mirror of https://github.com/zulip/zulip.git
429 lines
16 KiB
Python
429 lines
16 KiB
Python
from __future__ import absolute_import
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from __future__ import print_function
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from functools import wraps
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from django.core.cache import cache as djcache
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from django.core.cache import caches
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from django.conf import settings
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from django.db.models import Q
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from django.core.cache.backends.base import BaseCache
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from typing import Any, Callable, Iterable, Optional, Union, TypeVar
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from zerver.lib.utils import statsd, statsd_key, make_safe_digest
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import subprocess
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import time
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import base64
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import random
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import sys
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import os
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import os.path
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import hashlib
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import six
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from six import text_type
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if False:
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from zerver.models import UserProfile, Realm, Message
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# These modules have to be imported for type annotations but
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# they cannot be imported at runtime due to cyclic dependency.
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FuncT = TypeVar('FuncT', bound=Callable[..., Any])
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class NotFoundInCache(Exception):
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pass
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remote_cache_time_start = 0.0
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remote_cache_total_time = 0.0
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remote_cache_total_requests = 0
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def get_remote_cache_time():
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# type: () -> float
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return remote_cache_total_time
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def get_remote_cache_requests():
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# type: () -> int
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return remote_cache_total_requests
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def remote_cache_stats_start():
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# type: () -> None
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global remote_cache_time_start
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remote_cache_time_start = time.time()
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def remote_cache_stats_finish():
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# type: () -> None
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global remote_cache_total_time
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global remote_cache_total_requests
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global remote_cache_time_start
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remote_cache_total_requests += 1
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remote_cache_total_time += (time.time() - remote_cache_time_start)
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def get_or_create_key_prefix():
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# type: () -> text_type
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if settings.TEST_SUITE:
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# This sets the prefix for the benefit of the Casper tests.
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# The Python tests overwrite KEY_PREFIX on each test, but use
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# this codepath as well, just to save running the more complex
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# code below for reading the normal key prefix.
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#
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# Having a fixed key is OK since we don't support running
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# multiple copies of the casper tests at the same time anyway.
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if settings.TORNADO_SERVER:
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return u'casper_tests:'
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else:
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return u'django_tests:'
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# directory `var` should exist in production
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subprocess.check_call(["mkdir", "-p", os.path.join(settings.DEPLOY_ROOT, "var")])
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filename = os.path.join(settings.DEPLOY_ROOT, "var", "remote_cache_prefix")
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try:
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fd = os.open(filename, os.O_CREAT | os.O_EXCL | os.O_RDWR, 0o444)
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random_hash = hashlib.sha256(text_type(random.getrandbits(256)).encode('utf-8')).digest()
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prefix = base64.b16encode(random_hash)[:32].decode('utf-8').lower() + ':'
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# This does close the underlying file
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with os.fdopen(fd, 'w') as f:
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f.write(prefix + "\n")
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except OSError:
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# The file already exists
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tries = 1
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while tries < 10:
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with open(filename, 'r') as f:
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prefix = f.readline()[:-1]
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if len(prefix) == 33:
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break
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tries += 1
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prefix = ''
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time.sleep(0.5)
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if not prefix:
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print("Could not read remote cache key prefix file")
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sys.exit(1)
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return prefix
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KEY_PREFIX = get_or_create_key_prefix() # type: text_type
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def bounce_key_prefix_for_testing(test_name):
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# type: (text_type) -> None
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global KEY_PREFIX
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KEY_PREFIX = test_name + u':' + text_type(os.getpid()) + u':'
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def get_cache_backend(cache_name):
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# type: (Optional[str]) -> BaseCache
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if cache_name is None:
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return djcache
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return caches[cache_name]
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def get_cache_with_key(keyfunc, cache_name=None):
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# type: (Any, Optional[str]) -> Any
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"""
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The main goal of this function getting value from the cache like in the "cache_with_key".
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A cache value can contain any data including the "None", so
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here used exception for case if value isn't found in the cache.
