#!/usr/bin/env python # Copyright 2015 gRPC authors. # # Licensed 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. """Detect new flakes and create issues for them""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import datetime import json import logging import os import pprint import sys import urllib import urllib2 from collections import namedtuple gcp_utils_dir = os.path.abspath( os.path.join(os.path.dirname(__file__), '../gcp/utils')) sys.path.append(gcp_utils_dir) import big_query_utils GH_ISSUE_CREATION_URL = 'https://api.github.com/repos/grpc/grpc/issues' GH_ISSUE_SEARCH_URL = 'https://api.github.com/search/issues' KOKORO_BASE_URL = 'https://kokoro2.corp.google.com/job/' def gh(url, data=None): request = urllib2.Request(url, data=data) assert TOKEN request.add_header('Authorization', 'token {}'.format(TOKEN)) if data: request.add_header('Content-type', 'application/json') response = urllib2.urlopen(request) if 200 <= response.getcode() < 300: return json.loads(response.read()) else: raise ValueError('Error ({}) accessing {}'.format( response.getcode(), response.geturl())) def search_gh_issues(search_term, status='open'): params = ' '.join((search_term, 'is:issue', 'is:open', 'repo:grpc/grpc')) qargs = urllib.urlencode({'q': params}) url = '?'.join((GH_ISSUE_SEARCH_URL, qargs)) response = gh(url) return response def create_gh_issue(title, body, labels, assignees=[]): params = {'title': title, 'body': body, 'labels': labels} if assignees: params['assignees'] = assignees data = json.dumps(params) response = gh(GH_ISSUE_CREATION_URL, data) issue_url = response['html_url'] print('Created issue {} for {}'.format(issue_url, title)) def build_kokoro_url(job_name, build_id): job_path = '{}/{}'.format('/job/'.join(job_name.split('/')), build_id) return KOKORO_BASE_URL + job_path def create_issues(new_flakes, always_create): for test_name, results_row in new_flakes.items(): poll_strategy, job_name, build_id, timestamp = results_row # TODO(dgq): the Kokoro URL has a limited lifetime. The permanent and ideal # URL would be the sponge one, but there's currently no easy way to retrieve # it. url = build_kokoro_url(job_name, build_id) title = 'New Failure: ' + test_name body = '- Test: {}\n- Poll Strategy: {}\n- URL: {}'.format( test_name, poll_strategy, url) labels = ['infra/New Failure'] if always_create: proceed = True else: preexisting_issues = search_gh_issues(test_name) if preexisting_issues['total_count'] > 0: print('\nFound {} issues for "{}":'.format( preexisting_issues['total_count'], test_name)) for issue in preexisting_issues['items']: print('\t"{}" ; URL: {}'.format(issue['title'], issue['html_url'])) else: print( '\nNo preexisting issues found for "{}"'.format(test_name)) proceed = raw_input( 'Create issue for:\nTitle: {}\nBody: {}\n[Y/n] '.format( title, body)) in ('y', 'Y', '') if proceed: assignees_str = raw_input( 'Asignees? (comma-separated, leave blank for unassigned): ') assignees = [ assignee.strip() for assignee in assignees_str.split(',') ] create_gh_issue(title, body, labels, assignees) def print_table(table, format): first_time = True for test_name, results_row in table.items(): poll_strategy, job_name, build_id, timestamp = results_row full_kokoro_url = build_kokoro_url(job_name, build_id) if format == 'human': print("\t- Test: {}, Polling: {}, Timestamp: {}, url: {}".format( test_name, poll_strategy, timestamp, full_kokoro_url)) else: assert (format == 'csv') if first_time: print('test,timestamp,url') first_time = False print("{},{},{}".format(test_name, timestamp, full_kokoro_url)) Row = namedtuple('Row', ['poll_strategy', 'job_name', 'build_id', 'timestamp']) def get_new_failures(dates): bq = big_query_utils.create_big_query() this_script_path = os.path.join(os.path.dirname(__file__)) sql_script = os.path.join(this_script_path, 'sql/new_failures_24h.sql') with open(sql_script) as query_file: query = query_file.read().format( calibration_begin=dates['calibration']['begin'], calibration_end=dates['calibration']['end'], reporting_begin=dates['reporting']['begin'], reporting_end=dates['reporting']['end']) logging.debug("Query:\n%s", query) query_job = big_query_utils.sync_query_job(bq, 'grpc-testing', query) page = bq.jobs().getQueryResults( pageToken=None, **query_job['jobReference']).execute(num_retries=3) rows = page.get('rows') if rows: return { row['f'][0]['v']: Row(poll_strategy=row['f'][1]['v'], job_name=row['f'][2]['v'], build_id=row['f'][3]['v'], timestamp=row['f'][4]['v']) for row in rows } else: return {} def parse_isodate(date_str): return datetime.datetime.strptime(date_str, "%Y-%m-%d").date() def get_new_flakes(args): """The from_date_str argument marks the beginning of the "calibration", used to establish the set of pre-existing flakes, which extends over "calibration_days". After the calibration period, "reporting_days" is the length of time during which new flakes will be reported. from date |--------------------|---------------| ^____________________^_______________^ calibration reporting days days """ dates = process_date_args(args) new_failures = get_new_failures(dates) logging.info('|new failures| = %d', len(new_failures)) return new_failures def build_args_parser(): import argparse, datetime parser = argparse.ArgumentParser() today = datetime.date.today() a_week_ago = today - datetime.timedelta(days=7) parser.add_argument( '--calibration_days', type=int, default=7, help='How many days to consider for pre-existing flakes.') parser.add_argument( '--reporting_days', type=int, default=1, help='How many days to consider for the detection of new flakes.') parser.add_argument('--count_only', dest='count_only', action='store_true', help='Display only number of new flakes.') parser.set_defaults(count_only=False) parser.add_argument('--create_issues', dest='create_issues', action='store_true', help='Create issues for all new flakes.') parser.set_defaults(create_issues=False) parser.add_argument( '--always_create_issues', dest='always_create_issues', action='store_true', help='Always create issues for all new flakes. Otherwise,' ' interactively prompt for every issue.') parser.set_defaults(always_create_issues=False) parser.add_argument( '--token', type=str, default='', help='GitHub token to use its API with a higher rate limit') parser.add_argument('--format', type=str, choices=['human', 'csv'], default='human', help='Output format: are you a human or a machine?') parser.add_argument( '--loglevel', type=str, choices=['INFO', 'DEBUG', 'WARNING', 'ERROR', 'CRITICAL'], default='WARNING', help='Logging level.') return parser def process_date_args(args): calibration_begin = (datetime.date.today() - datetime.timedelta(days=args.calibration_days) - datetime.timedelta(days=args.reporting_days)) calibration_end = calibration_begin + datetime.timedelta( days=args.calibration_days) reporting_begin = calibration_end reporting_end = reporting_begin + datetime.timedelta( days=args.reporting_days) return { 'calibration': { 'begin': calibration_begin, 'end': calibration_end }, 'reporting': { 'begin': reporting_begin, 'end': reporting_end } } def main(): global TOKEN args_parser = build_args_parser() args = args_parser.parse_args() if args.create_issues and not args.token: raise ValueError( 'Missing --token argument, needed to create GitHub issues') TOKEN = args.token logging_level = getattr(logging, args.loglevel) logging.basicConfig(format='%(asctime)s %(message)s', level=logging_level) new_flakes = get_new_flakes(args) dates = process_date_args(args) dates_info_string = 'from {} until {} (calibrated from {} until {})'.format( dates['reporting']['begin'].isoformat(), dates['reporting']['end'].isoformat(), dates['calibration']['begin'].isoformat(), dates['calibration']['end'].isoformat()) if args.format == 'human': if args.count_only: print(len(new_flakes), dates_info_string) elif new_flakes: found_msg = 'Found {} new flakes {}'.format(len(new_flakes), dates_info_string) print(found_msg) print('*' * len(found_msg)) print_table(new_flakes, 'human') if args.create_issues: create_issues(new_flakes, args.always_create_issues) else: print('No new flakes found '.format(len(new_flakes)), dates_info_string) elif args.format == 'csv': if args.count_only: print('from_date,to_date,count') print('{},{},{}'.format(dates['reporting']['begin'].isoformat(), dates['reporting']['end'].isoformat(), len(new_flakes))) else: print_table(new_flakes, 'csv') else: raise ValueError('Invalid argument for --format: {}'.format( args.format)) if __name__ == '__main__': main()