mirror of https://github.com/zulip/zulip.git
975 lines
38 KiB
Python
975 lines
38 KiB
Python
# Documented in https://zulip.readthedocs.io/en/latest/subsystems/queuing.html
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import base64
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import copy
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import datetime
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import email
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import email.policy
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import functools
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import logging
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import os
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import signal
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import smtplib
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import socket
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import tempfile
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import time
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import urllib
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from abc import ABC, abstractmethod
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from collections import defaultdict, deque
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from email.message import EmailMessage
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from functools import wraps
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from threading import Lock, Timer
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from types import FrameType
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from typing import (
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Any,
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Callable,
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Dict,
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List,
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Mapping,
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MutableSequence,
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Optional,
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Sequence,
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Set,
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Tuple,
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Type,
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TypeVar,
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)
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import orjson
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import sentry_sdk
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from django.conf import settings
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from django.core.mail.backends.smtp import EmailBackend
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from django.db import connection
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from django.db.models import F
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from django.utils.timezone import now as timezone_now
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from django.utils.translation import gettext as _
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from django.utils.translation import override as override_language
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from sentry_sdk import add_breadcrumb, configure_scope
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from zulip_bots.lib import extract_query_without_mention
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from zerver.context_processors import common_context
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from zerver.lib.actions import (
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do_mark_stream_messages_as_read,
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do_send_confirmation_email,
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do_update_embedded_data,
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do_update_user_activity,
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do_update_user_activity_interval,
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do_update_user_presence,
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internal_send_private_message,
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notify_realm_export,
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render_incoming_message,
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)
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from zerver.lib.bot_lib import EmbeddedBotHandler, EmbeddedBotQuitException, get_bot_handler
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from zerver.lib.context_managers import lockfile
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from zerver.lib.db import reset_queries
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from zerver.lib.digest import bulk_handle_digest_email
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from zerver.lib.email_mirror import decode_stream_email_address, is_missed_message_address
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from zerver.lib.email_mirror import process_message as mirror_email
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from zerver.lib.email_mirror import rate_limit_mirror_by_realm
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from zerver.lib.email_notifications import handle_missedmessage_emails
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from zerver.lib.error_notify import do_report_error
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from zerver.lib.exceptions import RateLimited
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from zerver.lib.export import export_realm_wrapper
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from zerver.lib.outgoing_webhook import do_rest_call, get_outgoing_webhook_service_handler
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from zerver.lib.push_notifications import (
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clear_push_device_tokens,
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handle_push_notification,
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handle_remove_push_notification,
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initialize_push_notifications,
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)
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from zerver.lib.pysa import mark_sanitized
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from zerver.lib.queue import SimpleQueueClient, retry_event
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from zerver.lib.remote_server import PushNotificationBouncerRetryLaterError
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from zerver.lib.send_email import (
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EmailNotDeliveredException,
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FromAddress,
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handle_send_email_format_changes,
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initialize_connection,
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send_email,
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send_future_email,
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)
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from zerver.lib.timestamp import timestamp_to_datetime
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from zerver.lib.url_preview import preview as url_preview
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from zerver.models import (
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Message,
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PreregistrationUser,
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Realm,
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RealmAuditLog,
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UserMessage,
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UserProfile,
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filter_to_valid_prereg_users,
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flush_per_request_caches,
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get_bot_services,
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get_client,
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get_system_bot,
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get_user_profile_by_id,
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)
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logger = logging.getLogger(__name__)
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class WorkerTimeoutException(Exception):
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def __init__(self, limit: int, event_count: int) -> None:
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self.limit = limit
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self.event_count = event_count
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def __str__(self) -> str:
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return f"Timed out after {self.limit * self.event_count} seconds processing {self.event_count} events"
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class WorkerDeclarationException(Exception):
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pass
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ConcreteQueueWorker = TypeVar("ConcreteQueueWorker", bound="QueueProcessingWorker")
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def assign_queue(
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queue_name: str,
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enabled: bool = True,
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is_test_queue: bool = False,
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) -> Callable[[Type[ConcreteQueueWorker]], Type[ConcreteQueueWorker]]:
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def decorate(clazz: Type[ConcreteQueueWorker]) -> Type[ConcreteQueueWorker]:
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clazz.queue_name = queue_name
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if enabled:
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register_worker(queue_name, clazz, is_test_queue)
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return clazz
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return decorate
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worker_classes: Dict[str, Type["QueueProcessingWorker"]] = {}
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test_queues: Set[str] = set()
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def register_worker(
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queue_name: str, clazz: Type["QueueProcessingWorker"], is_test_queue: bool = False
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) -> None:
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worker_classes[queue_name] = clazz
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if is_test_queue:
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test_queues.add(queue_name)
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def get_worker(queue_name: str) -> "QueueProcessingWorker":
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return worker_classes[queue_name]()
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def get_active_worker_queues(only_test_queues: bool = False) -> List[str]:
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"""Returns all (either test, or real) worker queues."""
