|
| 1 | +#!/usr/bin/env python3 |
| 2 | + |
| 3 | +import argparse |
| 4 | +import json |
| 5 | +import sys |
| 6 | +import time |
| 7 | + |
| 8 | +from slack_sdk import WebClient |
| 9 | +from slack_sdk.errors import SlackApiError |
| 10 | + |
| 11 | +sys.path.insert(0, sys.path[0] + "/..") |
| 12 | +from open_search_db import OpenSearchDB |
| 13 | + |
| 14 | +QUERY_LOOKBACK_DAYS = 90 |
| 15 | +MAX_QUERY_SIZE = 3000 |
| 16 | +MAX_TEST_CASES_PER_MSG = 5 |
| 17 | +POST_SLACK_MSG_RETRY_TIMES = 5 |
| 18 | + |
| 19 | + |
| 20 | +def query_regression_data(project_name): |
| 21 | + """Query regression data from OpenSearch database.""" |
| 22 | + last_days = QUERY_LOOKBACK_DAYS |
| 23 | + |
| 24 | + must_clauses = [ |
| 25 | + {"term": {"b_is_valid": True}}, |
| 26 | + {"term": {"b_is_post_merge": True}}, |
| 27 | + {"term": {"b_is_regression": True}}, |
| 28 | + {"term": {"b_is_baseline": False}}, |
| 29 | + { |
| 30 | + "range": { |
| 31 | + "ts_created": { |
| 32 | + "gte": int(time.time() - 24 * 3600 * last_days) |
| 33 | + // (24 * 3600) |
| 34 | + * 24 |
| 35 | + * 3600 |
| 36 | + * 1000, |
| 37 | + } |
| 38 | + } |
| 39 | + }, |
| 40 | + ] |
| 41 | + |
| 42 | + json_data = { |
| 43 | + "query": { |
| 44 | + "bool": {"must": must_clauses}, |
| 45 | + }, |
| 46 | + "size": MAX_QUERY_SIZE, |
| 47 | + } |
| 48 | + json_data = json.dumps(json_data) |
| 49 | + |
| 50 | + data_list = [] |
| 51 | + try: |
| 52 | + res = OpenSearchDB.queryFromOpenSearchDB(json_data, project_name) |
| 53 | + if res is None: |
| 54 | + print(f"Failed to query from {project_name}, returned no response") |
| 55 | + return None |
| 56 | + payload = res.json().get("hits", {}).get("hits", []) |
| 57 | + if len(payload) == 0: |
| 58 | + print(f"No regression data found in {project_name}, returned empty list") |
| 59 | + return [] |
| 60 | + for hit in payload: |
| 61 | + data_dict = hit.get("_source", {}) |
| 62 | + data_dict["_id"] = hit.get("_id", "") |
| 63 | + if data_dict["_id"] == "": |
| 64 | + print(f"Failed to query from {project_name}, returned data with no _id") |
| 65 | + return None |
| 66 | + data_list.append(data_dict) |
| 67 | + print(f"Successfully queried from {project_name}, queried {len(data_list)} entries") |
| 68 | + return data_list |
| 69 | + except Exception as e: |
| 70 | + print(f"Failed to query from {project_name}, returned error: {e}") |
| 71 | + return None |
| 72 | + |
| 73 | + |
| 74 | +def get_regression_data_by_job_id(data_list, query_job_number): |
| 75 | + """Returns a dict with job_id as key and list of regression data as value. |
| 76 | +
|
| 77 | + Only returns the latest query_job_number jobs. |
| 78 | + """ |
| 79 | + if data_list is None or len(data_list) == 0: |
| 80 | + return {} |
| 81 | + |
| 82 | + # Group data by job_id |
| 83 | + job_data_dict = {} |
| 84 | + for data in data_list: |
| 85 | + job_id = data.get("s_job_id", "") |
| 86 | + if job_id == "": |
| 87 | + continue |
| 88 | + if job_id not in job_data_dict: |
| 89 | + job_data_dict[job_id] = [] |
| 90 | + job_data_dict[job_id].append(data) |
| 91 | + |
| 92 | + # Sort job_ids by the latest ts_created in each group (descending) |
| 93 | + def get_latest_timestamp(job_id): |
| 94 | + timestamps = [d.get("ts_created", 0) for d in job_data_dict[job_id]] |
