AnandInguva commented on code in PR #23931: URL: https://github.com/apache/beam/pull/23931#discussion_r1045182558
########## sdks/python/apache_beam/testing/analyzers/github_issues_utils.py: ########## @@ -0,0 +1,187 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import json +import logging +import os +from typing import List +from typing import Optional +from typing import Tuple + +import pandas as pd +import requests + +try: + _GITHUB_TOKEN: Optional[str] = os.environ['GITHUB_TOKEN'] +except KeyError as e: + _GITHUB_TOKEN = None + logging.warning( + 'A Github Personal Access token is required ' + 'to create Github Issues.') + +# TODO: Change the REPO owner name to apache before merging. +_BEAM_GITHUB_REPO_OWNER = 'AnandInguva' +_BEAM_GITHUB_REPO_NAME = 'beam' +# Adding GitHub Rest API version to the header to maintain version stability. +# For more information, please look at +# https://github.blog/2022-11-28-to-infinity-and-beyond-enabling-the-future-of-githubs-rest-api-with-api-versioning/ # pylint: disable=line-too-long +_HEADERS = { + "Authorization": 'token {}'.format(_GITHUB_TOKEN), + "Accept": "application/vnd.github+json", + "X-GitHub-Api-Version": "2022-11-28" +} + +# Fill the GitHub issue description with the below variables. +_ISSUE_DESCRIPTION_HEADER = """ Review Comment: All the points SG but for 4, I kept in that way because it would be easier to debug and its similar to internal google perf tests. I can remove it as well. ########## sdks/python/apache_beam/testing/analyzers/github_issues_utils.py: ########## @@ -0,0 +1,187 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import json +import logging +import os +from typing import List +from typing import Optional +from typing import Tuple + +import pandas as pd +import requests + +try: + _GITHUB_TOKEN: Optional[str] = os.environ['GITHUB_TOKEN'] +except KeyError as e: + _GITHUB_TOKEN = None + logging.warning( + 'A Github Personal Access token is required ' + 'to create Github Issues.') + +# TODO: Change the REPO owner name to apache before merging. +_BEAM_GITHUB_REPO_OWNER = 'AnandInguva' +_BEAM_GITHUB_REPO_NAME = 'beam' +# Adding GitHub Rest API version to the header to maintain version stability. +# For more information, please look at +# https://github.blog/2022-11-28-to-infinity-and-beyond-enabling-the-future-of-githubs-rest-api-with-api-versioning/ # pylint: disable=line-too-long +_HEADERS = { + "Authorization": 'token {}'.format(_GITHUB_TOKEN), + "Accept": "application/vnd.github+json", + "X-GitHub-Api-Version": "2022-11-28" +} + +# Fill the GitHub issue description with the below variables. Review Comment: Done ########## sdks/python/apache_beam/testing/analyzers/tests_config.yaml: ########## @@ -0,0 +1,38 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +test_1: + test_name: apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks + metrics_dataset: beam_run_inference + metrics_table: torch_inference_imagenet_results_resnet152 + project: apache-beam-testing + metric_name: mean_load_model_latency_milli_secs + labels: + - run-inference + min_runs_between_change_points: 5 Review Comment: Yes, default should be good enough. I will make a note about the optional metrics in the README file ########## sdks/python/apache_beam/testing/analyzers/perf_analysis_utils.py: ########## @@ -0,0 +1,199 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from dataclasses import asdict +from dataclasses import dataclass +import logging + +from typing import Any +from typing import Dict +from typing import List +from typing import Optional +from typing import Tuple +from typing import Union + +import pandas as pd +import yaml +from google.api_core import exceptions + +from apache_beam.testing.analyzers import constants +from apache_beam.testing.analyzers.github_issues_utils import get_issue_description +from apache_beam.testing.analyzers.github_issues_utils import report_change_point_on_issues +from