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"""
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def decorator(func):
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# type: (Callable[..., Any]) -> (Callable[..., Any])
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@wraps(func)
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def func_with_caching(*args, **kwargs):
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# type: (*Any, **Any) -> Callable[..., Any]
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key = keyfunc(*args, **kwargs)
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val = cache_get(key, cache_name=cache_name)
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if val is not None:
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return val[0]
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raise NotFoundInCache()
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return func_with_caching
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return decorator
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def cache_with_key(keyfunc, cache_name=None, timeout=None, with_statsd_key=None):
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# type: (Any, Optional[str], Optional[int], Optional[str]) -> Any
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# This function can't be typed perfectly because returning a generic function
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# isn't supported in mypy - https://github.com/python/mypy/issues/1551.
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"""Decorator which applies Django caching to a function.
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Decorator argument is a function which computes a cache key
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from the original function's arguments. You are responsible
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for avoiding collisions with other uses of this decorator or
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other uses of caching."""
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def decorator(func):
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# type: (Callable[..., Any]) -> (Callable[..., Any])
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@wraps(func)
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def func_with_caching(*args, **kwargs):
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# type: (*Any, **Any) -> Callable[..., Any]
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key = keyfunc(*args, **kwargs)
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val = cache_get(key, cache_name=cache_name)
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extra = ""
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if cache_name == 'database':
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extra = ".dbcache"
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if with_statsd_key is not None:
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metric_key = with_statsd_key
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else:
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metric_key = statsd_key(key)
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status = "hit" if val is not None else "miss"
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statsd.incr("cache%s.%s.%s" % (extra, metric_key, status))
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# Values are singleton tuples so that we can distinguish
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# a result of None from a missing key.
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if val is not None:
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return val[0]
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val = func(*args, **kwargs)
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cache_set(key, val, cache_name=cache_name, timeout=timeout)
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return val
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return func_with_caching
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return decorator
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def cache_set(key, val, cache_name=None, timeout=None):
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# type: (text_type, Any, Optional[str], Optional[int]) -> None
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remote_cache_stats_start()
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cache_backend = get_cache_backend(cache_name)
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cache_backend.set(KEY_PREFIX + key, (val,), timeout=timeout)
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remote_cache_stats_finish()
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def cache_get(key, cache_name=None):
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# type: (text_type, Optional[str]) -> Any
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remote_cache_stats_start()
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cache_backend = get_cache_backend(cache_name)
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ret = cache_backend.get(KEY_PREFIX + key)
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remote_cache_stats_finish()
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return ret
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def cache_get_many(keys, cache_name=None):
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# type: (List[text_type], Optional[str]) -> Dict[text_type, Any]
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keys = [KEY_PREFIX + key for key in keys]
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remote_cache_stats_start()
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ret = get_cache_backend(cache_name).get_many(keys)
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remote_cache_stats_finish()
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return dict([(key[len(KEY_PREFIX):], value) for key, value in ret.items()])
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def cache_set_many(items, cache_name=None, timeout=None):
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# type: (Dict[text_type, Any], Optional[str], Optional[int]) -> None
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new_items = {}
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for key in items:
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new_items[KEY_PREFIX + key] = items[key]
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items = new_items
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remote_cache_stats_start()
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get_cache_backend(cache_name).set_many(items, timeout=timeout)
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remote_cache_stats_finish()
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def cache_delete(key, cache_name=None):
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# type: (text_type, Optional[str]) -> None
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remote_cache_stats_start()
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get_cache_backend(cache_name).delete(KEY_PREFIX + key)
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remote_cache_stats_finish()
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def cache_delete_many(items, cache_name=None):
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# type: (Iterable[text_type], Optional[str]) -> None
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remote_cache_stats_start()
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get_cache_backend(cache_name).delete_many(
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KEY_PREFIX + item for item in items)
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remote_cache_stats_finish()
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# Required Arguments are as follows:
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# * object_ids: The list of object ids to look up
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# * cache_key_function: object_id => cache key
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# * query_function: [object_ids] => [objects from database]
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# Optional keyword arguments:
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# * setter: Function to call before storing items to cache (e.g. compression)
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# * extractor: Function to call on items returned from cache
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# (e.g. decompression). Should be the inverse of the setter
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# function.
