2013-10-21 23:25:53 +02:00
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import datetime
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2017-12-13 01:45:57 +01:00
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import logging
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2020-06-11 00:54:34 +02:00
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from collections import defaultdict
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from typing import Any, Dict, List, Set, Tuple, Union
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2013-10-21 23:25:53 +02:00
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2013-11-16 00:54:12 +01:00
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from django.conf import settings
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2017-08-27 16:30:48 +02:00
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from django.utils.timezone import now as timezone_now
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2013-10-21 23:25:53 +02:00
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2018-11-08 22:40:27 +01:00
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from confirmation.models import one_click_unsubscribe_link
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2016-11-08 10:07:47 +01:00
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from zerver.context_processors import common_context
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2020-06-11 00:54:34 +02:00
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from zerver.lib.email_notifications import build_message_list
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2017-12-13 01:45:57 +01:00
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from zerver.lib.logging_util import log_to_file
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2020-06-11 00:54:34 +02:00
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from zerver.lib.queue import queue_json_publish
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from zerver.lib.send_email import FromAddress, send_future_email
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from zerver.lib.url_encoding import encode_stream
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from zerver.models import (
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Message,
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Realm,
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RealmAuditLog,
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Recipient,
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Subscription,
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UserActivity,
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UserProfile,
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get_active_streams,
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get_user_profile_by_id,
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)
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2013-10-21 23:25:53 +02:00
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2017-12-13 01:45:57 +01:00
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logger = logging.getLogger(__name__)
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log_to_file(logger, settings.DIGEST_LOG_PATH)
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2014-01-08 17:33:12 +01:00
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2017-08-27 16:30:48 +02:00
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DIGEST_CUTOFF = 5
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2020-11-03 14:57:11 +01:00
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TopicKey = Tuple[int, str]
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2019-05-02 05:54:48 +02:00
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# Digests accumulate 2 types of interesting traffic for a user:
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# 1. New streams
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# 2. Interesting stream traffic, as determined by the longest and most
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2013-10-21 23:25:53 +02:00
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# diversely comment upon topics.
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2017-11-05 11:15:10 +01:00
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def inactive_since(user_profile: UserProfile, cutoff: datetime.datetime) -> bool:
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2017-08-25 21:44:28 +02:00
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# Hasn't used the app in the last DIGEST_CUTOFF (5) days.
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most_recent_visit = [row.last_visit for row in
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UserActivity.objects.filter(
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user_profile=user_profile)]
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if not most_recent_visit:
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# This person has never used the app.
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return True
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last_visit = max(most_recent_visit)
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return last_visit < cutoff
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2017-11-05 11:15:10 +01:00
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def should_process_digest(realm_str: str) -> bool:
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2017-08-25 21:48:19 +02:00
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if realm_str in settings.SYSTEM_ONLY_REALMS:
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# Don't try to send emails to system-only realms
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return False
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return True
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2017-08-25 21:52:47 +02:00
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# Changes to this should also be reflected in
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# zerver/worker/queue_processors.py:DigestWorker.consume()
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2017-11-05 11:15:10 +01:00
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def queue_digest_recipient(user_profile: UserProfile, cutoff: datetime.datetime) -> None:
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2017-08-25 21:52:47 +02:00
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# Convert cutoff to epoch seconds for transit.
