OpenSlides/server/openslides/utils/cache_providers.py

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import functools
import hashlib
from collections import defaultdict
from textwrap import dedent
from typing import Any, Callable, Coroutine, Dict, List, Optional, Set, Tuple
from django.core.exceptions import ImproperlyConfigured
from typing_extensions import Protocol
from . import logging
from .redis import use_redis
from .schema_version import SchemaVersion
from .utils import split_element_id, str_dict_to_bytes
logger = logging.getLogger(__name__)
if use_redis:
from .redis import aioredis, get_connection
class CacheReset(Exception):
pass
class ElementCacheProvider(Protocol):
"""
Base class for cache provider.
See RedisCacheProvider as reverence implementation.
"""
def __init__(self, ensure_cache: Callable[[], Coroutine[Any, Any, None]]) -> None:
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...
async def ensure_cache(self) -> None:
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...
async def clear_cache(self) -> None:
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...
async def reset_full_cache(
self, data: Dict[str, str], default_change_id: int
) -> None:
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...
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async def add_to_full_data(self, data: Dict[str, str]) -> None:
...
async def data_exists(self) -> bool:
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...
async def set_cache_ready(self) -> None:
...
async def get_all_data(self) -> Dict[bytes, bytes]:
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...
async def get_all_data_with_max_change_id(self) -> Tuple[int, Dict[bytes, bytes]]:
...
async def get_collection_data(self, collection: str) -> Dict[int, bytes]:
...
async def get_element_data(self, element_id: str) -> Optional[bytes]:
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...
async def add_changed_elements(
self, changed_elements: List[str], deleted_element_ids: List[str]
) -> int:
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...
async def get_data_since(
self, change_id: int
) -> Tuple[int, Dict[str, List[bytes]], List[str]]:
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...
async def get_current_change_id(self) -> int:
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...
async def get_lowest_change_id(self) -> int:
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...
async def get_schema_version(self) -> Optional[SchemaVersion]:
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...
async def set_schema_version(self, schema_version: SchemaVersion) -> None:
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...
def ensure_cache_wrapper() -> Callable[[Callable[..., Any]], Callable[..., Any]]:
"""
Wraps a cache function to ensure, that the cache is filled.
When the function raises a CacheReset-Error the cache will be ensured (call
to `ensure_cache`) and the method will be recalled. This is done, until the
operation was successful.
"""
def wrapper(func: Callable[..., Any]) -> Callable[..., Any]:
@functools.wraps(func)
async def wrapped(
cache_provider: ElementCacheProvider, *args: Any, **kwargs: Any
) -> Any:
success = False
while not success:
try:
result = await func(cache_provider, *args, **kwargs)
success = True
except CacheReset:
logger.warn(
f"Redis was flushed before method '{func.__name__}'. Ensures cache now."
)
await cache_provider.ensure_cache()
return result
return wrapped
return wrapper
class RedisCacheProvider:
"""
Cache provider that loads and saves the data to redis.
"""
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full_data_cache_key: str = "full_data"
change_id_cache_key: str = "change_id"
schema_cache_key: str = "schema"
cache_ready_key: str = "cache_ready"