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return [
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queue_name
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for queue_name in worker_classes.keys()
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if bool(queue_name in test_queues) == only_test_queues
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]
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def check_and_send_restart_signal() -> None:
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try:
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if not connection.is_usable():
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logging.warning("*** Sending self SIGUSR1 to trigger a restart.")
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os.kill(os.getpid(), signal.SIGUSR1)
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except Exception:
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pass
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# If you change the function on which this decorator is used be careful that the new
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# function doesn't delete the "failed_tries" attribute of "data" which is needed for
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# "retry_event" to work correctly; see EmailSendingWorker for an example with deepcopy.
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def retry_send_email_failures(
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func: Callable[[ConcreteQueueWorker, Dict[str, Any]], None],
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) -> Callable[[ConcreteQueueWorker, Dict[str, Any]], None]:
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@wraps(func)
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def wrapper(worker: ConcreteQueueWorker, data: Dict[str, Any]) -> None:
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try:
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func(worker, data)
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except (
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smtplib.SMTPServerDisconnected,
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socket.gaierror,
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socket.timeout,
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EmailNotDeliveredException,
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) as e:
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error_class_name = e.__class__.__name__
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def on_failure(event: Dict[str, Any]) -> None:
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logging.exception(
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"Event %r failed due to exception %s", event, error_class_name, stack_info=True
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)
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retry_event(worker.queue_name, data, on_failure)
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return wrapper
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def timer_expired(limit: int, event_count: int, signal: int, frame: FrameType) -> None:
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raise WorkerTimeoutException(limit, event_count)
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class QueueProcessingWorker(ABC):
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queue_name: str
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MAX_CONSUME_SECONDS: Optional[int] = 30
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ENABLE_TIMEOUTS = False
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CONSUME_ITERATIONS_BEFORE_UPDATE_STATS_NUM = 50
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MAX_SECONDS_BEFORE_UPDATE_STATS = 30
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def __init__(self) -> None:
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self.q: Optional[SimpleQueueClient] = None
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if not hasattr(self, "queue_name"):
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raise WorkerDeclarationException("Queue worker declared without queue_name")
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self.initialize_statistics()
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def initialize_statistics(self) -> None:
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self.queue_last_emptied_timestamp = time.time()
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self.consumed_since_last_emptied = 0
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self.recent_consume_times: MutableSequence[Tuple[int, float]] = deque(maxlen=50)
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self.consume_iteration_counter = 0
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self.idle = True
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self.last_statistics_update_time = 0.0
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self.update_statistics(0)
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def update_statistics(self, remaining_local_queue_size: int) -> None:
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total_seconds = sum(seconds for _, seconds in self.recent_consume_times)
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total_events = sum(events_number for events_number, _ in self.recent_consume_times)
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if total_events == 0:
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recent_average_consume_time = None
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else:
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recent_average_consume_time = total_seconds / total_events
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stats_dict = dict(
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update_time=time.time(),
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recent_average_consume_time=recent_average_consume_time,
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current_queue_size=remaining_local_queue_size,
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queue_last_emptied_timestamp=self.queue_last_emptied_timestamp,
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consumed_since_last_emptied=self.consumed_since_last_emptied,
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)
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os.makedirs(settings.QUEUE_STATS_DIR, exist_ok=True)
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fname = f"{self.queue_name}.stats"
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fn = os.path.join(settings.QUEUE_STATS_DIR, fname)
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with lockfile(fn + ".lock"):
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tmp_fn = fn + ".tmp"
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with open(tmp_fn, "wb") as f:
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f.write(
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orjson.dumps(stats_dict, option=orjson.OPT_APPEND_NEWLINE | orjson.OPT_INDENT_2)
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)
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os.rename(tmp_fn, fn)
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self.last_statistics_update_time = time.time()
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def get_remaining_local_queue_size(self) -> int:
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if self.q is not None:
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return self.q.local_queue_size()
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else:
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# This is a special case that will happen if we're operating without
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# using RabbitMQ (e.g. in tests). In that case there's no queuing to speak of
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# and the only reasonable size to return is 0.
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return 0
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@abstractmethod
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def consume(self, data: Dict[str, Any]) -> None:
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pass
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def do_consume(
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self, consume_func: Callable[[List[Dict[str, Any]]], None], events: List[Dict[str, Any]]
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) -> None:
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consume_time_seconds: Optional[float] = None
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with configure_scope() as scope:
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scope.clear_breadcrumbs()
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add_breadcrumb(
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type="debug",
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category="queue_processor",
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message=f"Consuming {self.queue_name}",
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data={"events": events, "local_queue_size": self.get_remaining_local_queue_size()},
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)
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try:
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if self.idle:
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# We're reactivating after having gone idle due to emptying the queue.