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event = {"user_profile_id": user_profile.id,
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"cutoff": cutoff.strftime('%s')}
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2017-11-24 13:18:46 +01:00
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queue_json_publish("digest_emails", event)
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2017-08-25 21:52:47 +02:00
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2017-11-05 11:15:10 +01:00
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def enqueue_emails(cutoff: datetime.datetime) -> None:
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2018-03-09 00:16:44 +01:00
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if not settings.SEND_DIGEST_EMAILS:
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return
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2019-03-28 04:47:03 +01:00
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weekday = timezone_now().weekday()
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for realm in Realm.objects.filter(deactivated=False, digest_emails_enabled=True, digest_weekday=weekday):
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2017-08-27 16:30:48 +02:00
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if not should_process_digest(realm.string_id):
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continue
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user_profiles = UserProfile.objects.filter(
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realm=realm, is_active=True, is_bot=False, enable_digest_emails=True)
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for user_profile in user_profiles:
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if inactive_since(user_profile, cutoff):
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queue_digest_recipient(user_profile, cutoff)
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2020-05-02 08:44:14 +02:00
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logger.info(
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"User %s is inactive, queuing for potential digest",
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user_profile.id,
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)
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2017-08-27 16:30:48 +02:00
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2020-11-03 16:54:45 +01:00
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def gather_hot_topics(
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2020-11-03 13:51:59 +01:00
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user_profile: UserProfile,
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stream_ids: List[int],
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cutoff_date: datetime.datetime,
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) -> List[Dict[str, Any]]:
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2020-11-03 16:54:45 +01:00
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# Gather stream topics of 2 types:
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# 1. long topics
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# 2. topics where many different people participated
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2013-10-21 23:25:53 +02:00
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#
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# Returns a list of dictionaries containing the templating
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2020-11-03 16:54:45 +01:00
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# information for each hot topic.
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2013-10-21 23:25:53 +02:00
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2020-11-03 13:51:59 +01:00
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messages = Message.objects.filter(
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recipient__type=Recipient.STREAM,
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recipient__type_id__in=stream_ids,
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date_sent__gt=cutoff_date).select_related('recipient', 'sender', 'sending_client')
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2020-11-03 16:54:45 +01:00
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topic_length: Dict[TopicKey, int] = defaultdict(int)
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topic_messages: Dict[TopicKey, List[Message]] = defaultdict(list)
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topic_senders: Dict[TopicKey, Set[str]] = defaultdict(set)
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2018-11-11 19:06:59 +01:00
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for message in messages:
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key = (message.recipient.type_id,
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message.topic_name())
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2020-11-03 16:54:45 +01:00
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topic_messages[key].append(message)
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2018-11-11 18:46:21 +01:00
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2018-11-11 19:06:59 +01:00
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if not message.sent_by_human():
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2013-12-31 22:45:21 +01:00
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# Don't include automated messages in the count.
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continue
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2020-11-03 16:54:45 +01:00
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topic_senders[key].add(message.sender.full_name)
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topic_length[key] += 1
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2013-10-21 23:25:53 +02:00
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2020-11-03 16:54:45 +01:00
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topics_by_diversity = list(topic_senders)
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topics_by_diversity.sort(key=lambda key: topic_senders[key], reverse=True)
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2013-10-21 23:25:53 +02:00
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2020-11-03 16:54:45 +01:00
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topics_by_length = list(topic_length)
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topics_by_diversity.sort(key=lambda key: topic_length[key], reverse=True)
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2013-10-21 23:25:53 +02:00
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2020-11-03 16:54:45 +01:00
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# Get up to the 4 best topics from the diversity list
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# and length list, filtering out overlapping topics.
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hot_topics = topics_by_diversity[:2]
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2020-11-03 15:20:45 +01:00
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for topic_key in topics_by_length:
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2020-11-03 16:54:45 +01:00
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if topic_key not in hot_topics:
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hot_topics.append(topic_key)
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if len(hot_topics) >= 4:
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2013-10-21 23:25:53 +02:00
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break
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2013-12-13 20:18:44 +01:00
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# There was so much overlap between the diversity and length lists that we
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2020-11-03 16:54:45 +01:00
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# still have < 4 topics. Try to use remaining diversity items to pad
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# out the hot topics.
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num_convos = len(hot_topics)
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2013-12-13 20:18:44 +01:00
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if num_convos < 4:
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2020-11-03 16:54:45 +01:00
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hot_topics.extend(topics_by_diversity[num_convos:4])
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2013-12-13 20:18:44 +01:00
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2020-11-03 16:54:45 +01:00
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hot_topic_render_payloads = []
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for h in hot_topics:
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users = list(topic_senders[h])
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count = topic_length[h]
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messages = topic_messages[h]
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2013-10-21 23:25:53 +02:00
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2020-11-03 16:54:45 +01:00
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# We'll display up to 2 messages from the topic.