# All lua-scripts used by this provider. Every entry is a Tuple (str, bool) with the
# script and an ensure_cache-indicator. If the indicator is True, a short ensure_cache-script
# will be prepended to the script which raises a CacheReset, if the full data cache is empty.
# This requires the full_data_cache_key to be the first key given in `keys`!
# All scripts are dedented and hashed for faster execution. Convention: The keys of this
# member are the methods that needs these scripts.
scripts = {
"clear_cache": (
"return redis.call('del', 'fake_key', unpack(redis.call('keys', ARGV[1])))",
False,
),
"get_all_data": ("return redis.call('hgetall', KEYS[1])", True),
"get_all_data_with_max_change_id": (
"""
local tmp = redis.call('zrevrangebyscore', KEYS[2], '+inf', '-inf', 'WITHSCORES', 'LIMIT', 0, 1)
local max_change_id
if next(tmp) == nil then
-- The key does not exist
return redis.error_reply("cache_reset")
else
max_change_id = tmp[2]
end
local all_data = redis.call('hgetall', KEYS[1])
table.insert(all_data, 'max_change_id')
table.insert(all_data, max_change_id)
return all_data
""",
True,
),
"get_collection_data": (
"""
local cursor = 0
local collection = {}
repeat
local result = redis.call('HSCAN', KEYS[1], cursor, 'MATCH', ARGV[1])
cursor = tonumber(result[1])
for _, v in pairs(result[2]) do
table.insert(collection, v)
end
until cursor == 0
return collection
""",
True,
),
"get_element_data": ("return redis.call('hget', KEYS[1], ARGV[1])", True),
"add_changed_elements": (
# KEYS[1]: full data cache key
# KEYS[2]: change id cache key
# ARGV[1]: amount changed elements
# ARGV[2]: amount deleted elements
# ARGV[3..(ARGV[1]+2)]: changed_elements (element_id, element, element_id, element, ...)
# ARGV[(3+ARGV[1])..(ARGV[1]+ARGV[2]+2)]: deleted_elements (element_id, element_id, ...)
"""
-- Generate a new change_id
local tmp = redis.call('zrevrangebyscore', KEYS[2], '+inf', '-inf', 'WITHSCORES', 'LIMIT', 0, 1)
local change_id
if next(tmp) == nil then
-- The key does not exist
return redis.error_reply("cache_reset")
else
change_id = tmp[2] + 1
end
local nc = tonumber(ARGV[1])
local nd = tonumber(ARGV[2])
local i, max, batch_counter
local change_id_data -- change_id, element_id, change_id, element_id, ...
-- Add changed_elements to the cache and sorted set using batches of 1000
-- values in unpack() (see #5386)
local elements -- element_id, element, element_id, element, ...
if (nc > 0) then
i = 3
max = 3 + nc
while (i < max) do
change_id_data = {}
elements = {}
batch_counter = 1
while (i < max and batch_counter <= 1000) do
change_id_data[batch_counter] = change_id
change_id_data[batch_counter + 1] = ARGV[i]
elements[batch_counter] = ARGV[i]
elements[batch_counter + 1] = ARGV[i + 1]
batch_counter = batch_counter + 2
i = i + 2
end
if (#change_id_data > 0) then -- so is #elements > 0
redis.call('hmset', KEYS[1], unpack(elements))
redis.call('zadd', KEYS[2], unpack(change_id_data))
end
end
end
-- Delete deleted_element_ids and add them to sorted set
local element_ids -- element_id, element_id, ...
local element_ids_counter
if (nd > 0) then
i = 3 + nc
max = 3 + nc + nd
while (i < max) do
change_id_data = {}
element_ids = {}
batch_counter = 1
element_ids_counter = 1
while (i < max and batch_counter <= 1000) do
change_id_data[batch_counter] = change_id
change_id_data[batch_counter + 1] = ARGV[i]
element_ids[element_ids_counter] = ARGV[i]
batch_counter = batch_counter + 2
element_ids_counter = element_ids_counter + 1
i = i + 1
end
if (#change_id_data > 0) then -- so is #element_ids > 0
redis.call('hdel', KEYS[1], unpack(element_ids))
redis.call('zadd', KEYS[2], unpack(change_id_data))
end
end
end
return change_id
""",
True,
),
"get_data_since": (
"""
-- get max change id
local tmp = redis.call('zrevrangebyscore', KEYS[2], '+inf', '-inf', 'WITHSCORES', 'LIMIT', 0, 1)
local max_change_id
if next(tmp) == nil then
-- The key does not exist
return redis.error_reply("cache_reset")
else
max_change_id = tmp[2]
end
-- Get change ids of changed elements
local element_ids = redis.call('zrangebyscore', KEYS[2], ARGV[1], max_change_id)
-- Save elements in array. First is the max_change_id with the key "max_change_id"
-- Than rotate element_id and element_json. This is ocnverted into a dict in python code.
