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8d5a6a9918
The default ECharts line chart left-joins each time-shifted comparison series onto the current period's rows, so a historical series gets truncated to wherever the main series ends (e.g. today's partial day). The deprecated NVD3 line chart kept comparison series at their full range, which some users relied on for intraday "today vs prior days" overlays. Add an opt-in "Show full range for time shift" control. When enabled, offset series are outer-joined and their x-axis is rebuilt so each comparison line spans its full period while the current-period line stops at its last data point. Default off; existing behavior unchanged. The option is wired only into the regular timeseries query builder, so it is hidden on Mixed charts where it would be a no-op.
82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import annotations
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import datetime
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from typing import Any, Literal, TYPE_CHECKING
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import numpy as np
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import pandas as pd
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if TYPE_CHECKING:
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from superset.common.query_object import QueryObject
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def left_join_df(
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left_df: pd.DataFrame,
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right_df: pd.DataFrame,
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join_keys: list[str],
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lsuffix: str = "",
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rsuffix: str = "",
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how: Literal["left", "right", "inner", "outer", "cross"] = "left",
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) -> pd.DataFrame:
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# `how` defaults to "left" so callers that only want the left frame's rows are
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# unaffected. Passing how="outer" keeps right-only rows, which is used by the
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# time-comparison "full range" option so historical series are not truncated to
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# the main series' time range.
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df = left_df.set_index(join_keys).join(
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right_df.set_index(join_keys), how=how, lsuffix=lsuffix, rsuffix=rsuffix
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)
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df.reset_index(inplace=True)
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return df
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def full_outer_join_df(
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left_df: pd.DataFrame,
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right_df: pd.DataFrame,
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lsuffix: str = "",
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rsuffix: str = "",
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) -> pd.DataFrame:
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df = left_df.join(right_df, lsuffix=lsuffix, rsuffix=rsuffix, how="outer")
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df.reset_index(inplace=True)
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return df
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def df_metrics_to_num(df: pd.DataFrame, query_object: QueryObject) -> None:
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"""Converting metrics to numeric when pandas.read_sql cannot"""
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for col, dtype in df.dtypes.items():
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if dtype.type == np.object_ and col in query_object.metric_names:
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# soft-convert a metric column to numeric only if all
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# non-null values look numeric (e.g. ClickHouse returns
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# SUM() results as strings). Leaves truly non-numeric
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# columns unchanged.
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converted = pd.to_numeric(df[col], errors="coerce")
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if converted.notna().eq(df[col].notna()).all():
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df[col] = converted
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def is_datetime_series(series: Any) -> bool:
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if series is None or not isinstance(series, pd.Series):
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return False
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if series.isnull().all():
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return False
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return pd.api.types.is_datetime64_any_dtype(series) or (
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series.apply(lambda x: isinstance(x, datetime.date) or x is None).all()
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)
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