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# * id_fetcher: Function mapping an object from database => object_id
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# (in case we're using a key more complex than obj.id)
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# * cache_transformer: Function mapping an object from database =>
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# value for cache (in case the values that we're caching are some
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# function of the objects, not the objects themselves)
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ObjKT = TypeVar('ObjKT', int, text_type)
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ItemT = Any # https://github.com/python/mypy/issues/1721
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CompressedItemT = Any # https://github.com/python/mypy/issues/1721
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def generic_bulk_cached_fetch(cache_key_function, # type: Callable[[ObjKT], text_type]
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query_function, # type: Callable[[List[ObjKT]], Iterable[Any]]
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object_ids, # type: Iterable[ObjKT]
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extractor=lambda obj: obj, # type: Callable[[CompressedItemT], ItemT]
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setter=lambda obj: obj, # type: Callable[[ItemT], CompressedItemT]
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id_fetcher=lambda obj: obj.id, # type: Callable[[Any], ObjKT]
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cache_transformer=lambda obj: obj # type: Callable[[Any], ItemT]
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):
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# type: (...) -> Dict[ObjKT, Any]
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cache_keys = {} # type: Dict[ObjKT, text_type]
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for object_id in object_ids:
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cache_keys[object_id] = cache_key_function(object_id)
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cached_objects = cache_get_many([cache_keys[object_id]
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for object_id in object_ids])
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for (key, val) in cached_objects.items():
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cached_objects[key] = extractor(cached_objects[key][0])
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needed_ids = [object_id for object_id in object_ids if
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cache_keys[object_id] not in cached_objects]
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db_objects = query_function(needed_ids)
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items_for_remote_cache = {} # type: Dict[text_type, Any]
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for obj in db_objects:
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key = cache_keys[id_fetcher(obj)]
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item = cache_transformer(obj)
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items_for_remote_cache[key] = (setter(item),)
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cached_objects[key] = item
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if len(items_for_remote_cache) > 0:
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cache_set_many(items_for_remote_cache)
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return dict((object_id, cached_objects[cache_keys[object_id]]) for object_id in object_ids
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if cache_keys[object_id] in cached_objects)
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def cache(func):
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# type: (FuncT) -> FuncT
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"""Decorator which applies Django caching to a function.
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Uses a key based on the function's name, filename, and
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the repr() of its arguments."""
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func_uniqifier = '%s-%s' % (func.__code__.co_filename, func.__name__) # type: ignore # https://github.com/python/mypy/issues/1923
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@wraps(func)
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def keyfunc(*args, **kwargs):
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# type: (*Any, **Any) -> str
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# Django complains about spaces because memcached rejects them
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key = func_uniqifier + repr((args, kwargs))
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return key.replace('-', '--').replace(' ', '-s')
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return cache_with_key(keyfunc)(func)
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def display_recipient_cache_key(recipient_id):
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# type: (int) -> text_type
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return u"display_recipient_dict:%d" % (recipient_id,)
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def user_profile_by_email_cache_key(email):
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# type: (text_type) -> text_type
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# See the comment in zerver/lib/avatar_hash.py:gravatar_hash for why we
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# are proactively encoding email addresses even though they will
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# with high likelihood be ASCII-only for the foreseeable future.
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return u'user_profile_by_email:%s' % (make_safe_digest(email.strip()),)
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def user_profile_by_id_cache_key(user_profile_id):
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# type: (int) -> text_type
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return u"user_profile_by_id:%s" % (user_profile_id,)
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# TODO: Refactor these cache helpers into another file that can import
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# models.py so that python3-style type annotations can also work.