local elements = {}
table.insert(elements, 'max_change_id')
table.insert(elements, max_change_id)
for _, element_id in pairs(element_ids) do
table.insert(elements, element_id)
table.insert(elements, redis.call('hget', KEYS[1], element_id))
end
return elements
""",
True,
),
}
def __init__(self, ensure_cache: Callable[[], Coroutine[Any, Any, None]]) -> None:
self._ensure_cache = ensure_cache
# hash all scripts and remove indentation.
for key in self.scripts.keys():
script, add_ensure_cache = self.scripts[key]
script = dedent(script)
if add_ensure_cache:
script = (
dedent(
"""
local exist = redis.call('exists', KEYS[1])
if (exist == 0) then
redis.log(redis.LOG_WARNING, "empty: "..KEYS[1])
return redis.error_reply("cache_reset")
end
"""
)
+ script
)
self.scripts[key] = (script, add_ensure_cache)
self._script_hashes = {
key: hashlib.sha1(script.encode()).hexdigest()
for key, (script, _) in self.scripts.items()
}
async def ensure_cache(self) -> None:
await self._ensure_cache()
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async def clear_cache(self) -> None:
"""
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Deleted all cache entries created with this element cache.
"""
await self.eval("clear_cache", keys=[], args=["*"])
async def reset_full_cache(
self, data: Dict[str, str], default_change_id: int
) -> None:
"""
Deletes the full_data_cache and write new data in it. Clears the change id key.
"""
async with get_connection() as redis:
tr = redis.multi_exec()
tr.delete(self.cache_ready_key)
tr.delete(self.change_id_cache_key)
tr.delete(self.full_data_cache_key)
tr.hmset_dict(self.full_data_cache_key, data)
tr.zadd(
self.change_id_cache_key, default_change_id, "_config:lowest_change_id"
)
await tr.execute()
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async def add_to_full_data(self, data: Dict[str, str]) -> None:
async with get_connection() as redis:
await redis.hmset_dict(self.full_data_cache_key, data)
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async def data_exists(self) -> bool:
"""
Returns True, when there is data in the cache.
"""
async with get_connection(read_only=True) as redis:
return (await redis.get(self.cache_ready_key)) is not None
# return await redis.exists(self.full_data_cache_key) and bool(
# await redis.zrangebyscore(
# self.change_id_cache_key, withscores=True, count=1, offset=0
# )
# )
async def set_cache_ready(self) -> None:
async with get_connection(read_only=False) as redis:
await redis.set(self.cache_ready_key, "ok")
@ensure_cache_wrapper()
async def get_all_data(self) -> Dict[bytes, bytes]:
"""
Returns all data from the full_data_cache in a mapping from element_id to the element.
"""
return await aioredis.util.wait_make_dict(
self.eval("get_all_data", keys=[self.full_data_cache_key], read_only=True)
)
@ensure_cache_wrapper()
async def get_all_data_with_max_change_id(self) -> Tuple[int, Dict[bytes, bytes]]:
"""
Returns all data from the full_data_cache in a mapping from element_id to the element and
the max change id.
"""
all_data = await aioredis.util.wait_make_dict(
self.eval(
"get_all_data_with_max_change_id",
keys=[self.full_data_cache_key, self.change_id_cache_key],
read_only=True,
)
)
max_change_id = int(all_data.pop(b"max_change_id"))
return max_change_id, all_data
@ensure_cache_wrapper()
async def get_collection_data(self, collection: str) -> Dict[int, bytes]:
"""
Returns all elements for a collection from the cache. The data is mapped
from element_id to the element.
"""
response = await self.eval(
"get_collection_data",
[self.full_data_cache_key],
[f"{collection}:*"],
read_only=True,
)
collection_data = {}
for i in range(0, len(response), 2):
_, id = split_element_id(response[i])
collection_data[id] = response[i + 1]
return collection_data
@ensure_cache_wrapper()
async def get_element_data(self, element_id: str) -> Optional[bytes]:
"""
Returns one element from the cache. Returns None, when the element does not exist.
"""
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return await self.eval(
"get_element_data", [self.full_data_cache_key], [element_id], read_only=True
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)
@ensure_cache_wrapper()
async def add_changed_elements(
self, changed_elements: List[str], deleted_element_ids: List[str]
) -> int:
"""
Modified the full_data_cache to insert the changed_elements and removes the
deleted_element_ids (in this order). Generates a new change_id and inserts all
element_ids (changed and deleted) with the change_id into the change_id_cache.
The newly generated change_id is returned.
