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presence: Extract get_legacy_user_info.
This code is a bit flatter and just preps the data for a single user. There is never any interaction between the data for user A and user B, so we can mostly avoid complicated nested data structures and do most of the data-crunching on a per-user basis. We also do an explicit sort of the data before running it through groupby. The explicit sort simplifies how we calculate `most_recent_info` and also avoids needing to add `dt` to an intermediate data structure. Finally, when it comes to the individual client data, the code has relied on the assumption that there is only one row per client, which I believe to be true, but now the code is more explicit about that.
This commit is contained in:
@@ -1,11 +1,12 @@
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from collections import defaultdict
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from collections import defaultdict
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import datetime
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import datetime
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import itertools
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import time
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import time
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from django.utils.timezone import now as timezone_now
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from django.utils.timezone import now as timezone_now
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from typing import Any, DefaultDict, Dict, List, Set
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from typing import Any, Dict, List, Set
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from zerver.lib.timestamp import datetime_to_timestamp
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from zerver.lib.timestamp import datetime_to_timestamp
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from zerver.models import (
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from zerver.models import (
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@@ -16,23 +17,49 @@ from zerver.models import (
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UserProfile,
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UserProfile,
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)
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)
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def get_status_dicts_for_rows(presence_rows: List[Dict[str, Any]],
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def get_status_dicts_for_rows(all_rows: List[Dict[str, Any]],
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mobile_user_ids: Set[int],
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mobile_user_ids: Set[int],
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slim_presence: bool) -> Dict[str, Dict[str, Any]]:
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slim_presence: bool) -> Dict[str, Dict[str, Any]]:
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info_row_dct = defaultdict(list) # type: DefaultDict[str, List[Dict[str, Any]]]
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# Note that datetime values have sub-second granularity, which is
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for row in presence_rows:
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# mostly important for avoiding test flakes, but it's also technically
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# For now slim_presence just means that we will use
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# more precise for real users.
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# user_id as a key instead of email. We will eventually
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# We could technically do this sort with the database, but doing it
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# do other things based on this flag to make things simpler
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# here prevents us from having to assume the caller is playing nice.
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# for the clients.
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all_rows = sorted(
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if slim_presence:
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all_rows,
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# Stringify user_id here, since it's gonna be turned
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key = lambda row: (row['user_profile__id'], row['timestamp'])
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# into a string anyway by JSON, and it keeps mypy happy.
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)
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user_key = str(row['user_profile__id'])
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else:
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user_key = row['user_profile__email']
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# For now slim_presence just means that we will use
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# user_id as a key instead of email. We will eventually
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# do other things based on this flag to make things simpler
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# for the clients.
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if slim_presence:
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# Stringify user_id here, since it's gonna be turned
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# into a string anyway by JSON, and it keeps mypy happy.
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get_user_key = lambda row: str(row['user_profile__id'])
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else:
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get_user_key = lambda row: row['user_profile__email']
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user_statuses = dict() # type: Dict[str, Dict[str, Any]]
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for user_key, presence_rows in itertools.groupby(all_rows, get_user_key):
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info = get_legacy_user_info(
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list(presence_rows),
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mobile_user_ids
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)
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user_statuses[user_key] = info
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return user_statuses
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def get_legacy_user_info(presence_rows: List[Dict[str, Any]],
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mobile_user_ids: Set[int]) -> Dict[str, Any]:
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# The format of data here is for legacy users of our API,
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# including old versions of the mobile app.
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info_rows = []
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for row in presence_rows:
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client_name = row['client__name']
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client_name = row['client__name']
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status = UserPresence.status_to_string(row['status'])
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status = UserPresence.status_to_string(row['status'])
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dt = row['timestamp']
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dt = row['timestamp']
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@@ -44,38 +71,31 @@ def get_status_dicts_for_rows(presence_rows: List[Dict[str, Any]],
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info = dict(
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info = dict(
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client=client_name,
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client=client_name,
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status=status,
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status=status,
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dt=dt,
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timestamp=timestamp,
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timestamp=timestamp,
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pushable=pushable,
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pushable=pushable,
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)
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)
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info_row_dct[user_key].append(info)
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info_rows.append(info)
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user_statuses = dict() # type: Dict[str, Dict[str, Any]]
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most_recent_info = info_rows[-1]
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for user_key, info_rows in info_row_dct.items():
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result = dict()
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# Note that datetime values have sub-second granularity, which is
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# mostly important for avoiding test flakes, but it's also technically
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# more precise for real users.
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by_time = lambda row: row['dt']
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most_recent_info = max(info_rows, key=by_time)
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# We don't send datetime values to the client.
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# The word "aggegrated" here is possibly misleading.
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for r in info_rows:
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# It's really just the most recent client's info.
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del r['dt']
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result['aggregated'] = dict(
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client=most_recent_info['client'],
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status=most_recent_info['status'],
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timestamp=most_recent_info['timestamp'],
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)
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client_dict = {info['client']: info for info in info_rows}
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# Build a dictionary of client -> info. There should
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user_statuses[user_key] = client_dict
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# only be one row per client, but to be on the safe side,
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# we always overwrite with rows that are later in our list.
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for info in info_rows:
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result[info['client']] = info
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# The word "aggegrated" here is possibly misleading.
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return result
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# It's really just the most recent client's info.
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user_statuses[user_key]['aggregated'] = dict(
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client=most_recent_info['client'],
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status=most_recent_info['status'],
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timestamp=most_recent_info['timestamp'],
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)
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return user_statuses
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def get_presence_for_user(user_profile_id: int,
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def get_presence_for_user(user_profile_id: int,
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slim_presence: bool=False) -> Dict[str, Dict[str, Any]]:
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slim_presence: bool=False) -> Dict[str, Dict[str, Any]]:
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