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moka-py
moka-py is a Python binding for the highly efficient Moka caching library written in Rust. This library allows you to leverage the power of Moka's high-performance, feature-rich cache in your Python projects.
Features
- Synchronous Cache: Supports thread-safe, in-memory caching for Python applications.
- TTL Support: Automatically evicts entries after a configurable time-to-live (TTL).
- TTI Support: Automatically evicts entries after a configurable time-to-idle (TTI).
- Size-based Eviction: Automatically removes items when the cache exceeds its size limit using TinyLFU or LRU policy.
- Concurrency: Optimized for high-performance, concurrent access in multithreaded environments.
- Fully typed:
mypyandpyrightfriendly.
Installation
You can install moka-py using uv:
uv add moka-py
poetry:
poetry add moka-py
Or, if you still stick to pip for some reason:
pip install moka-py
Table of Contents
Usage
Using moka_py.Moka
from time import sleep
from moka_py import Moka
# Create a cache with a capacity of 100 entries, with a TTL of 30 seconds
# and a TTI of 5.2 seconds. Entries are always removed after 30 seconds
# and are removed after 5.2 seconds if there are no `get`s happened for this time.
#
# Both TTL and TTI settings are optional. In the absence of an entry,
# the corresponding policy will not expire it.
# The default eviction policy is "tiny_lfu" which is optimal for most workloads,
# but you can choose "lru" as well.
cache: Moka[str, list[int]] = Moka(capacity=100, ttl=30, tti=5.2, policy="lru")
# Insert a value.
cache.set("key", [3, 2, 1])
# Retrieve the value.
assert cache.get("key") == [3, 2, 1]
# Wait for 5.2+ seconds, and the entry will be automatically evicted.
sleep(5.3)
assert cache.get("key") is None
As a decorator
moka-py can be used as a drop-in replacement for @lru_cache() with TTL + TTI support:
from time import sleep
from moka_py import cached
@cached(maxsize=1024, ttl=10.0, tti=1.0)
def f(x, y):
print("hard computations")
return x + y
f(1, 2) # calls computations
f(1, 2) # gets from the cache
sleep(1.1)
f(1, 2) # calls computations (since TTI has passed)
Async support
Unlike @lru_cache(), @moka_py.cached() supports async functions:
import asyncio
from time import perf_counter
from moka_py import cached
@cached(maxsize=1024, ttl=10.0, tti=1.0)
async def f(x, y):
print("http request happening")
await asyncio.sleep(2.0)
return x + y
start = perf_counter()
assert asyncio.run(f(5, 6)) == 11
assert asyncio.run(f(5, 6)) == 11 # got from cache
assert perf_counter() - start < 4.0
Do not call a function if another function is in progress
moka-py can synchronize threads on keys
import moka_py
from typing import Any
from time import sleep
import threading
from decimal import Decimal
calls = []
@moka_py.cached(ttl=5, wait_concurrent=True)
def get_user(id_: int) -> dict[str, Any]:
calls.append(id_)
sleep(0.3) # simulation of HTTP request
return {
"id": id_,
"first_name": "Jack",
"last_name": "Pot",
}
def process_request(path: str, user_id: int) -> None:
user = get_user(user_id)
print(f"user #{user_id} came to {path}, their info is {user}")
...
def charge_money(from_user_id: int, amount: Decimal) -> None:
user = get_user(from_user_id)
print(f"charging {amount} money from user #{from_user_id} ({user['first_name']} {user['last_name']})")
...
if __name__ == '__main__':
request_processing = threading.Thread(target=process_request, args=("/user/info/123", 123))
money_charging = threading.Thread(target=charge_money, args=(123, Decimal("3.14")))
request_processing.start()
money_charging.start()
request_processing.join()
money_charging.join()
# only one call occurred. without the `wait_concurrent` option, each thread would go for an HTTP request
# since no cache key was set
assert len(calls) == 1
ATTENTION:
wait_concurrentis not yet supported for async functions and will throwNotImplementedError
Eviction listener
moka-py supports adding of an eviction listener that's called whenever a key is dropped
from the cache for some reason. The listener must be a 3-arguments function (key, value, cause). The arguments
are passed as positional (not keyword).