"""
return int(
await self.eval(
"add_changed_elements",
keys=[self.full_data_cache_key, self.change_id_cache_key],
args=[
len(changed_elements),
len(deleted_element_ids),
*(changed_elements + deleted_element_ids),
],
)
)
@ensure_cache_wrapper()
async def get_data_since(
self, change_id: int
) -> Tuple[int, Dict[str, List[bytes]], List[str]]:
"""
Returns all elements since a change_id (included) and until the max_change_id (included).
The returend value is a two element tuple. The first value is a dict the elements where
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the key is the collection and the value a list of (json-) encoded elements. The
second element is a list of element_ids, that have been deleted since the change_id.
"""
changed_elements: Dict[str, List[bytes]] = defaultdict(list)
deleted_elements: List[str] = []
# lua script that returns gets all element_ids from change_id_cache_key
# and then uses each element_id on full_data or restricted_data.
# It returns a list where the odd values are the change_id and the
# even values the element as json. The function wait_make_dict creates
# a python dict from the returned list.
elements: Dict[bytes, Optional[bytes]] = await aioredis.util.wait_make_dict(
self.eval(
"get_data_since",
keys=[self.full_data_cache_key, self.change_id_cache_key],
args=[change_id],
read_only=True,
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)
)
max_change_id = int(elements[b"max_change_id"].decode()) # type: ignore
for element_id, element_json in elements.items():
if element_id.startswith(b"_config") or element_id == b"max_change_id":
# Ignore config values from the change_id cache key
continue
if element_json is None:
# The element is not in the cache. It has to be deleted.
deleted_elements.append(element_id.decode())
else:
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collection, id = split_element_id(element_id)
changed_elements[collection].append(element_json)
return max_change_id, changed_elements, deleted_elements
@ensure_cache_wrapper()
async def get_current_change_id(self) -> int:
"""
Get the highest change_id from redis.
"""
async with get_connection(read_only=True) as redis:
value = await redis.zrevrangebyscore(
self.change_id_cache_key, withscores=True, count=1, offset=0
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)
# Return the score (second element) of the first (and only) element, if exists.
if not value:
raise CacheReset()
return value[0][1]
@ensure_cache_wrapper()
async def get_lowest_change_id(self) -> int:
"""
Get the lowest change_id from redis.
"""
async with get_connection(read_only=True) as redis:
value = await redis.zscore(
self.change_id_cache_key, "_config:lowest_change_id"
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)
if not value:
raise CacheReset()
return value
async def get_schema_version(self) -> Optional[SchemaVersion]:
""" Retrieves the schema version of the cache or None, if not existent """
async with get_connection(read_only=True) as redis:
try:
schema_version = await redis.hgetall(self.schema_cache_key)
except aioredis.errors.ReplyError:
await redis.delete(self.schema_cache_key)
return None
if not schema_version:
return None
return {
"migration": int(schema_version[b"migration"].decode()),
"config": int(schema_version[b"config"].decode()),
"db": schema_version[b"db"].decode(),
}
async def set_schema_version(self, schema_version: SchemaVersion) -> None:
""" Sets the schema version for this cache. """
async with get_connection() as redis:
await redis.hmset_dict(self.schema_cache_key, schema_version)
async def eval(
self,
script_name: str,
keys: List[str] = [],
args: List[Any] = [],
read_only: bool = False,
) -> Any:
"""
Runs a lua script in redis. This wrapper around redis.eval tries to make
usage of redis script cache. First the hash is send to the server and if
the script is not present there (NOSCRIPT error) the actual script will be
send.
If the script uses the ensure_cache-prefix, the first key must be the full_data
cache key. This is checked here.
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Also this method incudes the custom "CacheReset" error, which will be raised in
python, if the lua-script returns a "cache_reset" string as an error response.