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# We should update the stats file to keep it fresh and to make it clear
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# that the queue started processing, in case the event we're about to process
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# makes us freeze.
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self.idle = False
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self.update_statistics(self.get_remaining_local_queue_size())
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time_start = time.time()
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if self.MAX_CONSUME_SECONDS and self.ENABLE_TIMEOUTS:
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try:
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signal.signal(
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signal.SIGALRM,
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functools.partial(timer_expired, self.MAX_CONSUME_SECONDS, len(events)),
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)
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try:
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signal.alarm(self.MAX_CONSUME_SECONDS * len(events))
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consume_func(events)
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finally:
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signal.alarm(0)
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finally:
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signal.signal(signal.SIGALRM, signal.SIG_DFL)
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else:
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consume_func(events)
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consume_time_seconds = time.time() - time_start
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self.consumed_since_last_emptied += len(events)
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except Exception as e:
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self._handle_consume_exception(events, e)
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finally:
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flush_per_request_caches()
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reset_queries()
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if consume_time_seconds is not None:
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self.recent_consume_times.append((len(events), consume_time_seconds))
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remaining_local_queue_size = self.get_remaining_local_queue_size()
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if remaining_local_queue_size == 0:
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self.queue_last_emptied_timestamp = time.time()
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self.consumed_since_last_emptied = 0
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# We've cleared all the events from the queue, so we don't
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# need to worry about the small overhead of doing a disk write.
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# We take advantage of this to update the stats file to keep it fresh,
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# especially since the queue might go idle until new events come in.
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self.update_statistics(0)
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self.idle = True
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return
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self.consume_iteration_counter += 1
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if (
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self.consume_iteration_counter >= self.CONSUME_ITERATIONS_BEFORE_UPDATE_STATS_NUM
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or time.time() - self.last_statistics_update_time
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>= self.MAX_SECONDS_BEFORE_UPDATE_STATS
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):
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self.consume_iteration_counter = 0
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self.update_statistics(remaining_local_queue_size)
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def consume_single_event(self, event: Dict[str, Any]) -> None:
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consume_func = lambda events: self.consume(events[0])
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self.do_consume(consume_func, [event])
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def _handle_consume_exception(self, events: List[Dict[str, Any]], exception: Exception) -> None:
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with configure_scope() as scope:
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scope.set_context(
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"events",
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{
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"data": events,
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"queue_name": self.queue_name,
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},
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)
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if isinstance(exception, WorkerTimeoutException):
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with sentry_sdk.push_scope() as scope:
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scope.fingerprint = ["worker-timeout", self.queue_name]
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logging.exception(
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"%s in queue %s", str(exception), self.queue_name, stack_info=True
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)
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else:
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logging.exception(
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"Problem handling data on queue %s", self.queue_name, stack_info=True
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)
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if not os.path.exists(settings.QUEUE_ERROR_DIR):
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os.mkdir(settings.QUEUE_ERROR_DIR) # nocoverage
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# Use 'mark_sanitized' to prevent Pysa from detecting this false positive
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# flow. 'queue_name' is always a constant string.
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fname = mark_sanitized(f"{self.queue_name}.errors")
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fn = os.path.join(settings.QUEUE_ERROR_DIR, fname)
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line = f"{time.asctime()}\t{orjson.dumps(events).decode()}\n"
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lock_fn = fn + ".lock"
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with lockfile(lock_fn):
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with open(fn, "a") as f:
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f.write(line)
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check_and_send_restart_signal()
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def setup(self) -> None:
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self.q = SimpleQueueClient()
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def start(self) -> None:
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assert self.q is not None
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self.initialize_statistics()
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self.q.start_json_consumer(
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self.queue_name,
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lambda events: self.consume_single_event(events[0]),
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)
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def stop(self) -> None: # nocoverage
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assert self.q is not None
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self.q.stop_consuming()
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class LoopQueueProcessingWorker(QueueProcessingWorker):
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sleep_delay = 1
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batch_size = 100
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def start(self) -> None: # nocoverage
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assert self.q is not None
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self.initialize_statistics()
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self.q.start_json_consumer(
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self.queue_name,
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lambda events: self.do_consume(self.consume_batch, events),