There are 4 reasons why a key may be dropped:
"expired": The entry's expiration timestamp has passed."explicit": The entry was manually removed by the user (.remove()is called)."replaced": The entry itself was not actually removed, but its value was replaced by the user (.set()is called for an existing entry)."size": The entry was evicted due to size constraints.
from typing import Literal
from moka_py import Moka
from time import sleep
def key_evicted(
k: str,
v: list[int],
cause: Literal["explicit", "size", "expired", "replaced"]
):
print(f"entry {k}:{v} was evicted. {cause=}")
moka: Moka[str, list[int]] = Moka(2, eviction_listener=key_evicted, ttl=0.1)
moka.set("hello", [1, 2, 3])
moka.set("hello", [3, 2, 1])
moka.set("foo", [4])
moka.set("bar", [])
sleep(1)
moka.get("foo")
# will print
# entry hello:[1, 2, 3] was evicted. cause='replaced'
# entry bar:[] was evicted. cause='size'
# entry hello:[3, 2, 1] was evicted. cause='expired'
# entry foo:[4] was evicted. cause='expired'
IMPORTANT NOTES:
- It's not guaranteed that the listener will be called just in time. Also, the underlying
mokadoesn't use any background threads or tasks, hence, the listener is never called in "background"- The listener must never raise any kind of
Exception. If an exception is raised, it might be raised to any of the moka-py method in any of the threads that call this method.- The listener must be fast. Since it's called only when you're interacting with
moka-py(via.get()/.set()/ etc.), the listener will slow down these operations. It's terrible idea to do some sort of IO in the listener. If you need so, run aThreadPoolExecutorsomewhere and call.submit()inside of the listener or commit an async task viaasyncio.create_task()
Removing entries
An entry can be removed using Moka.remove(key). If a value was set, it is returned; otherwise, None is returned.
from moka_py import Moka
c = Moka(128)
c.set("hello", "world")
assert c.remove("hello") == "world"
assert c.get("hello") is None
In some cases you may want Nones to be a valid cache value. In this case you need to distinguish between None as a
value and None as the absence of a value. Use Moka.remove(key, default=...):
from moka_py import Moka
c = Moka(128)
c.set("hello", None)
assert c.remove("hello", default="WAS_NOT_SET") is None # None is returned since is was set
# Now entry with key "hello" doesn't exist so `default` argument is returned
assert c.remove("hello", default="WAS_NOT_SET") == "WAS_NOT_SET"
How it works
Moka object stores Python object references
(by INCREFing PyObjects) and doesn't use
serialization or deserialization. This means you can use any Python object as a value and any Hashable object as a
key (Moka calls keys' __hash__ magic methods). But also you need to remember that mutable objects stored in Moka
are still mutable:
from moka_py import Moka
c = Moka(128)
my_list = [1, 2, 3]
c.set("hello", my_list)
still_the_same = c.get("hello")
still_the_same.append(4)
assert my_list == [1, 2, 3, 4]
Eviction policies
moka-py uses the TinyLFU eviction policy as default, with LRU option. You can learn more about the policies here
Performance
Measured using MacBook Pro 2021 with Apple M1 Pro processor and 16GiB RAM
-------------------------------------------------------------------------------------------- benchmark: 9 tests -------------------------------------------------------------------------------------------
Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Mops/s) Rounds Iterations
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_bench_remove 100.8775 (1.0) 108.9191 (1.0) 102.6757 (1.0) 3.4992 (34.54) 101.0640 (1.0) 2.4234 (15.49) 1;1 9.7394 (1.0) 5 10000000
test_bench_get[lru-False] 112.8452 (1.12) 113.0924 (1.04) 112.9415 (1.10) 0.1013 (1.0) 112.9176 (1.12) 0.1565 (1.0) 1;0 8.8541 (0.91) 5 10000000
test_bench_get[tiny_lfu-False] 135.0147 (1.34) 135.6069 (1.25) 135.2916 (1.32) 0.2246 (2.22) 135.2849 (1.34) 0.3164 (2.02) 2;0 7.3914 (0.76) 5 10000000
test_bench_get[lru-True] 135.1628 (1.34) 135.7813 (1.25) 135.4712 (1.32) 0.2231 (2.20) 135.4765 (1.34) 0.2477 (1.58) 2;0 7.3816 (0.76) 5 10000000
test_bench_get[tiny_lfu-True] 135.2461 (1.34) 135.6612 (1.25) 135.4463 (1.32) 0.1802 (1.78) 135.4026 (1.34) 0.3192 (2.04) 2;0 7.3830 (0.76) 5 10000000
test_bench_get_with 290.5307 (2.88) 291.0418 (2.67) 290.8393 (2.83) 0.1893 (1.87) 290.8867 (2.88) 0.1873 (1.20) 2;0 3.4383 (0.35) 5 10000000
test_bench_set[tiny_lfu] 515.7514 (5.11) 518.6080 (4.76) 517.4876 (5.04) 1.1196 (11.05) 517.6572 (5.12) 1.5465 (9.88) 2;0 1.9324 (0.20) 5 1912971
test_bench_set_str_key 516.1032 (5.12) 533.7330 (4.90) 525.7461 (5.12) 6.3386 (62.57) 526.8491 (5.21) 6.1052 (39.01) 2;0 1.9021 (0.20) 5 1918471
test_bench_set[lru] 637.3014 (6.32) 644.4533 (5.92) 640.3571 (6.24) 2.8981 (28.61) 639.8821 (6.33) 4.6131 (29.48) 2;0 1.5616 (0.16) 5 1581738
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
License
moka-py is distributed under the MIT license
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