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An example of a Python decorator to simplify caching a function's result.
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"""An example of a cache decorator.""" | |
import json | |
from functools import wraps | |
from redis import StrictRedis | |
redis = StrictRedis() | |
def cached(func): | |
""" | |
Decorator that caches the results of the function call. | |
We use Redis in this example, but any cache (e.g. memcached) will work. | |
We also assume that the result of the function can be seralized as JSON, | |
which obviously will be untrue in many situations. Tweak as needed. | |
""" | |
@wraps(func) | |
def wrapper(*args, **kwargs): | |
# Generate the cache key from the function's arguments. | |
key_parts = [func.__name__] + list(args) | |
key = '-'.join(key_parts) | |
result = redis.get(key) | |
if result is None: | |
# Run the function and cache the result for next time. | |
value = func(*args, **kwargs) | |
value_json = json.dumps(value) | |
redis.set(key, value_json) | |
else: | |
# Skip the function entirely and use the cached value instead. | |
value_json = result.decode('utf-8') | |
value = json.loads(value_json) | |
return value | |
return wrapper | |
# Usage: | |
@cached | |
def my_great_function(): | |
# The below calculation will run the first time this function is called. | |
# On subsequent runs the result will be pulled from the cache instead. | |
return list(range(10000)) |
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