| 95 | + return max(timestamps) if timestamps else 0 |
| 96 | + |
| 97 | + sorted_job_ids = sorted(job_data_dict.keys(), key=get_latest_timestamp, reverse=True) |
| 98 | + |
| 99 | + # Only keep the latest query_job_number jobs |
| 100 | + latest_job_ids = sorted_job_ids[:query_job_number] |
| 101 | + |
| 102 | + result = {} |
| 103 | + for job_id in latest_job_ids: |
| 104 | + result[job_id] = job_data_dict[job_id] |
| 105 | + |
| 106 | + return result |
| 107 | + |
| 108 | + |
| 109 | +def process_regression_message(regression_dict): |
| 110 | + """Process regression data into message chunks. |
| 111 | +
|
| 112 | + Returns a list of messages, each containing at most MAX_TEST_CASES_PER_MSG test cases. |
| 113 | + """ |
| 114 | + if not regression_dict: |
| 115 | + return [] |
| 116 | + |
| 117 | + # Flatten all test cases into a list with (job_id, idx, data) tuples |
| 118 | + all_test_cases = [] |
| 119 | + for job_id, data_list in regression_dict.items(): |
| 120 | + sorted_data_list = sorted(data_list, key=lambda x: x.get("s_test_case_name", "")) |
| 121 | + for idx, data in enumerate(sorted_data_list, start=1): |
| 122 | + all_test_cases.append((job_id, idx, data)) |
| 123 | + |
| 124 | + # Split into chunks of MAX_TEST_CASES_PER_MSG |
| 125 | + chunks = [] |
| 126 | + for i in range(0, len(all_test_cases), MAX_TEST_CASES_PER_MSG): |
| 127 | + chunks.append(all_test_cases[i : i + MAX_TEST_CASES_PER_MSG]) |
| 128 | + |
| 129 | + # Build messages for each chunk |
| 130 | + messages = [] |
| 131 | + for chunk in chunks: |
| 132 | + msg_parts = [] |
| 133 | + current_job_id = None |
| 134 | + for job_id, idx, data in chunk: |
| 135 | + # Add job header when switching to a new job_id |
| 136 | + if job_id != current_job_id: |
| 137 | + if msg_parts: |
| 138 | + msg_parts.append("\n") |
| 139 | + job_header = f"*LLM/main/L0_PostMerge/{job_id}:*\n" |
| 140 | + msg_parts.append(job_header) |
| 141 | + current_job_id = job_id |
| 142 | + |
| 143 | + test_case_name = data.get("s_test_case_name", "N/A") |
| 144 | + regression_info = data.get("s_regression_info", "N/A") |
| 145 | + msg_parts.append(f"*REGRESSION TEST CASE {idx}: {test_case_name}*\n") |
| 146 | + for part in regression_info.split(","): |
| 147 | + part = part.strip() |
| 148 | + if part and "baseline_id" not in part: |
| 149 | + msg_parts.append(f" {part}\n") |
| 150 | + |
| 151 | + msg = "".join(msg_parts).strip() |
| 152 | + messages.append(msg) |
| 153 | + |
| 154 | + return messages |
| 155 | + |
| 156 | + |
| 157 | +def send_regression_message(messages, channel_id, bot_token): |
| 158 | + """Send regression messages to Slack channel(s). |
| 159 | +
|
| 160 | + channel_id can be a single ID or multiple IDs separated by commas. |
| 161 | + """ |
| 162 | + if not messages: |
| 163 | + print("No regression data to send") |
| 164 | + return |
| 165 | + |
| 166 | + if channel_id and bot_token: |
| 167 | + channel_ids = [cid.strip() for cid in channel_id.split(",") if cid.strip()] |
| 168 | + for cid in channel_ids: |
| 169 | + for msg in messages: |
| 170 | + send_message(msg, cid, bot_token) |
| 171 | + else: |
| 172 | + print("Slack channel_id or bot_token not provided, printing message:") |