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batch_size=self.batch_size,
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timeout=self.sleep_delay,
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)
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@abstractmethod
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def consume_batch(self, events: List[Dict[str, Any]]) -> None:
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pass
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def consume(self, event: Dict[str, Any]) -> None:
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"""In LoopQueueProcessingWorker, consume is used just for automated tests"""
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self.consume_batch([event])
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@assign_queue("invites")
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class ConfirmationEmailWorker(QueueProcessingWorker):
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def consume(self, data: Mapping[str, Any]) -> None:
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invitee = filter_to_valid_prereg_users(
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PreregistrationUser.objects.filter(id=data["prereg_id"])
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).first()
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if invitee is None:
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# The invitation could have been revoked
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return
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referrer = get_user_profile_by_id(data["referrer_id"])
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logger.info(
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"Sending invitation for realm %s to %s", referrer.realm.string_id, invitee.email
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)
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activate_url = do_send_confirmation_email(invitee, referrer)
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# queue invitation reminder
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if settings.INVITATION_LINK_VALIDITY_DAYS >= 4:
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context = common_context(referrer)
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context.update(
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activate_url=activate_url,
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referrer_name=referrer.full_name,
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referrer_email=referrer.delivery_email,
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referrer_realm_name=referrer.realm.name,
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)
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send_future_email(
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"zerver/emails/invitation_reminder",
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referrer.realm,
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to_emails=[invitee.email],
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from_address=FromAddress.tokenized_no_reply_placeholder,
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language=referrer.realm.default_language,
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context=context,
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delay=datetime.timedelta(days=settings.INVITATION_LINK_VALIDITY_DAYS - 2),
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)
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|
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@assign_queue("user_activity")
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class UserActivityWorker(LoopQueueProcessingWorker):
|
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"""The UserActivity queue is perhaps our highest-traffic queue, and
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requires some care to ensure it performs adequately.
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We use a LoopQueueProcessingWorker as a performance optimization
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for managing the queue. The structure of UserActivity records is
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such that they are easily deduplicated before being sent to the
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database; we take advantage of that to make this queue highly
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effective at dealing with a backlog containing many similar
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events. Such a backlog happen in a few ways:
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* In abuse/DoS situations, if a client is sending huge numbers of
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similar requests to the server.
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* If the queue ends up with several minutes of backlog e.g. due to
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downtime of the queue processor, many clients will have several
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common events from doing an action multiple times.
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"""
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client_id_map: Dict[str, int] = {}
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def start(self) -> None:
|
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# For our unit tests to make sense, we need to clear this on startup.
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self.client_id_map = {}
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super().start()
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|
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def consume_batch(self, user_activity_events: List[Dict[str, Any]]) -> None:
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uncommitted_events: Dict[Tuple[int, int, str], Tuple[int, float]] = {}
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# First, we drain the queue of all user_activity events and
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# deduplicate them for insertion into the database.
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for event in user_activity_events:
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user_profile_id = event["user_profile_id"]
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if "client_id" not in event:
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# This is for compatibility with older events still stuck in the queue,
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# that used the client name in event["client"] instead of having
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# event["client_id"] directly.
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#
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# TODO/compatibility: We can delete this once it is no
|
|
# longer possible to directly upgrade from 2.1 to master.
|
|
if event["client"] not in self.client_id_map:
|
|
client = get_client(event["client"])
|
|
self.client_id_map[event["client"]] = client.id
|
|
client_id = self.client_id_map[event["client"]]
|
|
else:
|
|
client_id = event["client_id"]
|
|
|
|
key_tuple = (user_profile_id, client_id, event["query"])
|
|
if key_tuple not in uncommitted_events:
|
|
uncommitted_events[key_tuple] = (1, event["time"])
|
|
else:
|
|
count, time = uncommitted_events[key_tuple]
|
|
uncommitted_events[key_tuple] = (count + 1, max(time, event["time"]))
|
|
|
|
# Then we insert the updates into the database.
|
|
#
|
|
# TODO: Doing these updates in sequence individually is likely
|
|
# inefficient; the idealized version would do some sort of
|
|
# bulk insert_or_update query.
|
|
for key_tuple in uncommitted_events:
|
|
(user_profile_id, client_id, query) = key_tuple
|
|
count, time = uncommitted_events[key_tuple]
|
|
log_time = timestamp_to_datetime(time)
|
|
do_update_user_activity(user_profile_id, client_id, query, count, log_time)
|
|
|
|
|
|
@assign_queue("user_activity_interval")
|
|
class UserActivityIntervalWorker(QueueProcessingWorker):
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
user_profile = get_user_profile_by_id(event["user_profile_id"])
|
|
log_time = timestamp_to_datetime(event["time"])
|
|
do_update_user_activity_interval(user_profile, log_time)
|
|
|
|
|
|
@assign_queue("user_presence")
|
|
class UserPresenceWorker(QueueProcessingWorker):
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
logging.debug("Received presence event: %s", event)
|
|
user_profile = get_user_profile_by_id(event["user_profile_id"])
|
|
client = get_client(event["client"])
|
|
log_time = timestamp_to_datetime(event["time"])
|
|
status = event["status"]
|
|
do_update_user_presence(user_profile, client, log_time, status)
|
|
|
|
|
|
@assign_queue("missedmessage_emails")
|
|
class MissedMessageWorker(QueueProcessingWorker):