apache_beam.testing.load_tests import load_test_metrics_utils +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsFetcher +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsPublisher +from signal_processing_algorithms.energy_statistics.energy_statistics import e_divisive + + +@dataclass +class GitHubIssueMetaData: + """ + This class holds metadata that needs to be published to the + BigQuery when a GitHub issue is created on a performance + alert. + """ + issue_timestamp: pd.Timestamp + change_point_timestamp: pd.Timestamp + test_name: str + metric_name: str + issue_number: int + issue_url: str + test_id: str + change_point: float + + +def is_change_point_in_valid_window( + num_runs_in_change_point_window: int, change_point_index: int) -> bool: + # If the change point is more than N runs behind the most recent run, + # Ignore the change point and don't raise an alert for it. + return num_runs_in_change_point_window >= change_point_index + + +def get_existing_issues_data( + test_name: str, big_query_metrics_fetcher: BigQueryMetricsFetcher +) -> Optional[pd.DataFrame]: + """ + Finds the most recent GitHub issue created for the test_name. + If no table found with name=test_name, return (None, None) + else return latest created issue_number along with + """ + query = f""" + SELECT * FROM {constants._BQ_PROJECT_NAME}.{constants._BQ_DATASET}.{test_name} + ORDER BY {constants._ISSUE_CREATION_TIMESTAMP_LABEL} DESC + LIMIT 10 + """ + try: + df = big_query_metrics_fetcher.fetch(query=query) + except exceptions.NotFound: + # If no table found, that means this is first performance regression + # on the current test+metric. + return None + return df + + +def is_perf_alert( + previous_change_point_timestamps: List[pd.Timestamp], + change_point_index: int, + timestamps: List[pd.Timestamp], + min_runs_between_change_points: int) -> bool: + """ + Search the previous_change_point_timestamps with current observed + change point sibling window and determine if it is a duplicate + change point or not. + + Return False if the current observed change point is a duplicate of + already reported change points else return True. + """ + sibling_change_point_min_timestamp = timestamps[min( + change_point_index + min_runs_between_change_points, len(timestamps) - 1)] + sibling_change_point_max_timestamp = timestamps[max( + 0, change_point_index - min_runs_between_change_points)] + # Search a list of previous change point timestamps and compare it with + # current change point timestamp. We do this in case, if a current change + # point is already reported in the past. + for previous_change_point_timestamp in previous_change_point_timestamps: + if (sibling_change_point_min_timestamp <= previous_change_point_timestamp <= + sibling_change_point_max_timestamp): + return False + return True + + +def read_test_config(config_file_path: str) -> Dict: + """ + Reads the config file in which the data required to + run the change point analysis is specified. + """ + with open(config_file_path, 'r') as stream: + config = yaml.safe_load(stream) + return config + + +def validate_config(keys): + return constants._PERF_TEST_KEYS.issubset(keys) + + +def fetch_metric_data( + params: Dict[str, Any], big_query_metrics_fetcher: BigQueryMetricsFetcher +) -> Tuple[List[Union[int, float]], List[pd.Timestamp]]: + query = f""" + SELECT * + FROM {params['project']}.{params['metrics_dataset']}.