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			203 lines
		
	
	
		
			7.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			203 lines
		
	
	
		
			7.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
from typing import Dict, List, Optional, Set, Tuple
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from typing_extensions import TypedDict
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from zerver.lib.cache import (
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    bulk_cached_fetch,
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    cache_with_key,
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    display_recipient_bulk_get_users_by_id_cache_key,
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    display_recipient_cache_key,
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    transformed_bulk_cached_fetch,
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)
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from zerver.lib.types import DisplayRecipientT, UserDisplayRecipient
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from zerver.models import Recipient, Stream, UserProfile, bulk_get_huddle_user_ids
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display_recipient_fields = [
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    "id",
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    "email",
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    "full_name",
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    "is_mirror_dummy",
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]
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class TinyStreamResult(TypedDict):
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    id: int
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    name: str
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@cache_with_key(lambda *args: display_recipient_cache_key(args[0]), timeout=3600 * 24 * 7)
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def get_display_recipient_remote_cache(
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    recipient_id: int, recipient_type: int, recipient_type_id: Optional[int]
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) -> DisplayRecipientT:
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    """
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    returns: an appropriate object describing the recipient.  For a
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    stream this will be the stream name as a string.  For a huddle or
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    personal, it will be an array of dicts about each recipient.
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    """
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    if recipient_type == Recipient.STREAM:
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        assert recipient_type_id is not None
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        stream = Stream.objects.values("name").get(id=recipient_type_id)
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        return stream["name"]
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    # The main priority for ordering here is being deterministic.
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    # Right now, we order by ID, which matches the ordering of user
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    # names in the left sidebar.
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    user_profile_list = (
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        UserProfile.objects.filter(
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            subscription__recipient_id=recipient_id,
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        )
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        .order_by("id")
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        .values(*display_recipient_fields)
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    )
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    return list(user_profile_list)
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def user_dict_id_fetcher(user_dict: UserDisplayRecipient) -> int:
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    return user_dict["id"]
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def bulk_get_user_profile_by_id(uids: List[int]) -> Dict[int, UserDisplayRecipient]:
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    return bulk_cached_fetch(
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        # Use a separate cache key to protect us from conflicts with
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        # the get_user_profile_by_id cache.
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        # (Since we fetch only several fields here)
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        cache_key_function=display_recipient_bulk_get_users_by_id_cache_key,
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        query_function=lambda ids: list(
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            UserProfile.objects.filter(id__in=ids).values(*display_recipient_fields)
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        ),
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        object_ids=uids,
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        id_fetcher=user_dict_id_fetcher,
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    )
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def bulk_fetch_display_recipients(
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    recipient_tuples: Set[Tuple[int, int, int]],
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) -> Dict[int, DisplayRecipientT]:
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    """
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    Takes set of tuples of the form (recipient_id, recipient_type, recipient_type_id)
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    Returns dict mapping recipient_id to corresponding display_recipient
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    """
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    # Build dict mapping recipient id to (type, type_id) of the corresponding recipient:
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    recipient_id_to_type_pair_dict = {
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        recipient[0]: (recipient[1], recipient[2]) for recipient in recipient_tuples
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    }
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    # And the inverse mapping:
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    type_pair_to_recipient_id_dict = {
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        (recipient[1], recipient[2]): recipient[0] for recipient in recipient_tuples
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    }
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    stream_recipients = {
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        recipient for recipient in recipient_tuples if recipient[1] == Recipient.STREAM
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    }
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    personal_and_huddle_recipients = recipient_tuples - stream_recipients
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    def stream_query_function(recipient_ids: List[int]) -> List[TinyStreamResult]:
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        stream_ids = [
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            recipient_id_to_type_pair_dict[recipient_id][1] for recipient_id in recipient_ids
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        ]
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        return Stream.objects.filter(id__in=stream_ids).values("name", "id")
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    def stream_id_fetcher(stream: TinyStreamResult) -> int:
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        return type_pair_to_recipient_id_dict[(Recipient.STREAM, stream["id"])]
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    def stream_cache_transformer(stream: TinyStreamResult) -> str:
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        return stream["name"]
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    # ItemT = Stream, CacheItemT = str (name), ObjKT = int (recipient_id)