|
|
# Aggregate all messages received over the last BATCH_DURATION
|
|
# seconds to let someone finish sending a batch of messages and/or
|
|
# editing them before they are sent out as emails to recipients.
|
|
#
|
|
# The timer is running whenever; we poll at most every TIMER_FREQUENCY
|
|
# seconds, to avoid excessive activity.
|
|
#
|
|
# TODO: Since this process keeps events in memory for up to 2
|
|
# minutes, it now will lose approximately BATCH_DURATION worth of
|
|
# missed_message emails whenever it is restarted as part of a
|
|
# server restart. We should probably add some sort of save/reload
|
|
# mechanism for that case.
|
|
TIMER_FREQUENCY = 5
|
|
BATCH_DURATION = 120
|
|
timer_event: Optional[Timer] = None
|
|
events_by_recipient: Dict[int, List[Dict[str, Any]]] = defaultdict(list)
|
|
batch_start_by_recipient: Dict[int, float] = {}
|
|
|
|
# This lock protects access to all of the data structures declared
|
|
# above. A lock is required because maybe_send_batched_emails, as
|
|
# the argument to Timer, runs in a separate thread from the rest
|
|
# of the consumer.
|
|
lock = Lock()
|
|
|
|
def consume(self, event: Dict[str, Any]) -> None:
|
|
with self.lock:
|
|
logging.debug("Received missedmessage_emails event: %s", event)
|
|
|
|
# When we process an event, just put it into the queue and ensure we have a timer going.
|
|
user_profile_id = event["user_profile_id"]
|
|
if user_profile_id not in self.batch_start_by_recipient:
|
|
self.batch_start_by_recipient[user_profile_id] = time.time()
|
|
self.events_by_recipient[user_profile_id].append(event)
|
|
|
|
self.ensure_timer()
|
|
|
|
def ensure_timer(self) -> None:
|
|
# The caller is responsible for ensuring self.lock is held when it calls this.
|
|
if self.timer_event is not None:
|
|
return
|
|
|
|
self.timer_event = Timer(
|
|
self.TIMER_FREQUENCY, MissedMessageWorker.maybe_send_batched_emails, [self]
|
|
)
|
|
self.timer_event.start()
|
|
|
|
def maybe_send_batched_emails(self) -> None:
|
|
with self.lock:
|
|
# self.timer_event just triggered execution of this
|
|
# function in a thread, so now that we hold the lock, we
|
|
# clear the timer_event attribute to record that no Timer
|
|
# is active.
|
|
self.timer_event = None
|
|
|
|
current_time = time.time()
|
|
for user_profile_id, timestamp in list(self.batch_start_by_recipient.items()):
|
|
if current_time - timestamp < self.BATCH_DURATION:
|
|
continue
|
|
events = self.events_by_recipient[user_profile_id]
|
|
logging.info(
|
|
"Batch-processing %s missedmessage_emails events for user %s",
|
|
len(events),
|
|
user_profile_id,
|
|
)
|
|
handle_missedmessage_emails(user_profile_id, events)
|
|
del self.events_by_recipient[user_profile_id]
|
|
del self.batch_start_by_recipient[user_profile_id]
|
|
|
|
# By only restarting the timer if there are actually events in
|
|
# the queue, we ensure this queue processor is idle when there
|
|
# are no missed-message emails to process. This avoids
|
|
# constant CPU usage when there is no work to do.
|
|
if len(self.batch_start_by_recipient) > 0:
|
|
self.ensure_timer()
|
|
|
|
|
|
@assign_queue("email_senders")
|
|
class EmailSendingWorker(LoopQueueProcessingWorker):
|
|
def __init__(self) -> None:
|
|
super().__init__()
|
|
self.connection: EmailBackend = initialize_connection(None)
|
|
|
|
@retry_send_email_failures
|
|
def send_email(self, event: Dict[str, Any]) -> None:
