zulip/zerver/lib/digest.py

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import datetime
import logging
from collections import defaultdict
from typing import Any, Dict, List, Set, Tuple
from django.conf import settings
from django.db import transaction
from django.utils.timezone import now as timezone_now
from confirmation.models import one_click_unsubscribe_link
from zerver.context_processors import common_context
from zerver.lib.email_notifications import build_message_list
from zerver.lib.logging_util import log_to_file
from zerver.lib.message import get_last_message_id
from zerver.lib.queue import queue_json_publish
from zerver.lib.send_email import FromAddress, send_future_email
from zerver.lib.url_encoding import encode_stream
from zerver.models import (
Message,
Realm,
RealmAuditLog,
Recipient,
Subscription,
UserActivityInterval,
UserProfile,
get_active_streams,
)
logger = logging.getLogger(__name__)
log_to_file(logger, settings.DIGEST_LOG_PATH)
DIGEST_CUTOFF = 5
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TopicKey = Tuple[int, str]
class DigestTopic:
def __init__(self, topic_key: TopicKey) -> None:
self.topic_key = topic_key
self.human_senders: Set[str] = set()
self.sample_messages: List[Message] = []
self.num_human_messages = 0
def add_message(self, message: Message) -> None:
if len(self.sample_messages) < 2:
self.sample_messages.append(message)
if message.sent_by_human():
self.human_senders.add(message.sender.full_name)
self.num_human_messages += 1
def length(self) -> int:
return self.num_human_messages
def diversity(self) -> int:
return len(self.human_senders)
def teaser_data(self, user_profile: UserProfile) -> Dict[str, Any]:
teaser_count = self.num_human_messages - len(self.sample_messages)
first_few_messages = build_message_list(
user_profile,
self.sample_messages,
)
return {
"participants": self.human_senders,
"count": teaser_count,
"first_few_messages": first_few_messages,
}
# Digests accumulate 2 types of interesting traffic for a user:
# 1. New streams
# 2. Interesting stream traffic, as determined by the longest and most
# diversely comment upon topics.
def should_process_digest(realm_str: str) -> bool:
if realm_str in settings.SYSTEM_ONLY_REALMS:
# Don't try to send emails to system-only realms
return False
return True
# Changes to this should also be reflected in
# zerver/worker/queue_processors.py:DigestWorker.consume()
def queue_digest_recipient(user_id: int, cutoff: datetime.datetime) -> None:
# Convert cutoff to epoch seconds for transit.
event = {
"user_profile_id": user_id,
"cutoff": cutoff.strftime('%s')
}
queue_json_publish("digest_emails", event)
def enqueue_emails(cutoff: datetime.datetime) -> None:
if not settings.SEND_DIGEST_EMAILS:
return
weekday = timezone_now().weekday()
for realm in Realm.objects.filter(deactivated=False, digest_emails_enabled=True, digest_weekday=weekday):
if should_process_digest(realm.string_id):
_enqueue_emails_for_realm(realm, cutoff)
def _enqueue_emails_for_realm(realm: Realm, cutoff: datetime.datetime) -> None:
# This should only be called directly by tests. Use enqueue_emails
# to process all realms that are set up for processing on any given day.
realm_user_ids = set(UserProfile.objects.filter(
realm=realm,
is_active=True,
is_bot=False,
enable_digest_emails=True,
).values_list('id', flat=True))
twelve_hours_ago = timezone_now() - datetime.timedelta(hours=12)
recent_user_ids = set(RealmAuditLog.objects.filter(
realm_id=realm.id,
event_type=RealmAuditLog.USER_DIGEST_EMAIL_CREATED,
event_time__gt=twelve_hours_ago,
).values_list('modified_user_id', flat=True).distinct())
realm_user_ids -= recent_user_ids
active_user_ids = set(UserActivityInterval.objects.filter(
user_profile_id__in=realm_user_ids,
end__gt=cutoff,
).values_list('user_profile_id', flat=True).distinct())
user_ids = realm_user_ids - active_user_ids
for user_id in user_ids:
queue_digest_recipient(user_id, cutoff)
logger.info(
"User %s is inactive, queuing for potential digest",
user_id,
)
def get_recent_topics(
stream_ids: List[int],
cutoff_date: datetime.datetime,
) -> List[DigestTopic]:
# Gather information about topic conversations, then
# classify by:
# * topic length
# * number of senders
messages = Message.objects.filter(
recipient__type=Recipient.STREAM,
recipient__type_id__in=stream_ids,
date_sent__gt=cutoff_date,
).order_by(
'id', # we will sample the first few messages
).select_related(
'recipient', # we need stream_id
'sender', # we need the sender's full name
'sending_client' # for Message.sent_by_human
)
digest_topic_map: Dict[TopicKey, DigestTopic] = {}
for message in messages:
topic_key = (message.recipient.type_id, message.topic_name())
if topic_key not in digest_topic_map:
digest_topic_map[topic_key] = DigestTopic(topic_key)
digest_topic_map[topic_key].add_message(message)
topics = list(digest_topic_map.values())
return topics
def get_hot_topics(topics: List[DigestTopic]) -> List[DigestTopic]:
topics_by_diversity = sorted(topics, key=lambda dt: dt.diversity())
topics_by_length = sorted(topics, key=lambda dt: dt.length())