"""
hash = self._script_hashes[script_name]
if self.scripts[script_name][1] and not keys[0] == self.full_data_cache_key:
raise ImproperlyConfigured(
"A script with a ensure_cache prefix must have the full_data cache key as its first key"
)
async with get_connection(read_only=read_only) as redis:
try:
Redis: Wait for replication on writes Since channels_redis does not support dedicated read-redis instances, the autoupdate message may be received before the data was replicated. All workers read the autoupdate message from the write host, so there is a race between getting this message and a finished replication. For large payloads, the replication is slower in the most cases (even more in a distributed setup, where the master and replica are on different nodes). The easy way is to wait for replication. But there is one difficulty: The number of replicas has to be known. There is a new settings-variable "AMOUNT_REPLICAS" which defaults to 1. It needs to be set correctly! If it is too high, every autoupdate will be delayed by 1 seconds because of a timeout witing for non-existent replicas. If it is too low, some autoupdates may be wrong (and not detectable by the client!) becuase of reading from non-synchronised relicas. The other possibility is to fork channel_redis and add the feature of a read-only redis. This ould help, because on a single redis instance all commands are ordered: First, the data is synced, then the autoupdate message. Attention: This means, if redis-replicas are scaled up, one must make sure to read from the same instance. I think this is not possible in the way how dockers overlay networks work. The only way would be to open one connection and reuse the connection from channels_redis in OpenSlides. This would mean a heavy integration of channels_redis (meaning including the source code in our repo). For the first fix, this one is easy and should work.
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result = await redis.evalsha(hash, keys, args)
except aioredis.errors.ReplyError as e:
if str(e).startswith("NOSCRIPT"):
Redis: Wait for replication on writes Since channels_redis does not support dedicated read-redis instances, the autoupdate message may be received before the data was replicated. All workers read the autoupdate message from the write host, so there is a race between getting this message and a finished replication. For large payloads, the replication is slower in the most cases (even more in a distributed setup, where the master and replica are on different nodes). The easy way is to wait for replication. But there is one difficulty: The number of replicas has to be known. There is a new settings-variable "AMOUNT_REPLICAS" which defaults to 1. It needs to be set correctly! If it is too high, every autoupdate will be delayed by 1 seconds because of a timeout witing for non-existent replicas. If it is too low, some autoupdates may be wrong (and not detectable by the client!) becuase of reading from non-synchronised relicas. The other possibility is to fork channel_redis and add the feature of a read-only redis. This ould help, because on a single redis instance all commands are ordered: First, the data is synced, then the autoupdate message. Attention: This means, if redis-replicas are scaled up, one must make sure to read from the same instance. I think this is not possible in the way how dockers overlay networks work. The only way would be to open one connection and reuse the connection from channels_redis in OpenSlides. This would mean a heavy integration of channels_redis (meaning including the source code in our repo). For the first fix, this one is easy and should work.
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result = await self._eval(redis, script_name, keys=keys, args=args)
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elif str(e) == "cache_reset":
raise CacheReset()
else:
raise e
Redis: Wait for replication on writes Since channels_redis does not support dedicated read-redis instances, the autoupdate message may be received before the data was replicated. All workers read the autoupdate message from the write host, so there is a race between getting this message and a finished replication. For large payloads, the replication is slower in the most cases (even more in a distributed setup, where the master and replica are on different nodes). The easy way is to wait for replication. But there is one difficulty: The number of replicas has to be known. There is a new settings-variable "AMOUNT_REPLICAS" which defaults to 1. It needs to be set correctly! If it is too high, every autoupdate will be delayed by 1 seconds because of a timeout witing for non-existent replicas. If it is too low, some autoupdates may be wrong (and not detectable by the client!) becuase of reading from non-synchronised relicas. The other possibility is to fork channel_redis and add the feature of a read-only redis. This ould help, because on a single redis instance all commands are ordered: First, the data is synced, then the autoupdate message. Attention: This means, if redis-replicas are scaled up, one must make sure to read from the same instance. I think this is not possible in the way how dockers overlay networks work. The only way would be to open one connection and reuse the connection from channels_redis in OpenSlides. This would mean a heavy integration of channels_redis (meaning including the source code in our repo). For the first fix, this one is easy and should work.
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return result
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async def _eval(
self, redis: Any, script_name: str, keys: List[str] = [], args: List[Any] = []
) -> Any:
""" Do a real eval of the script (no hash used here). Catches "cache_reset". """
try:
return await redis.eval(self.scripts[script_name][0], keys, args)
except aioredis.errors.ReplyError as e:
if str(e) == "cache_reset":
raise CacheReset()
else:
raise e
class MemoryCacheProvider:
"""
CacheProvider for the ElementCache that uses only the memory.
See the RedisCacheProvider for a description of the methods.
This provider supports only one process. It saves the data into the memory.
When you use different processes they will use diffrent data.