|
|
# Copy the event, so that we don't pass the `failed_tries'
|
|
# data to send_email (which neither takes that
|
|
# argument nor needs that data).
|
|
copied_event = copy.deepcopy(event)
|
|
if "failed_tries" in copied_event:
|
|
del copied_event["failed_tries"]
|
|
handle_send_email_format_changes(copied_event)
|
|
self.connection = initialize_connection(self.connection)
|
|
send_email(**copied_event, connection=self.connection)
|
|
|
|
def consume_batch(self, events: List[Dict[str, Any]]) -> None:
|
|
for event in events:
|
|
self.send_email(event)
|
|
|
|
def stop(self) -> None:
|
|
try:
|
|
self.connection.close()
|
|
finally:
|
|
super().stop()
|
|
|
|
|
|
@assign_queue("missedmessage_mobile_notifications")
|
|
class PushNotificationsWorker(QueueProcessingWorker): # nocoverage
|
|
def start(self) -> None:
|
|
# initialize_push_notifications doesn't strictly do anything
|
|
# beyond printing some logging warnings if push notifications
|
|
# are not available in the current configuration.
|
|
initialize_push_notifications()
|
|
super().start()
|
|
|
|
def consume(self, event: Dict[str, Any]) -> None:
|
|
try:
|
|
if event.get("type", "add") == "remove":
|
|
message_ids = event.get("message_ids")
|
|
if message_ids is None: # legacy task across an upgrade
|
|
message_ids = [event["message_id"]]
|
|
handle_remove_push_notification(event["user_profile_id"], message_ids)
|
|
else:
|
|
handle_push_notification(event["user_profile_id"], event)
|
|
except PushNotificationBouncerRetryLaterError:
|
|
|
|
def failure_processor(event: Dict[str, Any]) -> None:
|
|
logger.warning(
|
|
"Maximum retries exceeded for trigger:%s event:push_notification",
|
|
event["user_profile_id"],
|
|
)
|
|
|
|
retry_event(self.queue_name, event, failure_processor)
|
|
|
|
|
|
@assign_queue("error_reports")
|
|
class ErrorReporter(QueueProcessingWorker):
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
logging.info(
|
|
"Processing traceback with type %s for %s", event["type"], event.get("user_email")
|
|
)
|
|
if settings.ERROR_REPORTING:
|
|
do_report_error(event["type"], event["report"])
|
|
|
|
|
|
@assign_queue("digest_emails")
|
|
class DigestWorker(QueueProcessingWorker): # nocoverage
|
|
# Who gets a digest is entirely determined by the enqueue_digest_emails
|
|
# management command, not here.
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
if "user_ids" in event:
|
|
user_ids = event["user_ids"]
|
|
else:
|
|
# legacy code may have enqueued a single id
|
|
user_ids = [event["user_profile_id"]]
|
|
bulk_handle_digest_email(user_ids, event["cutoff"])
|
|
|
|
|
|
@assign_queue("email_mirror")
|
|
class MirrorWorker(QueueProcessingWorker):
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
rcpt_to = event["rcpt_to"]
|
|
msg = email.message_from_bytes(
|
|
base64.b64decode(event["msg_base64"]),
|
|
policy=email.policy.default,
|
|
)
|
|
assert isinstance(msg, EmailMessage) # https://github.com/python/typeshed/issues/2417
|
|
if not is_missed_message_address(rcpt_to):
|
|
# Missed message addresses are one-time use, so we don't need
|
|
# to worry about emails to them resulting in message spam.
|
|
recipient_realm = decode_stream_email_address(rcpt_to)[0].realm
|
|
try:
|
|
rate_limit_mirror_by_realm(recipient_realm)
|
|
except RateLimited:
|
|
logger.warning(
|
|
"MirrorWorker: Rejecting an email from: %s to realm: %s - rate limited.",
|
|
msg["From"],
|
|
recipient_realm.name,
|
|
)
|
|
return
|
|
|
|
mirror_email(msg, rcpt_to=rcpt_to)
|
|
|
|
|
|
@assign_queue("embed_links")
|
|
class FetchLinksEmbedData(QueueProcessingWorker):
|
|
# This is a slow queue with network requests, so a disk write is negligible.
|
|
# Update stats file after every consume call.
|
|
CONSUME_ITERATIONS_BEFORE_UPDATE_STATS_NUM = 1
|
|
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
for url in event["urls"]:
|
|
start_time = time.time()
|
|
url_preview.get_link_embed_data(url)
|
|
logging.info(
|
|
"Time spent on get_link_embed_data for %s: %s", url, time.time() - start_time
|
|
)
|
|
|
|
message = Message.objects.get(id=event["message_id"])
|
|
# If the message changed, we will run this task after updating the message
|
|
# in zerver.views.message_edit.update_message_backend
|
|
if message.content != event["message_content"]:
|
|
return
|
|
if message.content is not None:
|
|
query = UserMessage.objects.filter(
|
|
message=message.id,
|
|
)
|
|
message_user_ids = set(query.values_list("user_profile_id", flat=True))
|
|
|
|
# Fetch the realm whose settings we're using for rendering
|
|
realm = Realm.objects.get(id=event["message_realm_id"])
