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aa845e7f60
ScheduledJob was written for much more generality than it ended up being used for. Currently it is used by send_future_email, and nothing else. Tailoring the model to emails in particular will make it easier to do things like selectively clear emails when people unsubscribe from particular email types, or seamlessly handle using the same email on multiple realms.
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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