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- Unify the metric interface (absorb the current plain string metric for built-in metric keys into the format used by adhoc metric) - Port the logic in adhocMetric on the client and process_metrics in the backend to the new typed Metrics class - Omit hasCustomLabel and formFromData properties from the new metric interface as their value can be inferred from label and optionName - Expose from the Metrics class both metrics and their labels as public methods to match the all_metrics and metric_labels fields in the backend code - Provide defaut values for filters, metrics and groupby in the backend
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# pylint: disable=R
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from typing import Dict, List, Optional
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from superset import app
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from superset.utils import core as utils
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# TODO: Type Metrics dictionary with TypedDict when it becomes a vanilla python type
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# https://github.com/python/mypy/issues/5288
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Metric = Dict
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class QueryObject:
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"""
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The query object's schema matches the interfaces of DB connectors like sqla
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and druid. The query objects are constructed on the client.
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"""
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def __init__(
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self,
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granularity: str,
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groupby: List[str] = None,
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metrics: List[Metric] = None,
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filters: List[str] = None,
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time_range: Optional[str] = None,
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time_shift: Optional[str] = None,
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is_timeseries: bool = False,
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row_limit: int = app.config.get('ROW_LIMIT'),
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limit: int = 0,
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timeseries_limit_metric: Optional[Metric] = None,
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order_desc: bool = True,
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extras: Optional[Dict] = None,
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):
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self.granularity = granularity
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self.from_dttm, self.to_dttm = utils.get_since_until(time_range, time_shift)
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self.is_timeseries = is_timeseries
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self.groupby = groupby or []
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self.metrics = metrics or []
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self.filter = filters or []
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self.row_limit = row_limit
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self.timeseries_limit = int(limit)
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self.timeseries_limit_metric = timeseries_limit_metric
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self.order_desc = order_desc
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self.prequeries = []
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self.is_prequery = False
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self.extras = extras
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def to_dict(self):
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raise NotImplementedError()
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