如何通知用户正在使用缓存？

Question

我正在使用 python 库 diskcache 及其装饰器 @cache.memoize 来缓存对我的 couchdb 数据库的调用。工作正常。但是，我想向用户打印数据是从数据库返回还是从缓存返回。

我什至不知道如何解决这个问题。

到目前为止我的代码：

import couchdb
from diskcache import Cache

cache = Cache("couch_cache")


@cache.memoize()
def fetch_doc(url: str, database: str, doc_id: str) -> dict:

    server = couchdb.Server(url=url)
    db = server[database]

    return dict(db[doc_id])

Answer 1

这是一种方法，但我并不真正推荐它，因为 (1) 它添加了一个额外的操作，即您自己手动检查缓存，并且 (2) 它可能会重复库内部已经在做的事情。我没有对任何性能影响进行适当的检查，因为我没有生产 data/env 和各种 doc_ids，但正如所说，它可以由于额外的查找操作，速度变慢了。

但事情就是这样。

diskcache.Cache object "supports a familiar Python mapping interface" (like dicts). You can then manually check for yourself if a given key is already present in the cache, using the same key automatically generated based on the arguments to the memoize-d函数：

An additional __cache_key__ attribute can be used to generate the cache key used for the given arguments.
>>> key = fibonacci.__cache_key__(100)  
>>> print(cache[key])  
>>> 354224848179261915075    

因此，您可以将 fetch_doc 函数包装到 另一个 函数中，该函数检查缓存键是否基于 url、database，并且 doc_id 参数存在，将结果打印给用户，所有这些都在调用实际的 fetch_doc 函数之前：

import couchdb
from diskcache import Cache

cache = Cache("couch_cache")

@cache.memoize()
def fetch_doc(url: str, database: str, doc_id: str) -> dict:
    server = couchdb.Server(url=url)
    db = server[database]
    return dict(db[doc_id])

def fetch_doc_with_logging(url: str, database: str, doc_id: str):
    # Generate the key
    key = fetch_doc.__cache_key__(url, database, doc_id)

    # Print out whether getting from cache or not
    if key in cache:
        print(f'Getting {doc_id} from cache!')
    else:
        print(f'Getting {doc_id} from DB!')

    # Call the actual memoize-d function
    return fetch_doc(url, database, doc_id)

测试时：

url = 'https://your.couchdb.instance'
database = 'test'
doc_id = 'c97bbe3127fb6b89779c86da7b000885'

cache.stats(enable=True, reset=True)
for _ in range(5):
    fetch_doc_with_logging(url, database, doc_id)
print(f'(hits, misses) = {cache.stats()}')

# Only for testing, so 1st call will always miss and will get from DB
cache.clear()

它输出：

$ python test.py 
Getting c97bbe3127fb6b89779c86da7b000885 from DB!
Getting c97bbe3127fb6b89779c86da7b000885 from cache!
Getting c97bbe3127fb6b89779c86da7b000885 from cache!
Getting c97bbe3127fb6b89779c86da7b000885 from cache!
Getting c97bbe3127fb6b89779c86da7b000885 from cache!
(hits, misses) = (4, 1)

您可以将该包装函数变成装饰器：

def log_if_cache_or_not(memoized_func):
    def _wrap(*args):
        key = memoized_func.__cache_key__(*args)
        if key in cache:
            print(f'Getting {doc_id} from cache!')
        else:
            print(f'Getting {doc_id} from DB!')
        return memoized_func(*args)

    return _wrap

@log_if_cache_or_not
@cache.memoize()
def fetch_doc(url: str, database: str, doc_id: str) -> dict:
    server = couchdb.Server(url=url)
    db = server[database]
    return dict(db[doc_id])

for _ in range(5):
    fetch_doc(url, database, doc_id)

或，组合成1个新装饰器：

def memoize_with_logging(func):
    memoized_func = cache.memoize()(func)

    def _wrap(*args):
        key = memoized_func.__cache_key__(*args)
        if key in cache:
            print(f'Getting {doc_id} from cache!')
        else:
            print(f'Getting {doc_id} from DB!')
        return memoized_func(*args)

    return _wrap

@memoize_with_logging
def fetch_doc(url: str, database: str, doc_id: str) -> dict:
    server = couchdb.Server(url=url)
    db = server[database]
    return dict(db[doc_id])

for _ in range(5):
    fetch_doc(url, database, doc_id)

一些快速测试：

In [9]: %timeit for _ in range(100000): fetch_doc(url, database, doc_id)
13.7 s ± 112 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [10]: %timeit for _ in range(100000): fetch_doc_with_logging(url, database, doc_id)
21.2 s ± 637 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

(如果 doc_id 在调用中随机变化可能会更好)

同样，正如我在开始时提到的，缓存和 memoize-ing 函数调用应该可以加速该函数。这个答案增加了缓存查找和 printing/logging 的额外操作，无论您是从数据库还是从缓存中获取，它可能影响该函数调用的性能。适当测试。

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