{params['metrics_table']} + WHERE CONTAINS_SUBSTR(({load_test_metrics_utils.METRICS_TYPE_LABEL}), '{params['metric_name']}') + ORDER BY {load_test_metrics_utils.SUBMIT_TIMESTAMP_LABEL} DESC + LIMIT {constants._NUM_DATA_POINTS_TO_RUN_CHANGE_POINT_ANALYSIS} + """ + metric_data: pd.DataFrame = big_query_metrics_fetcher.fetch(query=query) + return ( + metric_data[load_test_metrics_utils.VALUE_LABEL], + metric_data[load_test_metrics_utils.SUBMIT_TIMESTAMP_LABEL]) + + +def find_latest_change_point_index(metric_values: List[Union[float, int]]): + change_points_idx = e_divisive(metric_values) + if not change_points_idx: + return None + # Consider the latest change point. Review Comment: You are right. This confuses a users. I changed metric_values and timestamps to be sorted based on timestamps. ########## sdks/python/apache_beam/testing/analyzers/perf_analysis_utils.py: ########## @@ -0,0 +1,199 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from dataclasses import asdict +from dataclasses import dataclass +import logging + +from typing import Any +from typing import Dict +from typing import List +from typing import Optional +from typing import Tuple +from typing import Union + +import pandas as pd +import yaml +from google.api_core import exceptions + +from apache_beam.testing.analyzers import constants +from apache_beam.testing.analyzers.github_issues_utils import get_issue_description +from apache_beam.testing.analyzers.github_issues_utils import report_change_point_on_issues +from apache_beam.testing.load_tests import load_test_metrics_utils +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsFetcher +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsPublisher +from signal_processing_algorithms.energy_statistics.energy_statistics import e_divisive + + +@dataclass +class GitHubIssueMetaData: + """ + This class holds metadata that needs to be published to the + BigQuery when a GitHub issue is created on a performance + alert. + """ + issue_timestamp: pd.Timestamp + change_point_timestamp: pd.Timestamp + test_name: str + metric_name: str + issue_number: int + issue_url: str + test_id: str + change_point: float + + +def is_change_point_in_valid_window( + num_runs_in_change_point_window: int, change_point_index: int) -> bool: + # If the change point is more than N runs behind the most recent run, + # Ignore the change point and don't raise an alert for it. Review Comment: Removed it ########## sdks/python/apache_beam/testing/analyzers/github_issues_utils.py: ########## @@ -0,0 +1,187 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import json +import logging +import os +from typing import List +from typing import Optional +from typing import Tuple + +import pandas as pd +import requests + +try: + _GITHUB_TOKEN: Optional[str] = os.environ['GITHUB_TOKEN'] +except KeyError as e: + _GITHUB_TOKEN = None + logging.warning( + 'A Github Personal Access token is required ' + 'to create Github Issues.') + +# TODO: Change the REPO owner name to apache before merging. +_BEAM_GITHUB_REPO_OWNER = 'AnandInguva' +_BEAM_GITHUB_REPO_NAME = 'beam' +# Adding GitHub Rest API version to the header to maintain version stability. +# For more information, please look at +# https://github.blog/2022-11-28-to-infinity-and-beyond-enabling-the-future-of-githubs-rest-api-with-api-versioning/ # pylint: disable=line-too-long +_HEADERS = { + "Authorization": 'token {}'.format(_GITHUB_TOKEN), + "Accept": "application/vnd.github+json", + "X-GitHub-Api-Version": "2022-11-28" +} + +# Fill the GitHub issue description with the below variables. +_ISSUE_DESCRIPTION_HEADER = """ + Affected metric: `{}` +""" +_METRIC_INFO = "timestamp: {}, metric_value: `{}`" +_AWAITING_TRIAGE_LABEL = 'awaiting triage' +_PERF_ALERT_LABEL = 'perf-alert' + + +def create_issue( + title: str, + description: str, + labels: Optional[List[str]] = None, +) -> Tuple[int, str]: + """ + Create an issue with title, description with a label. + + Args: + title: GitHub issue title. + description: GitHub issue description. + labels: Labels used to tag the GitHub issue. + Returns: + Tuple containing GitHub issue number and issue URL. + """ + url = "https://api.github.com/repos/{}/{}/issues".format( + _BEAM_GITHUB_REPO_OWNER, _BEAM_GITHUB_REPO_NAME) + data = { + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'title': title, + 'body': description, + 'labels': [_AWAITING_TRIAGE_LABEL, _PERF_ALERT_LABEL] + } + if labels: + data['labels'] += labels + response = requests.post( + url=url, data=json.dumps(data), headers=_HEADERS).json() + return response['number'], response['html_url'] + + +def comment_on_issue(issue_number: int, + comment_description: str) -> Tuple[bool, Optional[str]]: + """ + This method looks for an issue with provided issue_number. If an open + issue is found, comment on the open issue with provided description else + do nothing. + + Args: + issue_number: A GitHub issue number. + comment_description: If an issue with issue_number is open, + then comment on the issue with the using comment_description. + Returns: + Boolean, indicating a comment was added to issue, and URL directing to + the comment. + """ + url = 'https://api.github.com/repos/{}/{}/issues/{}'.format( + _BEAM_GITHUB_REPO_OWNER, _BEAM_GITHUB_REPO_NAME, issue_number) + open_issue_response = requests.get( + url, + json.dumps({ + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'issue_number': issue_number + }), + headers=_HEADERS).json() + if open_issue_response['state'] == 'open': + data = { + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'body': comment_description, + issue_number: issue_number, + } + response = requests.post( + open_issue_response['comments_url'], json.dumps(data), headers=_HEADERS) + return True, response.json()['html_url'] + return False, None + + +def add_awaiting_triage_label_to_issue(issue_number: int): + url = 'https://api.github.com/repos/{}/{}/issues/{}/labels'.format( + _BEAM_GITHUB_REPO_OWNER, _BEAM_GITHUB_REPO_NAME, issue_number) + requests.post( + url, json.dumps({'labels': [_AWAITING_TRIAGE_LABEL]}), headers=_HEADERS) + + +def get_issue_description( + metric_name: str, + timestamps: List[pd.Timestamp], Review Comment: Done ########## sdks/python/apache_beam/testing/analyzers/github_issues_utils.py: ########## @@ -0,0 +1,187 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +import json +import logging +import os +from typing import List +from typing import Optional +from typing import Tuple + +import pandas as pd +import requests + +try: + _GITHUB_TOKEN: Optional[str] = os.environ['GITHUB_TOKEN'] +except KeyError as e: + _GITHUB_TOKEN = None + logging.warning( + 'A Github Personal Access token is required ' + 'to create Github Issues.') + +# TODO: Change the REPO owner name to apache before merging. +_BEAM_GITHUB_REPO_OWNER = 'AnandInguva' +_BEAM_GITHUB_REPO_NAME = 'beam' +# Adding GitHub Rest API version to the header to maintain version stability. +# For more information, please look at +# https://github.blog/2022-11-28-to-infinity-and-beyond-enabling-the-future-of-githubs-rest-api-with-api-versioning/ # pylint: disable=line-too-long +_HEADERS = { + "Authorization": 'token {}'.format(_GITHUB_TOKEN), + "Accept": "application/vnd.github+json", + "X-GitHub-Api-Version": "2022-11-28" +} + +# Fill the GitHub issue description with the below variables. +_ISSUE_DESCRIPTION_HEADER = """ + Affected metric: `{}` +""" +_METRIC_INFO = "timestamp: {}, metric_value: `{}`" +_AWAITING_TRIAGE_LABEL = 'awaiting triage' +_PERF_ALERT_LABEL = 'perf-alert' + + +def create_issue( + title: str, + description: str, + labels: Optional[List[str]] = None, +) -> Tuple[int, str]: + """ + Create an issue with title, description with a label. + + Args: + title: GitHub issue title. + description: GitHub issue description. + labels: Labels used to tag the GitHub issue. + Returns: + Tuple containing GitHub issue number and issue URL. + """ + url = "https://api.github.com/repos/{}/{}/issues".format( + _BEAM_GITHUB_REPO_OWNER, _BEAM_GITHUB_REPO_NAME) + data = { + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'title': title, + 'body': description, + 'labels': [_AWAITING_TRIAGE_LABEL, _PERF_ALERT_LABEL] + } + if labels: + data['labels'] += labels + response = requests.post( + url=url, data=json.dumps(data), headers=_HEADERS).json() + return response['number'], response['html_url'] + + +def comment_on_issue(issue_number: int, + comment_description: str) -> Tuple[bool, Optional[str]]: + """ + This method looks for an issue with provided issue_number. If an open + issue is found, comment on the open issue with provided description else + do nothing. + + Args: + issue_number: A GitHub issue number. + comment_description: If an issue with issue_number is open, + then comment on the issue with the using comment_description. + Returns: + Boolean, indicating a comment was added to issue, and URL directing to + the comment. + """ + url = 'https://api.github.com/repos/{}/{}/issues/{}'.format( + _BEAM_GITHUB_REPO_OWNER, _BEAM_GITHUB_REPO_NAME, issue_number) + open_issue_response = requests.get( + url, + json.dumps({ + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'issue_number': issue_number + }), + headers=_HEADERS).json() + if open_issue_response['state'] == 'open': + data = { + 'owner': _BEAM_GITHUB_REPO_OWNER, + 'repo': _BEAM_GITHUB_REPO_NAME, + 'body': comment_description, + issue_number: issue_number, + } + response = requests.post( + open_issue_response['comments_url'], json.dumps(data), headers=_HEADERS) + return True, response.json()['html_url'] + return False, None + + +def add_awaiting_triage_label_to_issue(issue_number: int): Review Comment: Makes sense. ########## sdks/python/apache_beam/testing/analyzers/perf_analysis_utils.py: ########## @@ -0,0 +1,199 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from dataclasses import asdict +from dataclasses import dataclass +import logging + +from typing import Any +from typing import Dict +from typing import List +from typing import Optional +from typing import Tuple +from typing import Union + +import pandas as pd +import yaml +from google.api_core import exceptions + +from apache_beam.testing.analyzers import constants +from apache_beam.testing.analyzers.github_issues_utils import get_issue_description +from apache_beam.testing.analyzers.github_issues_utils import report_change_point_on_issues +from apache_beam.testing.load_tests import load_test_metrics_utils +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsFetcher +from apache_beam.testing.load_tests.load_test_metrics_utils import BigQueryMetricsPublisher +from signal_processing_algorithms.energy_statistics.energy_statistics import e_divisive + + +@dataclass +class GitHubIssueMetaData: + """ + This class holds metadata that needs to be published to the + BigQuery when a GitHub issue is created on a performance + alert. + """ + issue_timestamp: pd.Timestamp + change_point_timestamp: pd.Timestamp + test_name: str + metric_name: str + issue_number: int + issue_url: str + test_id: str + change_point: float + + +def is_change_point_in_valid_window( + num_runs_in_change_point_window: int, change_point_index: int) -> bool: + # If the change point is more than N runs behind the most recent run, + # Ignore the change point and don't raise an alert for it. + return num_runs_in_change_point_window >= change_point_index + + +def get_existing_issues_data( + test_name: str, big_query_metrics_fetcher: BigQueryMetricsFetcher +) -> Optional[pd.DataFrame]: + """ + Finds the most recent GitHub issue created for the test_name. + If no table found with name=test_name, return (None, None) + else return latest created issue_number along with + """ + query = f""" + SELECT * FROM {constants._BQ_PROJECT_NAME}.{constants._BQ_DATASET}.{test_name} + ORDER BY {constants._ISSUE_CREATION_TIMESTAMP_LABEL} DESC + LIMIT 10 + """ + try: + df = big_query_metrics_fetcher.fetch(query=query) + except exceptions.NotFound: + # If no table found, that means this is first performance regression + # on the current test+metric. + return None + return df + + +def is_perf_alert( + previous_change_point_timestamps: List[pd.Timestamp], + change_point_index: int, + timestamps: List[pd.Timestamp], Review Comment: I will change timestamps ordered in ascending order everywhere. -- This is an automated message from the Apache Git Service. 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