|
|
|
|
# If rendering fails, the called code will raise a JsonableError.
|
|
rendered_content = render_incoming_message(
|
|
message, message.content, message_user_ids, realm
|
|
)
|
|
do_update_embedded_data(message.sender, message, message.content, rendered_content)
|
|
|
|
|
|
@assign_queue("outgoing_webhooks")
|
|
class OutgoingWebhookWorker(QueueProcessingWorker):
|
|
def consume(self, event: Dict[str, Any]) -> None:
|
|
message = event["message"]
|
|
event["command"] = message["content"]
|
|
|
|
services = get_bot_services(event["user_profile_id"])
|
|
for service in services:
|
|
event["service_name"] = str(service.name)
|
|
service_handler = get_outgoing_webhook_service_handler(service)
|
|
do_rest_call(service.base_url, event, service_handler)
|
|
|
|
|
|
@assign_queue("embedded_bots")
|
|
class EmbeddedBotWorker(QueueProcessingWorker):
|
|
def get_bot_api_client(self, user_profile: UserProfile) -> EmbeddedBotHandler:
|
|
return EmbeddedBotHandler(user_profile)
|
|
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
user_profile_id = event["user_profile_id"]
|
|
user_profile = get_user_profile_by_id(user_profile_id)
|
|
|
|
message: Dict[str, Any] = event["message"]
|
|
|
|
# TODO: Do we actually want to allow multiple Services per bot user?
|
|
services = get_bot_services(user_profile_id)
|
|
for service in services:
|
|
bot_handler = get_bot_handler(str(service.name))
|
|
if bot_handler is None:
|
|
logging.error(
|
|
"Error: User %s has bot with invalid embedded bot service %s",
|
|
user_profile_id,
|
|
service.name,
|
|
)
|
|
continue
|
|
try:
|
|
if hasattr(bot_handler, "initialize"):
|
|
bot_handler.initialize(self.get_bot_api_client(user_profile))
|
|
if event["trigger"] == "mention":
|
|
message["content"] = extract_query_without_mention(
|
|
message=message,
|
|
client=self.get_bot_api_client(user_profile),
|
|
)
|
|
assert message["content"] is not None
|
|
bot_handler.handle_message(
|
|
message=message,
|
|
bot_handler=self.get_bot_api_client(user_profile),
|
|
)
|
|
except EmbeddedBotQuitException as e:
|
|
logging.warning(str(e))
|
|
|
|
|
|
@assign_queue("deferred_work")
|
|
class DeferredWorker(QueueProcessingWorker):
|
|
"""This queue processor is intended for cases where we want to trigger a
|
|
potentially expensive, not urgent, job to be run on a separate
|
|
thread from the Django worker that initiated it (E.g. so we that
|
|
can provide a low-latency HTTP response or avoid risk of request
|
|
timeouts for an operation that could in rare cases take minutes).
|
|
"""
|
|
|
|
# Because these operations have no SLO, and can take minutes,
|
|
# remove any processing timeouts
|
|
MAX_CONSUME_SECONDS = None
|
|
|
|
def consume(self, event: Dict[str, Any]) -> None:
|
|
start = time.time()
|
|
if event["type"] == "mark_stream_messages_as_read":
|
|
user_profile = get_user_profile_by_id(event["user_profile_id"])
|
|
|
|
for recipient_id in event["stream_recipient_ids"]:
|
|
do_mark_stream_messages_as_read(user_profile, recipient_id)
|
|
elif event["type"] == "mark_stream_messages_as_read_for_everyone":
|
|
# This event is generated by the stream deactivation code path.
|
|
batch_size = 100
|
|
offset = 0
|
|
while True:
|
|
messages = Message.objects.filter(
|
|
recipient_id=event["stream_recipient_id"]
|
|
).order_by("id")[offset : offset + batch_size]
|
|
UserMessage.objects.filter(message__in=messages).extra(
|
|
where=[UserMessage.where_unread()]
|
|
).update(flags=F("flags").bitor(UserMessage.flags.read))
|
|
offset += len(messages)
|
|
if len(messages) < batch_size:
|
|
break
|
|
elif event["type"] == "clear_push_device_tokens":
|
|
try:
|
|
clear_push_device_tokens(event["user_profile_id"])
|
|
except PushNotificationBouncerRetryLaterError:
|
|
|
|
def failure_processor(event: Dict[str, Any]) -> None:
|
|
logger.warning(
|
|
"Maximum retries exceeded for trigger:%s event:clear_push_device_tokens",
|
|
event["user_profile_id"],
|
|
)
|
|
|
|
retry_event(self.queue_name, event, failure_processor)
|
|
elif event["type"] == "realm_export":
|
|
realm = Realm.objects.get(id=event["realm_id"])
|
|
output_dir = tempfile.mkdtemp(prefix="zulip-export-")
|
|
export_event = RealmAuditLog.objects.get(id=event["id"])
|
|
user_profile = get_user_profile_by_id(event["user_profile_id"])
|
|
|
|
try:
|
|
public_url = export_realm_wrapper(
|
|
realm=realm,
|
|
output_dir=output_dir,
|
|
threads=6,
|
|
upload=True,
|
|
public_only=True,
|
|
delete_after_upload=True,
|
|
)
|
|
except Exception:
|
|
export_event.extra_data = orjson.dumps(
|
|
dict(
|
|
failed_timestamp=timezone_now().timestamp(),
|
|
)
|
|
).decode()
|
|
export_event.save(update_fields=["extra_data"])
|
|
logging.error(
|
|
"Data export for %s failed after %s",
|
|
user_profile.realm.string_id,
|
|
time.time() - start,
|
|
)
|
|
notify_realm_export(user_profile)
