zulip/zerver/lib/cache.py

458 lines
17 KiB
Python

from __future__ import absolute_import
from __future__ import print_function
from functools import wraps
from django.core.cache import cache as djcache
from django.core.cache import caches
from django.conf import settings
from django.db.models import Q
from django.core.cache.backends.base import BaseCache
from typing import Any, Callable, Dict, Iterable, List, Optional, Union, TypeVar, Text
from zerver.lib.utils import statsd, statsd_key, make_safe_digest
import subprocess
import time
import base64
import random
import sys
import os
import os.path
import hashlib
import six
if False:
from zerver.models import UserProfile, Realm, Message
# These modules have to be imported for type annotations but
# they cannot be imported at runtime due to cyclic dependency.
FuncT = TypeVar('FuncT', bound=Callable[..., Any])
class NotFoundInCache(Exception):
pass
remote_cache_time_start = 0.0
remote_cache_total_time = 0.0
remote_cache_total_requests = 0
def get_remote_cache_time():
# type: () -> float
return remote_cache_total_time
def get_remote_cache_requests():
# type: () -> int
return remote_cache_total_requests
def remote_cache_stats_start():
# type: () -> None
global remote_cache_time_start
remote_cache_time_start = time.time()
def remote_cache_stats_finish():
# type: () -> None
global remote_cache_total_time
global remote_cache_total_requests
global remote_cache_time_start
remote_cache_total_requests += 1
remote_cache_total_time += (time.time() - remote_cache_time_start)
def get_or_create_key_prefix():
# type: () -> Text
if settings.CASPER_TESTS:
# This sets the prefix for the benefit of the Casper tests.
#
# Having a fixed key is OK since we don't support running
# multiple copies of the casper tests at the same time anyway.
return u'casper_tests:'
elif settings.TEST_SUITE:
# The Python tests overwrite KEY_PREFIX on each test, but use
# this codepath as well, just to save running the more complex
# code below for reading the normal key prefix.
return u'django_tests_unused:'
# directory `var` should exist in production
subprocess.check_call(["mkdir", "-p", os.path.join(settings.DEPLOY_ROOT, "var")])
filename = os.path.join(settings.DEPLOY_ROOT, "var", "remote_cache_prefix")
try:
fd = os.open(filename, os.O_CREAT | os.O_EXCL | os.O_RDWR, 0o444)
random_hash = hashlib.sha256(Text(random.getrandbits(256)).encode('utf-8')).digest()
prefix = base64.b16encode(random_hash)[:32].decode('utf-8').lower() + ':'
# This does close the underlying file
with os.fdopen(fd, 'w') as f:
f.write(prefix + "\n")
except OSError:
# The file already exists
tries = 1
while tries < 10:
with open(filename, 'r') as f:
prefix = f.readline()[:-1]
if len(prefix) == 33:
break
tries += 1
prefix = ''
time.sleep(0.5)
if not prefix:
print("Could not read remote cache key prefix file")
sys.exit(1)
return prefix
KEY_PREFIX = get_or_create_key_prefix() # type: Text
def bounce_key_prefix_for_testing(test_name):
# type: (Text) -> None
global KEY_PREFIX
KEY_PREFIX = test_name + u':' + Text(os.getpid()) + u':'
# We are taking the hash of the KEY_PREFIX to decrease the size of the key.
# Memcached keys should have a length of less than 256.
KEY_PREFIX = hashlib.sha1(KEY_PREFIX.encode('utf-8')).hexdigest()
def get_cache_backend(cache_name):
# type: (Optional[str]) -> BaseCache
if cache_name is None:
return djcache
return caches[cache_name]
def get_cache_with_key(keyfunc, cache_name=None):
# type: (Any, Optional[str]) -> Any
"""
The main goal of this function getting value from the cache like in the "cache_with_key".
A cache value can contain any data including the "None", so
here used exception for case if value isn't found in the cache.