| 173 | + for i, msg in enumerate(messages, start=1): |
| 174 | + print(f"--- Message {i} ---") |
| 175 | + print(msg) |
| 176 | + |
| 177 | + |
| 178 | +def send_message(msg, channel_id, bot_token): |
| 179 | + """Send message to Slack channel using slack_sdk.""" |
| 180 | + client = WebClient(token=bot_token) |
| 181 | + |
| 182 | + attachments = [ |
| 183 | + { |
| 184 | + "title": "Perf Sanity Regression Report", |
| 185 | + "color": "#ff0000", |
| 186 | + "text": msg, |
| 187 | + } |
| 188 | + ] |
| 189 | + |
| 190 | + for attempt in range(1, POST_SLACK_MSG_RETRY_TIMES + 1): |
| 191 | + try: |
| 192 | + result = client.chat_postMessage( |
| 193 | + channel=channel_id, |
| 194 | + attachments=attachments, |
| 195 | + ) |
| 196 | + assert result["ok"] is True, json.dumps(result.data) |
| 197 | + print(f"Message sent successfully to channel {channel_id}") |
| 198 | + return |
| 199 | + except SlackApiError as e: |
| 200 | + print( |
| 201 | + f"Attempt {attempt}/{POST_SLACK_MSG_RETRY_TIMES}: Error sending message to Slack: {e}" |
| 202 | + ) |
| 203 | + except Exception as e: |
| 204 | + print(f"Attempt {attempt}/{POST_SLACK_MSG_RETRY_TIMES}: Unexpected error: {e}") |
| 205 | + |
| 206 | + if attempt < POST_SLACK_MSG_RETRY_TIMES: |
| 207 | + time.sleep(1) |
| 208 | + |
| 209 | + print( |
| 210 | + f"Failed to send message to channel {channel_id} after {POST_SLACK_MSG_RETRY_TIMES} attempts" |
| 211 | + ) |
| 212 | + |
| 213 | + |
| 214 | +def main(): |
| 215 | + parser = argparse.ArgumentParser(description="Perf Sanity Triage Script") |
| 216 | + parser.add_argument("--project_name", type=str, required=True, help="OpenSearch project name") |
| 217 | + parser.add_argument("--operation", type=str, required=True, help="Operation to perform") |
| 218 | + parser.add_argument( |
| 219 | + "--channel_id", |
| 220 | + type=str, |
| 221 | + default="", |
| 222 | + help="Slack channel ID(s), comma-separated for multiple channels", |
| 223 | + ) |
| 224 | + parser.add_argument("--bot_token", type=str, default="", help="Slack bot token") |
| 225 | + parser.add_argument( |
| 226 | + "--query_job_number", type=int, default=1, help="Number of latest jobs to query" |
| 227 | + ) |
| 228 | + |
| 229 | + args = parser.parse_args() |
| 230 | + |
| 231 | + print(f"Project Name: {args.project_name}") |
| 232 | + print(f"Operation: {args.operation}") |
| 233 | + print(f"Channel ID: {args.channel_id}") |
| 234 | + print(f"Bot Token: {'***' if args.bot_token else 'Not provided'}") |
| 235 | + print(f"Query Job Number: {args.query_job_number}") |
| 236 | + |
| 237 | + if args.operation == "SLACK BOT SENDS MESSAGE": |
| 238 | + data_list = query_regression_data(args.project_name) |
| 239 | + if data_list is None: |
| 240 | + print("Failed to query regression data") |
| 241 | + return |
| 242 | + |
| 243 | + regression_dict = get_regression_data_by_job_id(data_list, args.query_job_number) |
| 244 | + messages = process_regression_message(regression_dict) |
| 245 | + send_regression_message(messages, args.channel_id, args.bot_token) |
| 246 | + else: |
| 247 | + print(f"Unknown operation: {args.operation}") |
| 248 | + |
| 249 | + |
| 250 | +if __name__ == "__main__": |
| 251 | + main() |
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