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    stream_display_recipients: Dict[int, str] = transformed_bulk_cached_fetch(
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        cache_key_function=display_recipient_cache_key,
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        query_function=stream_query_function,
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        object_ids=[recipient[0] for recipient in stream_recipients],
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        id_fetcher=stream_id_fetcher,
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        cache_transformer=stream_cache_transformer,
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    )
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    # Now we have to create display_recipients for personal and huddle messages.
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    # We do this via generic_bulk_cached_fetch, supplying apprioprate functions to it.
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    def personal_and_huddle_query_function(
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        recipient_ids: List[int],
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    ) -> List[Tuple[int, List[UserDisplayRecipient]]]:
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        """
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        Return a list of tuples of the form (recipient_id, [list of UserProfiles])
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        where [list of UserProfiles] has users corresponding to the recipient,
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        so the receiving userin Recipient.PERSONAL case,
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        or in Personal.HUDDLE case - users in the huddle.
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        This is a pretty hacky return value, but it needs to be in this form,
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        for this function to work as the query_function in generic_bulk_cached_fetch.
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        """
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        recipients = [
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            Recipient(
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                id=recipient_id,
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                type=recipient_id_to_type_pair_dict[recipient_id][0],
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                type_id=recipient_id_to_type_pair_dict[recipient_id][1],
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            )
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            for recipient_id in recipient_ids
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        ]
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        # Find all user ids whose UserProfiles we will need to fetch:
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        user_ids_to_fetch: Set[int] = set()
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        huddle_user_ids: Dict[int, List[int]] = {}
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        huddle_user_ids = bulk_get_huddle_user_ids(
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            [recipient for recipient in recipients if recipient.type == Recipient.HUDDLE]
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        )
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        for recipient in recipients:
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            if recipient.type == Recipient.PERSONAL:
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                user_ids_to_fetch.add(recipient.type_id)
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            else:
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                user_ids_to_fetch = user_ids_to_fetch.union(huddle_user_ids[recipient.id])
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        # Fetch the needed UserProfiles:
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        user_profiles: Dict[int, UserDisplayRecipient] = bulk_get_user_profile_by_id(
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            list(user_ids_to_fetch)
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        )
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        # Build the return value:
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        result: List[Tuple[int, List[UserDisplayRecipient]]] = []
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        for recipient in recipients:
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            if recipient.type == Recipient.PERSONAL:
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                result.append((recipient.id, [user_profiles[recipient.type_id]]))
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            else:
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                result.append(
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                    (
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                        recipient.id,
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                        [user_profiles[user_id] for user_id in huddle_user_ids[recipient.id]],
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                    )
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                )
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        return result
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    def personal_and_huddle_cache_transformer(
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        db_object: Tuple[int, List[UserDisplayRecipient]],
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    ) -> List[UserDisplayRecipient]:
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        """
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        Takes an element of the list returned by the query_function, maps it to the final
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        display_recipient list.
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        """
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        user_profile_list = db_object[1]
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        display_recipient = user_profile_list
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        return display_recipient
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    def personal_and_huddle_id_fetcher(db_object: Tuple[int, List[UserDisplayRecipient]]) -> int:
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        # db_object is a tuple, with recipient_id in the first position
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        return db_object[0]
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    # ItemT = Tuple[int, List[UserDisplayRecipient]] (recipient_id, list of corresponding users)
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    # CacheItemT = List[UserDisplayRecipient] (display_recipient list)
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    # ObjKT = int (recipient_id)
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    personal_and_huddle_display_recipients: Dict[
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        int, List[UserDisplayRecipient]
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    ] = transformed_bulk_cached_fetch(
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        cache_key_function=display_recipient_cache_key,
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        query_function=personal_and_huddle_query_function,
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        object_ids=[recipient[0] for recipient in personal_and_huddle_recipients],
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        id_fetcher=personal_and_huddle_id_fetcher,
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        cache_transformer=personal_and_huddle_cache_transformer,
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    )
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    # Glue the dicts together and return:
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    return {**stream_display_recipients, **personal_and_huddle_display_recipients}
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