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2018-11-11 18:46:21 +01:00
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first_few_messages = messages[:2]
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2013-10-21 23:25:53 +02:00
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2013-10-25 18:53:35 +02:00
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teaser_data = {"participants": users,
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2013-10-21 23:25:53 +02:00
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"count": count - len(first_few_messages),
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2016-12-02 08:15:16 +01:00
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"first_few_messages": build_message_list(
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2017-01-24 06:02:39 +01:00
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user_profile, first_few_messages)}
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2013-10-21 23:25:53 +02:00
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2020-11-03 16:54:45 +01:00
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hot_topic_render_payloads.append(teaser_data)
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return hot_topic_render_payloads
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2013-10-21 23:25:53 +02:00
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2017-11-05 11:15:10 +01:00
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def gather_new_streams(user_profile: UserProfile,
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2018-05-10 19:13:36 +02:00
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threshold: datetime.datetime) -> Tuple[int, Dict[str, List[str]]]:
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2020-07-24 19:41:27 +02:00
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if user_profile.is_guest:
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new_streams = list(get_active_streams(user_profile.realm).filter(
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is_web_public=True, date_created__gt=threshold))
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elif user_profile.can_access_public_streams():
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2014-01-24 23:30:53 +01:00
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new_streams = list(get_active_streams(user_profile.realm).filter(
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2017-01-24 07:06:13 +01:00
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invite_only=False, date_created__gt=threshold))
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2013-10-21 23:25:53 +02:00
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2020-06-10 06:41:04 +02:00
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base_url = f"{user_profile.realm.uri}/#narrow/stream/"
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2013-10-25 18:53:35 +02:00
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streams_html = []
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streams_plain = []
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2013-10-21 23:25:53 +02:00
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for stream in new_streams:
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2018-02-15 21:02:47 +01:00
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narrow_url = base_url + encode_stream(stream.id, stream.name)
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2020-06-10 06:41:04 +02:00
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stream_link = f"<a href='{narrow_url}'>{stream.name}</a>"
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2013-10-25 18:53:35 +02:00
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streams_html.append(stream_link)
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streams_plain.append(stream.name)
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2013-10-21 23:25:53 +02:00
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return len(new_streams), {"html": streams_html, "plain": streams_plain}
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2019-05-02 05:54:48 +02:00
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def enough_traffic(hot_conversations: str, new_streams: int) -> bool:
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return bool(hot_conversations or new_streams)
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2013-10-21 23:25:53 +02:00
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2018-08-12 22:09:34 +02:00
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def handle_digest_email(user_profile_id: int, cutoff: float,
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render_to_web: bool = False) -> Union[None, Dict[str, Any]]:
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2017-08-15 21:53:48 +02:00
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user_profile = get_user_profile_by_id(user_profile_id)
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2017-08-16 06:59:38 +02:00
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2013-10-21 23:25:53 +02:00
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# Convert from epoch seconds to a datetime object.
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2020-06-05 06:55:20 +02:00
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cutoff_date = datetime.datetime.fromtimestamp(int(cutoff), tz=datetime.timezone.utc)
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2013-10-21 23:25:53 +02:00
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2017-05-04 23:37:01 +02:00
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context = common_context(user_profile)
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2016-11-08 10:07:47 +01:00
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2013-10-21 23:25:53 +02:00
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# Start building email template data.
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2020-09-03 05:32:15 +02:00
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context.update(
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unsubscribe_link=one_click_unsubscribe_link(user_profile, "digest"),
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)
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2013-10-21 23:25:53 +02:00
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2019-03-03 07:14:58 +01:00
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home_view_streams = Subscription.objects.filter(
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2019-03-03 07:09:32 +01:00
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user_profile=user_profile,
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2019-03-03 07:14:58 +01:00
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recipient__type=Recipient.STREAM,
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2019-03-03 07:09:32 +01:00
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active=True,
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2018-08-02 23:46:05 +02:00
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is_muted=False).values_list('recipient__type_id', flat=True)
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2013-10-21 23:25:53 +02:00
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2019-03-03 07:14:58 +01:00
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if not user_profile.long_term_idle:
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stream_ids = home_view_streams
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else:
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stream_ids = exclude_subscription_modified_streams(user_profile, home_view_streams, cutoff_date)
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2013-10-21 23:25:53 +02:00
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# Gather hot conversations.
