payload["df"] + + filters = query_obj.filter + filter_columns = cast(List[str], [flt.get("col") for flt in filters]) + columns = set(datasource.column_names) + applied_time_columns, rejected_time_columns = get_time_filter_status( + datasource, query_obj.applied_time_extras + ) + payload["applied_filters"] = [ + {"column": col} for col in filter_columns if col in columns + ] + applied_time_columns + payload["rejected_filters"] = [ + {"reason": "not_in_datasource", "column": col} + for col in filter_columns + if col not in columns + ] + rejected_time_columns + + if result_type == ChartDataResultType.RESULTS and status != QueryStatus.FAILED: + return {"data": payload["data"]} + return payload + + +def _get_samples( + query_context: "QueryContext", query_obj: "QueryObject", force_cached: bool = False +) -> Dict[str, Any]: + datasource = _get_datasource(query_context, query_obj) + row_limit = query_obj.row_limit or math.inf + query_obj = copy.copy(query_obj) + query_obj.is_timeseries = False + query_obj.orderby = [] + query_obj.groupby = [] + query_obj.metrics = [] + query_obj.post_processing = [] + query_obj.row_limit = min(row_limit, config["SAMPLES_ROW_LIMIT"]) + query_obj.row_offset = 0 + query_obj.columns = [o.column_name for o in datasource.columns] + return _get_full(query_context, query_obj, force_cached) + + +def _get_results( + query_context: "QueryContext", query_obj: "QueryObject", force_cached: bool = False +) -> Dict[str, Any]: + payload = _get_full(query_context, query_obj, force_cached) + return {"data": payload["data"]} + + +_result_type_functions: Dict[ + ChartDataResultType, Callable[["QueryContext", "QueryObject", bool], Dict[str, Any]] +] = { + ChartDataResultType.COLUMNS: _get_columns, + ChartDataResultType.TIMEGRAINS: _get_timegrains, + ChartDataResultType.QUERY: _get_query, + ChartDataResultType.SAMPLES: _get_samples, + ChartDataResultType.FULL: _get_full, + ChartDataResultType.RESULTS: _get_results, Review comment: @villebro Sorry for being late to the party, but it there a reason why `is_rowcount` is not implemented as another `ChartDataResultType`? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
