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