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2020-11-03 16:54:45 +01:00
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context["hot_conversations"] = gather_hot_topics(user_profile, stream_ids, cutoff_date)
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2013-10-21 23:25:53 +02:00
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# Gather new streams.
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new_streams_count, new_streams = gather_new_streams(
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2016-06-04 21:50:32 +02:00
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user_profile, cutoff_date)
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2017-05-04 23:37:01 +02:00
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context["new_streams"] = new_streams
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context["new_streams_count"] = new_streams_count
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2013-10-21 23:25:53 +02:00
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2019-08-17 11:04:48 +02:00
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# TODO: Set has_preheader if we want to include a preheader.
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2018-08-12 22:09:34 +02:00
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if render_to_web:
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return context
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2013-10-21 23:25:53 +02:00
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# We don't want to send emails containing almost no information.
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2019-05-02 05:54:48 +02:00
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if enough_traffic(context["hot_conversations"], new_streams_count):
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2020-05-02 08:44:14 +02:00
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logger.info("Sending digest email for user %s", user_profile.id)
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2017-07-02 21:10:41 +02:00
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# Send now, as a ScheduledEmail
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2018-12-03 23:26:51 +01:00
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send_future_email('zerver/emails/digest', user_profile.realm, to_user_ids=[user_profile.id],
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2020-03-12 20:28:05 +01:00
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from_name="Zulip Digest", from_address=FromAddress.no_reply_placeholder,
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context=context)
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2018-08-12 22:09:34 +02:00
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return None
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2019-03-03 07:14:58 +01:00
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def exclude_subscription_modified_streams(user_profile: UserProfile,
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stream_ids: List[int],
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cutoff_date: datetime.datetime) -> List[int]:
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"""Exclude streams from given list where users' subscription was modified."""
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events = [
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RealmAuditLog.SUBSCRIPTION_CREATED,
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RealmAuditLog.SUBSCRIPTION_ACTIVATED,
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python: Use trailing commas consistently.
Automatically generated by the following script, based on the output
of lint with flake8-comma:
import re
import sys
last_filename = None
last_row = None
lines = []
for msg in sys.stdin:
m = re.match(
r"\x1b\[35mflake8 \|\x1b\[0m \x1b\[1;31m(.+):(\d+):(\d+): (\w+)", msg
)
if m:
filename, row_str, col_str, err = m.groups()
row, col = int(row_str), int(col_str)
if filename == last_filename:
assert last_row != row
else:
if last_filename is not None:
with open(last_filename, "w") as f:
f.writelines(lines)
with open(filename) as f:
lines = f.readlines()
last_filename = filename
last_row = row
line = lines[row - 1]
if err in ["C812", "C815"]:
lines[row - 1] = line[: col - 1] + "," + line[col - 1 :]
elif err in ["C819"]:
assert line[col - 2] == ","
lines[row - 1] = line[: col - 2] + line[col - 1 :].lstrip(" ")
if last_filename is not None:
with open(last_filename, "w") as f:
f.writelines(lines)
Signed-off-by: Anders Kaseorg <anders@zulipchat.com>
2020-04-10 05:23:40 +02:00
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RealmAuditLog.SUBSCRIPTION_DEACTIVATED,
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2019-03-03 07:14:58 +01:00
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]
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# Streams where the user's subscription was changed
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modified_streams = RealmAuditLog.objects.filter(
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realm=user_profile.realm,
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modified_user=user_profile,
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event_time__gt=cutoff_date,
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event_type__in=events).values_list('modified_stream_id', flat=True)
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return list(set(stream_ids) - set(modified_streams))
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