mirror of https://github.com/apache/superset.git
fix: send CSV pivoted in reports (#16347)
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@ -499,6 +499,12 @@ class ChartRestApi(BaseSupersetModelRestApi):
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result_type = result["query_context"].result_type
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result_format = result["query_context"].result_format
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# Post-process the data so it matches the data presented in the chart.
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# This is needed for sending reports based on text charts that do the
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# post-processing of data, eg, the pivot table.
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if result_type == ChartDataResultType.POST_PROCESSED:
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result = apply_post_process(result, form_data)
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if result_format == ChartDataResultFormat.CSV:
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# Verify user has permission to export CSV file
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if not security_manager.can_access("can_csv", "Superset"):
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@ -509,12 +515,6 @@ class ChartRestApi(BaseSupersetModelRestApi):
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return CsvResponse(data, headers=generate_download_headers("csv"))
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if result_format == ChartDataResultFormat.JSON:
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# Post-process the data so it matches the data presented in the chart.
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# This is needed for sending reports based on text charts that do the
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# post-processing of data, eg, the pivot table.
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if result_type == ChartDataResultType.POST_PROCESSED:
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result = apply_post_process(result, form_data)
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response_data = simplejson.dumps(
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{"result": result["queries"]},
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default=json_int_dttm_ser,
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@ -26,11 +26,17 @@ In order to do that, we reproduce the post-processing in Python
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for these chart types.
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"""
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from io import StringIO
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from typing import Any, Dict, List, Optional, Tuple
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import pandas as pd
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from superset.utils.core import DTTM_ALIAS, extract_dataframe_dtypes, get_metric_name
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from superset.utils.core import (
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ChartDataResultFormat,
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DTTM_ALIAS,
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extract_dataframe_dtypes,
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get_metric_name,
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)
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def get_column_key(label: Tuple[str, ...], metrics: List[str]) -> Tuple[Any, ...]:
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@ -276,7 +282,13 @@ def apply_post_process(
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post_processor = post_processors[viz_type]
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for query in result["queries"]:
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df = pd.DataFrame.from_dict(query["data"])
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if query["result_format"] == ChartDataResultFormat.JSON:
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df = pd.DataFrame.from_dict(query["data"])
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elif query["result_format"] == ChartDataResultFormat.CSV:
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df = pd.read_csv(StringIO(query["data"]))
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else:
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raise Exception(f"Result format {query['result_format']} not supported")
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processed_df = post_processor(df, form_data)
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query["colnames"] = list(processed_df.columns)
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@ -298,6 +310,12 @@ def apply_post_process(
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for index in processed_df.index
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]
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query["data"] = processed_df.to_dict()
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if query["result_format"] == ChartDataResultFormat.JSON:
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query["data"] = processed_df.to_dict()
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elif query["result_format"] == ChartDataResultFormat.CSV:
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buf = StringIO()
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processed_df.to_csv(buf)
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buf.seek(0)
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query["data"] = buf.getvalue()
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return result
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@ -104,6 +104,7 @@ def _get_full(
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payload["indexnames"] = list(df.index)
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payload["coltypes"] = extract_dataframe_dtypes(df)
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payload["data"] = query_context.get_data(df)
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payload["result_format"] = query_context.result_format
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del payload["df"]
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filters = query_obj.filter
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