zulip/zerver/lib/digest.py

220 lines
8.4 KiB
Python

from typing import Any, Dict, List, Set, Tuple, Union
from collections import defaultdict
import datetime
import logging
import pytz
from django.conf import settings
from django.utils.timezone import now as timezone_now
from confirmation.models import one_click_unsubscribe_link
from zerver.lib.email_notifications import build_message_list
from zerver.lib.send_email import send_future_email, FromAddress
from zerver.lib.url_encoding import encode_stream
from zerver.models import UserProfile, UserMessage, Recipient, \
Subscription, UserActivity, get_active_streams, get_user_profile_by_id, \
Realm, Message
from zerver.context_processors import common_context
from zerver.lib.queue import queue_json_publish
from zerver.lib.logging_util import log_to_file
logger = logging.getLogger(__name__)
log_to_file(logger, settings.DIGEST_LOG_PATH)
DIGEST_CUTOFF = 5
# 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 inactive_since(user_profile: UserProfile, cutoff: datetime.datetime) -> bool:
# Hasn't used the app in the last DIGEST_CUTOFF (5) days.
most_recent_visit = [row.last_visit for row in
UserActivity.objects.filter(
user_profile=user_profile)]
if not most_recent_visit:
# This person has never used the app.
return True
last_visit = max(most_recent_visit)
return last_visit < cutoff
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_profile: UserProfile, cutoff: datetime.datetime) -> None:
# Convert cutoff to epoch seconds for transit.
event = {"user_profile_id": user_profile.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 not should_process_digest(realm.string_id):
continue
user_profiles = UserProfile.objects.filter(
realm=realm, is_active=True, is_bot=False, enable_digest_emails=True)
for user_profile in user_profiles:
if inactive_since(user_profile, cutoff):
queue_digest_recipient(user_profile, cutoff)
logger.info("%s is inactive, queuing for potential digest" % (
user_profile.email,))
def gather_hot_conversations(user_profile: UserProfile, messages: List[Message]) -> List[Dict[str, Any]]:
# Gather stream conversations of 2 types:
# 1. long conversations
# 2. conversations where many different people participated
#
# Returns a list of dictionaries containing the templating
# information for each hot conversation.
conversation_length = defaultdict(int) # type: Dict[Tuple[int, str], int]
conversation_messages = defaultdict(list) # type: Dict[Tuple[int, str], List[Message]]
conversation_diversity = defaultdict(set) # type: Dict[Tuple[int, str], Set[str]]
for message in messages:
key = (message.recipient.type_id,
message.topic_name())
conversation_messages[key].append(message)
if not message.sent_by_human():
# Don't include automated messages in the count.
continue
conversation_diversity[key].add(
message.sender.full_name)
conversation_length[key] += 1
diversity_list = list(conversation_diversity.items())
diversity_list.sort(key=lambda entry: len(entry[1]), reverse=True)
length_list = list(conversation_length.items())
length_list.sort(key=lambda entry: entry[1], reverse=True)
# Get up to the 4 best conversations from the diversity list
# and length list, filtering out overlapping conversations.
hot_conversations = [elt[0] for elt in diversity_list[:2]]
for candidate, _ in length_list:
if candidate not in hot_conversations:
hot_conversations.append(candidate)
if len(hot_conversations) >= 4:
break
# There was so much overlap between the diversity and length lists that we
# still have < 4 conversations. Try to use remaining diversity items to pad
# out the hot conversations.
num_convos = len(hot_conversations)
if num_convos < 4:
hot_conversations.extend([elt[0] for elt in diversity_list[num_convos:4]])
hot_conversation_render_payloads = []
for h in hot_conversations:
users = list(conversation_diversity[h])
count = conversation_length[h]
messages = conversation_messages[h]
# We'll display up to 2 messages from the conversation.
first_few_messages = messages[:2]
teaser_data = {"participants": users,
"count": count - len(first_few_messages),
"first_few_messages": build_message_list(
user_profile, first_few_messages)}
hot_conversation_render_payloads.append(teaser_data)
return hot_conversation_render_payloads
def gather_new_streams(user_profile: UserProfile,
threshold: datetime.datetime) -> Tuple[int, Dict[str, List[str]]]:
if user_profile.can_access_public_streams():
new_streams = list(get_active_streams(user_profile.realm).filter(
invite_only=False, date_created__gt=threshold))
else:
new_streams = []
base_url = "%s/#narrow/stream/" % (user_profile.realm.uri,)
streams_html = []
streams_plain = []
for stream in new_streams:
narrow_url = base_url + encode_stream(stream.id, stream.name)
stream_link = "<a href='%s'>%s</a>" % (narrow_url, stream.name)
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 handle_digest_email(user_profile_id: int, cutoff: float,
render_to_web: bool = False) -> Union[None, Dict[str, Any]]:
user_profile = get_user_profile_by_id(user_profile_id)
# We are disabling digest emails for soft deactivated users for the time.
# TODO: Find an elegant way to generate digest emails for these users.
if user_profile.long_term_idle:
return None
# Convert from epoch seconds to a datetime object.
cutoff_date = datetime.datetime.fromtimestamp(int(cutoff), tz=pytz.utc)
all_messages = UserMessage.objects.filter(
user_profile=user_profile,
message__pub_date__gt=cutoff_date
).select_related('message').order_by("message__pub_date")
context = common_context(user_profile)
# Start building email template data.
context.update({
'unsubscribe_link': one_click_unsubscribe_link(user_profile, "digest")
})
home_view_recipients = Subscription.objects.filter(
user_profile=user_profile,
active=True,
in_home_view=True).values_list('recipient_id', flat=True)
stream_messages = all_messages.filter(
message__recipient__type=Recipient.STREAM,
message__recipient__in=home_view_recipients)
messages = [um.message for um in stream_messages]
# Gather hot conversations.
context["hot_conversations"] = gather_hot_conversations(
user_profile, messages)
# Gather new streams.
new_streams_count, new_streams = gather_new_streams(
user_profile, cutoff_date)
context["new_streams"] = new_streams
context["new_streams_count"] = new_streams_count
if render_to_web:
return context
# We don't want to send emails containing almost no information.
if enough_traffic(context["hot_conversations"], new_streams_count):
logger.info("Sending digest email for %s" % (user_profile.email,))
# Send now, as a ScheduledEmail
send_future_email('zerver/emails/digest', user_profile.realm, to_user_ids=[user_profile.id],
from_name="Zulip Digest", from_address=FromAddress.NOREPLY, context=context)
return None