"""
def decorator(func):
# type: (Callable[..., Any]) -> (Callable[..., Any])
@wraps(func)
def func_with_caching(*args, **kwargs):
# type: (*Any, **Any) -> Callable[..., Any]
key = keyfunc(*args, **kwargs)
val = cache_get(key, cache_name=cache_name)
if val is not None:
return val[0]
raise NotFoundInCache()
return func_with_caching
return decorator
def cache_with_key(keyfunc, cache_name=None, timeout=None, with_statsd_key=None):
# type: (Any, Optional[str], Optional[int], Optional[str]) -> Any
# This function can't be typed perfectly because returning a generic function
# isn't supported in mypy - https://github.com/python/mypy/issues/1551.
"""Decorator which applies Django caching to a function.
Decorator argument is a function which computes a cache key
from the original function's arguments. You are responsible
for avoiding collisions with other uses of this decorator or
other uses of caching."""
def decorator(func):
# type: (Callable[..., Any]) -> (Callable[..., Any])
@wraps(func)
def func_with_caching(*args, **kwargs):
# type: (*Any, **Any) -> Any
key = keyfunc(*args, **kwargs)
val = cache_get(key, cache_name=cache_name)
extra = ""
if cache_name == 'database':
extra = ".dbcache"
if with_statsd_key is not None:
metric_key = with_statsd_key
else:
metric_key = statsd_key(key)
status = "hit" if val is not None else "miss"
statsd.incr("cache%s.%s.%s" % (extra, metric_key, status))
# Values are singleton tuples so that we can distinguish
# a result of None from a missing key.
if val is not None:
return val[0]
val = func(*args, **kwargs)
cache_set(key, val, cache_name=cache_name, timeout=timeout)
return val
return func_with_caching
return decorator
def cache_set(key, val, cache_name=None, timeout=None):
# type: (Text, Any, Optional[str], Optional[int]) -> None
remote_cache_stats_start()
cache_backend = get_cache_backend(cache_name)
cache_backend.set(KEY_PREFIX + key, (val,), timeout=timeout)
remote_cache_stats_finish()
def cache_get(key, cache_name=None):
# type: (Text, Optional[str]) -> Any
remote_cache_stats_start()
cache_backend = get_cache_backend(cache_name)
ret = cache_backend.get(KEY_PREFIX + key)
remote_cache_stats_finish()
return ret
def cache_get_many(keys, cache_name=None):
# type: (List[Text], Optional[str]) -> Dict[Text, Any]
keys = [KEY_PREFIX + key for key in keys]
remote_cache_stats_start()
ret = get_cache_backend(cache_name).get_many(keys)
remote_cache_stats_finish()
return dict([(key[len(KEY_PREFIX):], value) for key, value in ret.items()])
def cache_set_many(items, cache_name=None, timeout=None):
# type: (Dict[Text, Any], Optional[str], Optional[int]) -> None
new_items = {}
for key in items:
new_items[KEY_PREFIX + key] = items[key]
items = new_items
remote_cache_stats_start()
get_cache_backend(cache_name).set_many(items, timeout=timeout)
remote_cache_stats_finish()
def cache_delete(key, cache_name=None):
# type: (Text, Optional[str]) -> None
remote_cache_stats_start()
get_cache_backend(cache_name).delete(KEY_PREFIX + key)
remote_cache_stats_finish()
def cache_delete_many(items, cache_name=None):
# type: (Iterable[Text], Optional[str]) -> None
remote_cache_stats_start()
get_cache_backend(cache_name).delete_many(
KEY_PREFIX + item for item in items)
remote_cache_stats_finish()