For this reason, the ensure_cache is not used and the schema version always
returns an invalid schema to always buold the cache.
"""
def __init__(self, ensure_cache: Callable[[], Coroutine[Any, Any, None]]) -> None:
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self.set_data_dicts()
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def set_data_dicts(self) -> None:
self.ready = False
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self.full_data: Dict[str, str] = {}
self.change_id_data: Dict[int, Set[str]] = {}
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self.locks: Dict[str, str] = {}
self.default_change_id: int = -1
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async def ensure_cache(self) -> None:
pass
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async def clear_cache(self) -> None:
self.set_data_dicts()
self.ready = False
async def reset_full_cache(
self, data: Dict[str, str], default_change_id: int
) -> None:
self.change_id_data = {}
self.full_data = data
self.default_change_id = default_change_id
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async def add_to_full_data(self, data: Dict[str, str]) -> None:
self.full_data.update(data)
async def data_exists(self) -> bool:
return self.ready
# return bool(self.full_data) and self.default_change_id >= 0
async def set_cache_ready(self) -> None:
self.ready = True
async def get_all_data(self) -> Dict[bytes, bytes]:
return str_dict_to_bytes(self.full_data)
async def get_all_data_with_max_change_id(self) -> Tuple[int, Dict[bytes, bytes]]:
all_data = await self.get_all_data()
max_change_id = await self.get_current_change_id()
return max_change_id, all_data
async def get_collection_data(self, collection: str) -> Dict[int, bytes]:
out = {}
query = f"{collection}:"
for element_id, value in self.full_data.items():
if element_id.startswith(query):
_, id = split_element_id(element_id)
out[id] = value.encode()
return out
async def get_element_data(self, element_id: str) -> Optional[bytes]:
value = self.full_data.get(element_id, None)
return value.encode() if value is not None else None
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async def add_changed_elements(
self, changed_elements: List[str], deleted_element_ids: List[str]
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) -> int:
change_id = await self.get_current_change_id() + 1
for i in range(0, len(changed_elements), 2):
element_id = changed_elements[i]
self.full_data[element_id] = changed_elements[i + 1]
if change_id in self.change_id_data:
self.change_id_data[change_id].add(element_id)
else:
self.change_id_data[change_id] = {element_id}
for element_id in deleted_element_ids:
try:
del self.full_data[element_id]
except KeyError:
pass
if change_id in self.change_id_data:
self.change_id_data[change_id].add(element_id)
else:
self.change_id_data[change_id] = {element_id}
return change_id
async def get_data_since(
self, change_id: int
) -> Tuple[int, Dict[str, List[bytes]], List[str]]:
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changed_elements: Dict[str, List[bytes]] = defaultdict(list)
deleted_elements: List[str] = []
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all_element_ids: Set[str] = set()
for data_change_id, element_ids in self.change_id_data.items():
if data_change_id >= change_id:
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all_element_ids.update(element_ids)
for element_id in all_element_ids:
element_json = self.full_data.get(element_id, None)
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if element_json is None:
deleted_elements.append(element_id)
else:
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collection, id = split_element_id(element_id)
changed_elements[collection].append(element_json.encode())
max_change_id = await self.get_current_change_id()
return (max_change_id, changed_elements, deleted_elements)
async def get_current_change_id(self) -> int:
if self.change_id_data:
return max(self.change_id_data.keys())
else:
return await self.get_lowest_change_id()
async def get_lowest_change_id(self) -> int:
return self.default_change_id
async def get_schema_version(self) -> Optional[SchemaVersion]:
return None
async def set_schema_version(self, schema_version: SchemaVersion) -> None:
pass
class Cachable(Protocol):
"""
A Cachable is an object that returns elements that can be cached.
It needs at least the methods defined here.
"""
personalized_model: bool
def get_collection_string(self) -> str:
"""
Returns the string representing the name of the cachable.
"""
def get_elements(self) -> List[Dict[str, Any]]:
"""
Returns all elements of the cachable.
"""
async def restrict_elements(
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self, user_id: int, elements: List[Dict[str, Any]]
) -> List[Dict[str, Any]]:
"""
Converts full_data to restricted_data.
elements can be an empty list, a list with some elements of the cachable or with all
elements of the cachable.
"""