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def cache_save_user_profile(user_profile):
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# type: (UserProfile) -> None
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cache_set(user_profile_by_id_cache_key(user_profile.id), user_profile, timeout=3600*24*7)
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active_user_dict_fields = ['id', 'full_name', 'short_name', 'email', 'is_realm_admin', 'is_bot'] # type: List[str]
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def active_user_dicts_in_realm_cache_key(realm):
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# type: (Realm) -> text_type
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return u"active_user_dicts_in_realm:%s" % (realm.id,)
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active_bot_dict_fields = ['id', 'full_name', 'short_name',
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'email', 'default_sending_stream__name',
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'default_events_register_stream__name',
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'default_all_public_streams', 'api_key',
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'bot_owner__email', 'avatar_source'] # type: List[str]
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def active_bot_dicts_in_realm_cache_key(realm):
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# type: (Realm) -> text_type
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return u"active_bot_dicts_in_realm:%s" % (realm.id,)
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def get_stream_cache_key(stream_name, realm):
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# type: (text_type, Union[Realm, int]) -> text_type
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from zerver.models import Realm
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if isinstance(realm, Realm):
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realm_id = realm.id
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else:
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realm_id = realm
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return u"stream_by_realm_and_name:%s:%s" % (
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realm_id, make_safe_digest(stream_name.strip().lower()))
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def delete_user_profile_caches(user_profiles):
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# type: (Iterable[UserProfile]) -> None
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keys = []
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for user_profile in user_profiles:
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keys.append(user_profile_by_email_cache_key(user_profile.email))
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keys.append(user_profile_by_id_cache_key(user_profile.id))
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cache_delete_many(keys)
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# Called by models.py to flush the user_profile cache whenever we save
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# a user_profile object
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def flush_user_profile(sender, **kwargs):
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# type: (Any, **Any) -> None
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user_profile = kwargs['instance']
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delete_user_profile_caches([user_profile])
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# Invalidate our active_users_in_realm info dict if any user has changed
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# the fields in the dict or become (in)active
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if kwargs.get('update_fields') is None or \
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len(set(active_user_dict_fields + ['is_active']) &
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set(kwargs['update_fields'])) > 0:
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cache_delete(active_user_dicts_in_realm_cache_key(user_profile.realm))
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# Invalidate our active_bots_in_realm info dict if any bot has
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# changed the fields in the dict or become (in)active
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if user_profile.is_bot and (kwargs['update_fields'] is None or
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(set(active_bot_dict_fields + ['is_active']) &
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set(kwargs['update_fields']))):
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cache_delete(active_bot_dicts_in_realm_cache_key(user_profile.realm))
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# Invalidate realm-wide alert words cache if any user in the realm has changed
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# alert words
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if kwargs.get('update_fields') is None or "alert_words" in kwargs['update_fields']:
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cache_delete(realm_alert_words_cache_key(user_profile.realm))
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# Called by models.py to flush various caches whenever we save
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# a Realm object. The main tricky thing here is that Realm info is
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# generally cached indirectly through user_profile objects.
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def flush_realm(sender, **kwargs):
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# type: (Any, **Any) -> None
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realm = kwargs['instance']
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users = realm.get_active_users()
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delete_user_profile_caches(users)
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if realm.deactivated:
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cache_delete(active_user_dicts_in_realm_cache_key(realm))
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cache_delete(active_bot_dicts_in_realm_cache_key(realm))
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cache_delete(realm_alert_words_cache_key(realm))
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def realm_alert_words_cache_key(realm):
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# type: (Realm) -> text_type
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return u"realm_alert_words:%s" % (realm.domain,)
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# Called by models.py to flush the stream cache whenever we save a stream
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# object.
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def flush_stream(sender, **kwargs):
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# type: (Any, **Any) -> None
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from zerver.models import UserProfile
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stream = kwargs['instance']
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items_for_remote_cache = {}
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items_for_remote_cache[get_stream_cache_key(stream.name, stream.realm)] = (stream,)
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cache_set_many(items_for_remote_cache)
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if kwargs.get('update_fields') is None or 'name' in kwargs['update_fields'] and \
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UserProfile.objects.filter(
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Q(default_sending_stream=stream) |
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Q(default_events_register_stream=stream)
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).exists():
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cache_delete(active_bot_dicts_in_realm_cache_key(stream.realm))
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# TODO: Rename to_dict_cache_key_id and to_dict_cache_key
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def to_dict_cache_key_id(message_id, apply_markdown):
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# type: (int, bool) -> text_type
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return u'message_dict:%d:%d' % (message_id, apply_markdown)
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def to_dict_cache_key(message, apply_markdown):
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# type: (Message, bool) -> text_type
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return to_dict_cache_key_id(message.id, apply_markdown)
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def flush_message(sender, **kwargs):
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# type: (Any, **Any) -> None
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message = kwargs['instance']
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cache_delete(to_dict_cache_key(message, False))
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cache_delete(to_dict_cache_key(message, True))
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