# Required Arguments are as follows:
# * object_ids: The list of object ids to look up
# * cache_key_function: object_id => cache key
# * query_function: [object_ids] => [objects from database]
# Optional keyword arguments:
# * setter: Function to call before storing items to cache (e.g. compression)
# * extractor: Function to call on items returned from cache
# (e.g. decompression). Should be the inverse of the setter
# function.
# * id_fetcher: Function mapping an object from database => object_id
# (in case we're using a key more complex than obj.id)
# * cache_transformer: Function mapping an object from database =>
# value for cache (in case the values that we're caching are some
# function of the objects, not the objects themselves)
ObjKT = TypeVar('ObjKT', int, Text)
ItemT = Any # https://github.com/python/mypy/issues/1721
CompressedItemT = Any # https://github.com/python/mypy/issues/1721
def generic_bulk_cached_fetch(cache_key_function, # type: Callable[[ObjKT], Text]
query_function, # type: Callable[[List[ObjKT]], Iterable[Any]]
object_ids, # type: Iterable[ObjKT]
extractor=lambda obj: obj, # type: Callable[[CompressedItemT], ItemT]
setter=lambda obj: obj, # type: Callable[[ItemT], CompressedItemT]
id_fetcher=lambda obj: obj.id, # type: Callable[[Any], ObjKT]
cache_transformer=lambda obj: obj # type: Callable[[Any], ItemT]
):
# type: (...) -> Dict[ObjKT, Any]
cache_keys = {} # type: Dict[ObjKT, Text]
for object_id in object_ids:
cache_keys[object_id] = cache_key_function(object_id)
cached_objects = cache_get_many([cache_keys[object_id]
for object_id in object_ids])
for (key, val) in cached_objects.items():
cached_objects[key] = extractor(cached_objects[key][0])
needed_ids = [object_id for object_id in object_ids if
cache_keys[object_id] not in cached_objects]
db_objects = query_function(needed_ids)
items_for_remote_cache = {} # type: Dict[Text, Any]
for obj in db_objects:
key = cache_keys[id_fetcher(obj)]
item = cache_transformer(obj)
items_for_remote_cache[key] = (setter(item),)
cached_objects[key] = item
if len(items_for_remote_cache) > 0:
cache_set_many(items_for_remote_cache)
return dict((object_id, cached_objects[cache_keys[object_id]]) for object_id in object_ids
if cache_keys[object_id] in cached_objects)
def cache(func):
# type: (FuncT) -> FuncT
"""Decorator which applies Django caching to a function.
Uses a key based on the function's name, filename, and
the repr() of its arguments."""
func_uniqifier = '%s-%s' % (func.__code__.co_filename, func.__name__)
@wraps(func)
def keyfunc(*args, **kwargs):
# type: (*Any, **Any) -> str
# Django complains about spaces because memcached rejects them
key = func_uniqifier + repr((args, kwargs))
return key.replace('-', '--').replace(' ', '-s')
return cache_with_key(keyfunc)(func)
def display_recipient_cache_key(recipient_id):
# type: (int) -> Text
return u"display_recipient_dict:%d" % (recipient_id,)
def user_profile_by_email_cache_key(email):
# type: (Text) -> Text
# See the comment in zerver/lib/avatar_hash.py:gravatar_hash for why we
# are proactively encoding email addresses even though they will
# with high likelihood be ASCII-only for the foreseeable future.
return u'user_profile_by_email:%s' % (make_safe_digest(email.strip()),)
def user_profile_cache_key(email, realm):
# type: (Text, Realm) -> Text
return u"user_profile:%s:%s" % (make_safe_digest(email.strip()), realm.id,)
def bot_profile_cache_key(email):
# type: (Text) -> Text
return u"bot_profile:%s" % (make_safe_digest(email.strip()))
def user_profile_by_id_cache_key(user_profile_id):
# type: (int) -> Text
return u"user_profile_by_id:%s" % (user_profile_id,)
def user_profile_by_api_key_cache_key(api_key):
# type: (Text) -> Text
return u"user_profile_by_api_key:%s" % (api_key,)
# TODO: Refactor these cache helpers into another file that can import
# models.py so that python v3 style type annotations can also work.
active_user_dict_fields = [
'id', 'full_name', 'short_name', 'email',
'avatar_source', 'avatar_version',
'is_realm_admin', 'is_bot', 'realm_id', 'timezone'] # type: List[str]
def active_user_dicts_in_realm_cache_key(realm):
# type: (Realm) -> Text
return u"active_user_dicts_in_realm:%s" % (realm.id,)
bot_dict_fields = ['id', 'full_name', 'short_name', 'bot_type', 'email',
'is_active', 'default_sending_stream__name',
'realm_id',
'default_events_register_stream__name',
'default_all_public_streams', 'api_key',
'bot_owner__email', 'avatar_source',
'avatar_version'] # type: List[str]
def bot_dicts_in_realm_cache_key(realm):
# type: (Realm) -> Text
return u"bot_dicts_in_realm:%s" % (realm.id,)
def get_stream_cache_key(stream_name, realm):
# type: (Text, Union[Realm, int]) -> Text
from zerver.models import Realm
if isinstance(realm, Realm):
realm_id = realm.id
else:
realm_id = realm
return u"stream_by_realm_and_name:%s:%s" % (
realm_id, make_safe_digest(stream_name.strip().lower()))
def delete_user_profile_caches(user_profiles):
# type: (Iterable[UserProfile]) -> None
keys = []
for user_profile in user_profiles:
keys.append(user_profile_by_email_cache_key(user_profile.email))
keys.append(user_profile_by_id_cache_key(user_profile.id))
keys.append(user_profile_by_api_key_cache_key(user_profile.api_key))
keys.append(user_profile_cache_key(user_profile.email, user_profile.realm))
cache_delete_many(keys)
def delete_display_recipient_cache(user_profile):
# type: (UserProfile) -> None
from zerver.models import Subscription # We need to import here to avoid cyclic dependency.
