zulip/zerver/lib/digest.py

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from __future__ import absolute_import
from typing import Any, Callable, Dict, Iterable, List, Set, Tuple, Text
from collections import defaultdict
import datetime
import pytz
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import six
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from django.db.models import Q, QuerySet
from django.template import loader
from django.conf import settings
from zerver.lib.notifications import build_message_list, hash_util_encode, \
one_click_unsubscribe_link
from zerver.lib.send_email import display_email, send_future_email, FromAddress
from zerver.models import UserProfile, UserMessage, Recipient, Stream, \
Subscription, get_active_streams
from zerver.context_processors import common_context
import logging
log_format = "%(asctime)s: %(message)s"
logging.basicConfig(format=log_format)
formatter = logging.Formatter(log_format)
file_handler = logging.FileHandler(settings.DIGEST_LOG_PATH)
file_handler.setFormatter(formatter)
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
logger.addHandler(file_handler)
# Digests accumulate 4 types of interesting traffic for a user:
# 1. Missed PMs
# 2. New streams
# 3. New users
# 4. Interesting stream traffic, as determined by the longest and most
# diversely comment upon topics.
def gather_hot_conversations(user_profile, stream_messages):
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# type: (UserProfile, QuerySet) -> 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, Text], int]
conversation_diversity = defaultdict(set) # type: Dict[Tuple[int, Text], Set[Text]]
for user_message in stream_messages:
if not user_message.message.sent_by_human():
# Don't include automated messages in the count.
continue
key = (user_message.message.recipient.type_id,
user_message.message.subject)
conversation_diversity[key].add(
user_message.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:
stream_id, subject = h
users = list(conversation_diversity[h])
count = conversation_length[h]
# We'll display up to 2 messages from the conversation.
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first_few_messages = [user_message.message for user_message in
stream_messages.filter(
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message__recipient__type_id=stream_id,
message__subject=subject)[:2]]
teaser_data = {"participants": users,
"count": count - len(first_few_messages),
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"first_few_messages": build_message_list(
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user_profile, first_few_messages)}
hot_conversation_render_payloads.append(teaser_data)
return hot_conversation_render_payloads
def gather_new_users(user_profile, threshold):
# type: (UserProfile, datetime.datetime) -> Tuple[int, List[Text]]
# Gather information on users in the realm who have recently
# joined.
if user_profile.realm.is_zephyr_mirror_realm:
new_users = [] # type: List[UserProfile]
else:
new_users = list(UserProfile.objects.filter(
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realm=user_profile.realm, date_joined__gt=threshold,
is_bot=False))
user_names = [user.full_name for user in new_users]
return len(user_names), user_names
def gather_new_streams(user_profile, threshold):
# type: (UserProfile, datetime.datetime) -> Tuple[int, Dict[str, List[Text]]]
if user_profile.realm.is_zephyr_mirror_realm:
new_streams = [] # type: List[Stream]
else:
new_streams = list(get_active_streams(user_profile.realm).filter(
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invite_only=False, date_created__gt=threshold))
base_url = u"%s/ # narrow/stream/" % (user_profile.realm.uri,)
streams_html = []
streams_plain = []
for stream in new_streams:
narrow_url = base_url + hash_util_encode(stream.name)
stream_link = u"<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(unread_pms, hot_conversations, new_streams, new_users):
# type: (Text, Text, int, int) -> bool
if unread_pms or hot_conversations:
# If you have any unread traffic, good enough.
return True
if new_streams and new_users:
# If you somehow don't have any traffic but your realm did get
# new streams and users, good enough.
return True
return False
def handle_digest_email(user_profile_id, cutoff):
# type: (int, float) -> None
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user_profile = UserProfile.objects.get(id=user_profile_id)
# 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,
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message__pub_date__gt=cutoff_date).order_by("message__pub_date")
context = common_context(user_profile)
# Start building email template data.
context.update({
'realm_name': user_profile.realm.name,
'name': user_profile.full_name,
'unsubscribe_link': one_click_unsubscribe_link(user_profile, "digest")
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})
# Gather recent missed PMs, re-using the missed PM email logic.
# You can't have an unread message that you sent, but when testing
# this causes confusion so filter your messages out.
pms = all_messages.filter(
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~Q(message__recipient__type=Recipient.STREAM) &
~Q(message__sender=user_profile))
# Show up to 4 missed PMs.
pms_limit = 4
context['unread_pms'] = build_message_list(
user_profile, [pm.message for pm in pms[:pms_limit]])
context['remaining_unread_pms_count'] = min(0, len(pms) - pms_limit)
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home_view_recipients = [sub.recipient for sub in
Subscription.objects.filter(
user_profile=user_profile,
active=True,
in_home_view=True)]
stream_messages = all_messages.filter(
message__recipient__type=Recipient.STREAM,
message__recipient__in=home_view_recipients)
# Gather hot conversations.
context["hot_conversations"] = gather_hot_conversations(
user_profile, stream_messages)
# Gather new streams.
new_streams_count, new_streams = gather_new_streams(
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user_profile, cutoff_date)
context["new_streams"] = new_streams
context["new_streams_count"] = new_streams_count
# Gather users who signed up recently.
new_users_count, new_users = gather_new_users(
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user_profile, cutoff_date)
context["new_users"] = new_users
# We don't want to send emails containing almost no information.
if enough_traffic(context["unread_pms"], context["hot_conversations"],
new_streams_count, new_users_count):
logger.info("Sending digest email for %s" % (user_profile.email,))
# Send now, as a ScheduledJob
send_future_email('zerver/emails/digest', to_user_id=user_profile.id,
from_name="Zulip Digest", from_address=FromAddress.NOREPLY,
context=context)