|
|
return
|
|
|
|
assert public_url is not None
|
|
|
|
# Update the extra_data field now that the export is complete.
|
|
export_event.extra_data = orjson.dumps(
|
|
dict(
|
|
export_path=urllib.parse.urlparse(public_url).path,
|
|
)
|
|
).decode()
|
|
export_event.save(update_fields=["extra_data"])
|
|
|
|
# Send a private message notification letting the user who
|
|
# triggered the export know the export finished.
|
|
with override_language(user_profile.default_language):
|
|
content = _(
|
|
"Your data export is complete and has been uploaded here:\n\n{public_url}"
|
|
).format(public_url=public_url)
|
|
internal_send_private_message(
|
|
sender=get_system_bot(settings.NOTIFICATION_BOT),
|
|
recipient_user=user_profile,
|
|
content=content,
|
|
)
|
|
|
|
# For future frontend use, also notify administrator
|
|
# clients that the export happened.
|
|
notify_realm_export(user_profile)
|
|
logging.info(
|
|
"Completed data export for %s in %s",
|
|
user_profile.realm.string_id,
|
|
time.time() - start,
|
|
)
|
|
|
|
end = time.time()
|
|
logger.info("deferred_work processed %s event (%dms)", event["type"], (end - start) * 1000)
|
|
|
|
|
|
@assign_queue("test", is_test_queue=True)
|
|
class TestWorker(QueueProcessingWorker):
|
|
# This worker allows you to test the queue worker infrastructure without
|
|
# creating significant side effects. It can be useful in development or
|
|
# for troubleshooting prod/staging. It pulls a message off the test queue
|
|
# and appends it to a file in /tmp.
|
|
def consume(self, event: Mapping[str, Any]) -> None: # nocoverage
|
|
fn = settings.ZULIP_WORKER_TEST_FILE
|
|
message = orjson.dumps(event)
|
|
logging.info("TestWorker should append this message to %s: %s", fn, message.decode())
|
|
with open(fn, "ab") as f:
|
|
f.write(message + b"\n")
|
|
|
|
|
|
@assign_queue("noop", is_test_queue=True)
|
|
class NoopWorker(QueueProcessingWorker):
|
|
"""Used to profile the queue processing framework, in zilencer's queue_rate."""
|
|
|
|
def __init__(self, max_consume: int = 1000, slow_queries: Sequence[int] = []) -> None:
|
|
self.consumed = 0
|
|
self.max_consume = max_consume
|
|
self.slow_queries: Set[int] = set(slow_queries)
|
|
|
|
def consume(self, event: Mapping[str, Any]) -> None:
|
|
self.consumed += 1
|
|
if self.consumed in self.slow_queries:
|
|
logging.info("Slow request...")
|
|
time.sleep(60)
|
|
logging.info("Done!")
|
|
if self.consumed >= self.max_consume:
|
|
self.stop()
|
|
|
|
|
|
@assign_queue("noop_batch", is_test_queue=True)
|
|
class BatchNoopWorker(LoopQueueProcessingWorker):
|
|
"""Used to profile the queue processing framework, in zilencer's queue_rate."""
|
|
|
|
batch_size = 500
|
|
|
|
def __init__(self, max_consume: int = 1000, slow_queries: Sequence[int] = []) -> None:
|
|
self.consumed = 0
|
|
self.max_consume = max_consume
|
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self.slow_queries: Set[int] = set(slow_queries)
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|
|
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def consume_batch(self, events: List[Dict[str, Any]]) -> None:
|
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event_numbers = set(range(self.consumed + 1, self.consumed + 1 + len(events)))
|
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found_slow = self.slow_queries & event_numbers
|
|
if found_slow:
|
|
logging.info("%d slow requests...", len(found_slow))
|
|
time.sleep(60 * len(found_slow))
|
|
logging.info("Done!")
|
|
self.consumed += len(events)
|
|
if self.consumed >= self.max_consume:
|
|
self.stop()
|