recipient_ids = Subscription.objects.filter(user_profile=user_profile)
recipient_ids = recipient_ids.values_list('recipient_id', flat=True)
keys = [display_recipient_cache_key(rid) for rid in recipient_ids]
cache_delete_many(keys)
# Called by models.py to flush the user_profile cache whenever we save
# a user_profile object
def flush_user_profile(sender, **kwargs):
# type: (Any, **Any) -> None
user_profile = kwargs['instance']
delete_user_profile_caches([user_profile])
# Invalidate our active_users_in_realm info dict if any user has changed
# the fields in the dict or become (in)active
if kwargs.get('update_fields') is None or \
len(set(active_user_dict_fields + ['is_active', 'email']) &
set(kwargs['update_fields'])) > 0:
cache_delete(active_user_dicts_in_realm_cache_key(user_profile.realm))
if kwargs.get('updated_fields') is None or \
'email' in kwargs['update_fields']:
delete_display_recipient_cache(user_profile)
# Invalidate our bots_in_realm info dict if any bot has
# changed the fields in the dict or become (in)active
if user_profile.is_bot and (kwargs['update_fields'] is None or
(set(bot_dict_fields) & set(kwargs['update_fields']))):
cache_delete(bot_dicts_in_realm_cache_key(user_profile.realm))
# Invalidate realm-wide alert words cache if any user in the realm has changed
# alert words
if kwargs.get('update_fields') is None or "alert_words" in kwargs['update_fields']:
cache_delete(realm_alert_words_cache_key(user_profile.realm))
# Called by models.py to flush various caches whenever we save
# a Realm object. The main tricky thing here is that Realm info is
# generally cached indirectly through user_profile objects.
def flush_realm(sender, **kwargs):
# type: (Any, **Any) -> None
realm = kwargs['instance']
users = realm.get_active_users()
delete_user_profile_caches(users)
if realm.deactivated:
cache_delete(active_user_dicts_in_realm_cache_key(realm))
cache_delete(bot_dicts_in_realm_cache_key(realm))
cache_delete(realm_alert_words_cache_key(realm))
def realm_alert_words_cache_key(realm):
# type: (Realm) -> Text
return u"realm_alert_words:%s" % (realm.string_id,)
# Called by models.py to flush the stream cache whenever we save a stream
# object.
def flush_stream(sender, **kwargs):
# type: (Any, **Any) -> None
from zerver.models import UserProfile
stream = kwargs['instance']
items_for_remote_cache = {}
items_for_remote_cache[get_stream_cache_key(stream.name, stream.realm)] = (stream,)
cache_set_many(items_for_remote_cache)
if kwargs.get('update_fields') is None or 'name' in kwargs['update_fields'] and \
UserProfile.objects.filter(
Q(default_sending_stream=stream) |
Q(default_events_register_stream=stream)).exists():
cache_delete(bot_dicts_in_realm_cache_key(stream.realm))
# TODO: Rename to_dict_cache_key_id and to_dict_cache_key
def to_dict_cache_key_id(message_id, apply_markdown):
# type: (int, bool) -> Text
return u'message_dict:%d:%d' % (message_id, apply_markdown)
def to_dict_cache_key(message, apply_markdown):
# type: (Message, bool) -> Text
return to_dict_cache_key_id(message.id, apply_markdown)
def flush_message(sender, **kwargs):
# type: (Any, **Any) -> None
message = kwargs['instance']
cache_delete(to_dict_cache_key(message, False))
cache_delete(to_dict_cache_key(message, True))