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b221417e19
* chore: migrate all harmless incubator refs like comments and documentation files * chore: migrate all superset.incubator.apache.org to superset.apache.org to * chore: migrate dist.apache.org refs * chore: removing incubating and Disclaimer * fix: linting issues
97 lines
3.0 KiB
Python
97 lines
3.0 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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import logging
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from datetime import datetime
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from typing import Optional
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import pandas as pd
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from sqlalchemy.orm import Session
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from superset import jinja_context
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from superset.models.alerts import Alert, SQLObservation
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logger = logging.getLogger("tasks.email_reports")
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# Session needs to be passed along in the celery workers and db.session cannot be used.
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# For more info see: https://github.com/apache/superset/issues/10530
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def observe(alert_id: int, session: Session) -> Optional[str]:
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"""Collect observations for the alert.
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Returns an error message if the observer value was not valid
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"""
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alert = session.query(Alert).filter_by(id=alert_id).one()
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value = None
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tp = jinja_context.get_template_processor(database=alert.database)
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rendered_sql = tp.process_template(alert.sql)
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df = alert.database.get_df(rendered_sql)
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error_msg = validate_observer_result(df, alert.id, alert.label)
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if not error_msg and not df.empty and df.to_records()[0][1] is not None:
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value = float(df.to_records()[0][1])
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observation = SQLObservation(
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alert_id=alert_id, dttm=datetime.utcnow(), value=value, error_msg=error_msg,
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)
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session.add(observation)
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session.commit()
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return error_msg
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def validate_observer_result(
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sql_result: pd.DataFrame, alert_id: int, alert_label: str
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) -> Optional[str]:
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"""
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Verifies if a DataFrame SQL query result to see if
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it contains a valid value for a SQLObservation.
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Returns an error message if the result is invalid.
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"""
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try:
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if sql_result.empty:
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# empty results are used for the not null validator
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return None
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rows = sql_result.to_records()
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assert (
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len(rows) == 1
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), f"Observer for alert <{alert_id}:{alert_label}> returned more than 1 row"
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assert (
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len(rows[0]) == 2
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), f"Observer for alert <{alert_id}:{alert_label}> returned more than 1 column"
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if rows[0][1] is None:
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return None
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float(rows[0][1])
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except AssertionError as error:
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return str(error)
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except (TypeError, ValueError):
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return (
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f"Observer for alert <{alert_id}:{alert_label}> returned a non-number value"
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)
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return None
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