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How to use generate_metric_query method in localstack

Best Python code snippet using localstack_python

alarm_scheduler.py

Source:alarm_scheduler.py

...104    return client.describe_alarms(AlarmNames=[alarm_name])["MetricAlarms"][0]105def get_cloudwatch_client_for_region_of_alarm(alarm_arn: str) -> "CloudWatchClient":106    region = aws_stack.extract_region_from_arn(alarm_arn)107    return aws_stack.connect_to_service("cloudwatch", region_name=region)108def generate_metric_query(alarm_details: MetricAlarm) -> MetricDataQuery:109    """Creates the dict with the required data for MetricDataQueries when calling client.get_metric_data"""110    metric = {111        "MetricName": alarm_details["MetricName"],112    }113    if alarm_details.get("Namespace"):114        metric["Namespace"] = alarm_details["Namespace"]115    if alarm_details.get("Dimensions"):116        metric["Dimensions"] = alarm_details["Dimensions"]117    return {118        "Id": alarm_details["AlarmName"],119        "MetricStat": {120            "Metric": metric,121            "Period": alarm_details["Period"],122            "Stat": alarm_details["Statistic"].capitalize(),123        },124        # TODO other fields might be required in the future125    }126def is_threshold_exceeded(metric_values: List[float], alarm_details: MetricAlarm) -> bool:127    """Evaluates if the threshold is exceeded for the configured alarm and given metric values128    :param metric_values: values to compare against threshold129    :param alarm_details: Alarm Description, as returned from describe_alarms130    :return: True if threshold is exceeded, else False131    """132    threshold = alarm_details["Threshold"]133    comparison_operator = alarm_details["ComparisonOperator"]134    treat_missing_data = alarm_details.get("TreatMissingData", "missing")135    evaluation_periods = alarm_details.get("EvaluationPeriods")136    datapoints_to_alarm = alarm_details.get("DatapointsToAlarm", evaluation_periods)137    evaluated_datapoints = []138    for value in metric_values:139        if value is None:140            if treat_missing_data == "breaching":141                evaluated_datapoints.append(True)142            elif treat_missing_data == "notBreaching":143                evaluated_datapoints.append(False)144            # else we can ignore the data145        else:146            evaluated_datapoints.append(COMPARISON_OPS.get(comparison_operator)(value, threshold))147    sum_breaching = evaluated_datapoints.count(True)148    if sum_breaching >= datapoints_to_alarm:149        return True150    return False151def is_triggering_premature_alarm(metric_values: List[float], alarm_details: MetricAlarm) -> bool:152    """153    Checks if a premature alarm should be triggered.154    https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/AlarmThatSendsEmail.html#CloudWatch-alarms-avoiding-premature-transition:155    [...] alarms are designed to always go into ALARM state when the oldest available breaching datapoint during the Evaluation156    Periods number of data points is at least as old as the value of Datapoints to Alarm, and all other more recent data157    points are breaching or missing. In this case, the alarm goes into ALARM state even if the total number of datapoints158    available is lower than M (Datapoints to Alarm).159    This alarm logic applies to M out of N alarms as well.160    """161    treat_missing_data = alarm_details.get("TreatMissingData", "missing")162    if treat_missing_data not in ("missing", "ignore"):163        return False164    datapoints_to_alarm = alarm_details.get("DatapointsToAlarm", 1)165    if datapoints_to_alarm > 1:166        comparison_operator = alarm_details["ComparisonOperator"]167        threshold = alarm_details["Threshold"]168        oldest_datapoints = metric_values[:-datapoints_to_alarm]169        if oldest_datapoints.count(None) == len(oldest_datapoints):170            if metric_values[-datapoints_to_alarm] and COMPARISON_OPS.get(comparison_operator)(171                metric_values[-datapoints_to_alarm], threshold172            ):173                values = list(filter(None, metric_values[len(oldest_datapoints) :]))174                if all(175                    COMPARISON_OPS.get(comparison_operator)(value, threshold) for value in values176                ):177                    return True178    return False179def collect_metric_data(alarm_details: MetricAlarm, client: "CloudWatchClient") -> List[float]:180    """181    Collects the metric data for the evaluation interval.182    :param alarm_details: the alarm details as returned by describe_alarms183    :param client: the cloudwatch client184    :return: list with data points185    """186    metric_values = []187    evaluation_periods = alarm_details["EvaluationPeriods"]188    period = alarm_details["Period"]189    # From the docs: "Whenever an alarm evaluates whether to change state, CloudWatch attempts to retrieve a higher number of data190    # points than the number specified as Evaluation Periods."191    # No other indication, try to calculate a reasonable value:192    magic_number = max(math.floor(evaluation_periods / 3), 2)193    collected_periods = evaluation_periods + magic_number194    now = datetime.utcnow().replace(tzinfo=timezone.utc)195    metric_query = generate_metric_query(alarm_details)196    # get_metric_data needs to be run in a loop, so we also collect empty data points on the right position197    for i in range(0, collected_periods):198        start_time = now - timedelta(seconds=period)199        end_time = now200        metric_data = client.get_metric_data(201            MetricDataQueries=[metric_query], StartTime=start_time, EndTime=end_time202        )["MetricDataResults"][0]203        val = metric_data["Values"]204        # oldest datapoint should be at the beginning of the list205        metric_values.insert(0, val[0] if val else None)206        now = start_time207    return metric_values208def update_alarm_state(209    client: "CloudWatchClient",...

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