# Start with the two most diverse topics.
hot_topics = topics_by_diversity[:2]
# Pad out our list up to 4 items, using the topics' length (aka message
# count) as the secondary filter.
for topic in topics_by_length:
if topic not in hot_topics:
hot_topics.append(topic)
if len(hot_topics) >= 4:
break
return hot_topics
def gather_new_streams(user_profile: UserProfile,
threshold: datetime.datetime) -> Tuple[int, Dict[str, List[str]]]:
if user_profile.is_guest:
new_streams = list(get_active_streams(user_profile.realm).filter(
is_web_public=True, date_created__gt=threshold))
elif user_profile.can_access_public_streams():
new_streams = list(get_active_streams(user_profile.realm).filter(
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invite_only=False, date_created__gt=threshold))
base_url = f"{user_profile.realm.uri}/#narrow/stream/"
streams_html = []
streams_plain = []
for stream in new_streams:
narrow_url = base_url + encode_stream(stream.id, stream.name)
stream_link = f"<a href='{narrow_url}'>{stream.name}</a>"
streams_html.append(stream_link)
streams_plain.append(stream.name)
return len(new_streams), {"html": streams_html, "plain": streams_plain}
def enough_traffic(hot_conversations: str, new_streams: int) -> bool:
return bool(hot_conversations or new_streams)
def bulk_get_digest_context(users: List[UserProfile], cutoff: float) -> Dict[int, Dict[str, Any]]:
# Convert from epoch seconds to a datetime object.
cutoff_date = datetime.datetime.fromtimestamp(int(cutoff), tz=datetime.timezone.utc)
result: Dict[int, Dict[str, Any]] = {}
user_ids = [user.id for user in users]
def get_stream_map(user_ids: List[int]) -> Dict[int, Set[int]]:
rows = Subscription.objects.filter(
user_profile_id__in=user_ids,
recipient__type=Recipient.STREAM,
active=True,
is_muted=False,
).values('user_profile_id', 'recipient__type_id')
# maps user_id -> {stream_id, stream_id, ...}
dct: Dict[int, Set[int]] = defaultdict(set)
for row in rows:
dct[row['user_profile_id']].add(row['recipient__type_id'])
return dct
stream_map = get_stream_map(user_ids)
for user in users:
stream_ids = stream_map[user.id]
if user.long_term_idle:
stream_ids -= streams_recently_modified_for_user(user, cutoff_date)
recent_topics = get_recent_topics(sorted(list(stream_ids)), cutoff_date)
hot_topics = get_hot_topics(recent_topics)
context = common_context(user)
# Start building email template data.
unsubscribe_link = one_click_unsubscribe_link(user, "digest")
context.update(unsubscribe_link=unsubscribe_link)
# Get context data for hot conversations.
context["hot_conversations"] = [
hot_topic.teaser_data(user)
for hot_topic in hot_topics
]
# Gather new streams.
new_streams_count, new_streams = gather_new_streams(user, cutoff_date)
context["new_streams"] = new_streams
context["new_streams_count"] = new_streams_count
result[user.id] = context
return result
def get_digest_context(user: UserProfile, cutoff: float) -> Dict[str, Any]:
return bulk_get_digest_context([user], cutoff)[user.id]
@transaction.atomic
def bulk_handle_digest_email(user_ids: List[int], cutoff: float) -> None:
# We go directly to the database to get user objects,
# since inactive users are likely to not be in the cache.
users = UserProfile.objects.filter(id__in=user_ids).order_by('id')
context_map = bulk_get_digest_context(users, cutoff)
digest_users = []
for user in users:
context = context_map[user.id]
# We don't want to send emails containing almost no information.
if enough_traffic(context["hot_conversations"], context["new_streams_count"]):
digest_users.append(user)
logger.info("Sending digest email for user %s", user.id)
# Send now, as a ScheduledEmail
send_future_email(
'zerver/emails/digest',
user.realm,
to_user_ids=[user.id],
from_name="Zulip Digest",
from_address=FromAddress.no_reply_placeholder,
context=context,
)
bulk_write_realm_audit_logs(digest_users)
def bulk_write_realm_audit_logs(users: List[UserProfile]) -> None:
if not users:
return
# We write RealmAuditLog rows for auditing, and we will also
# use these rows during the next run to possibly exclude the
# users (if insufficient time has passed).
last_message_id = get_last_message_id()
now = timezone_now()
log_rows = [
RealmAuditLog(
realm_id=user.realm_id,
modified_user_id=user.id,
event_last_message_id=last_message_id,
event_time=now,
event_type=RealmAuditLog.USER_DIGEST_EMAIL_CREATED,
)
for user in users
]
RealmAuditLog.objects.bulk_create(log_rows)
def handle_digest_email(user_id: int, cutoff: float) -> None:
bulk_handle_digest_email([user_id], cutoff)
def streams_recently_modified_for_user(user: UserProfile, cutoff_date: datetime.datetime) -> Set[int]:
events = [
RealmAuditLog.SUBSCRIPTION_CREATED,
RealmAuditLog.SUBSCRIPTION_ACTIVATED,
RealmAuditLog.SUBSCRIPTION_DEACTIVATED,
]
# Streams where the user's subscription was changed
modified_streams = RealmAuditLog.objects.filter(
realm=user.realm,
modified_user=user,
event_time__gt=cutoff_date,
event_type__in=events).values_list('modified_stream_id', flat=True)
return set(modified_streams)