Python 如何缓存 Django Rest Framework API 调用？
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How to cache Django Rest Framework API calls?
提问by Kitti Wateesatogkij
I'm using Memcached as backend to my django app. This code works fine in normal django query:
我使用 Memcached 作为 django 应用程序的后端。此代码在正常的 Django 查询中工作正常：
def get_myobj():
cache_key = 'mykey'
result = cache.get(cache_key, None)
if not result:
result = Product.objects.all().filter(draft=False)
cache.set(cache_key, result)
return result
But it doesn't work when used with django-rest-framework api calls:
但是当与 django-rest-framework api 调用一起使用时它不起作用：
class ProductListAPIView(generics.ListAPIView):
def get_queryset(self):
product_list = Product.objects.all()
return product_list
serializer_class = ProductSerializer
I'm about to try DRF-extensions which provide caching functionality:
我将尝试提供缓存功能的 DRF 扩展：
https://github.com/chibisov/drf-extensions
https://github.com/chibisov/drf-extensions
but the build status on github is currently saying "build failing".
但 github 上的构建状态目前显示“构建失败”。
My app is very read-heavy on api calls. Is there a way to cache these calls?
我的应用程序对 api 调用的读取量很大。有没有办法缓存这些调用？
Thank you.
谢谢你。
回答by Linovia
Ok, so, in order to use caching for your queryset:
好的，为了对查询集使用缓存：
class ProductListAPIView(generics.ListAPIView):
def get_queryset(self):
return get_myobj()
serializer_class = ProductSerializer
You'd probably want to set a timeout on the cache set though (like 60 seconds):
您可能希望在缓存集上设置超时（例如 60 秒）：
cache.set(cache_key, result, 60)
If you want to cache the whole view:
如果要缓存整个视图：
from django.utils.decorators import method_decorator
from django.views.decorators.cache import cache_page
class ProductListAPIView(generics.ListAPIView):
serializer_class = ProductSerializer
@method_decorator(cache_page(60))
def dispatch(self, *args, **kwargs):
return super(ProductListAPIView, self).dispatch(*args, **kwargs)
回答by Marco Silva
I just implemented this to use on my serializers
我刚刚实现了这个以在我的序列化程序上使用
def cache_me(cache):
def true_decorator(f):
@wraps(f)
def wrapper(*args, **kwargs):
instance = args[1]
cache_key = '%s.%s' % (instance.facility, instance.id)
logger.debug('%s cache_key: %s' % (cache, cache_key))
try:
data = caches[cache].get(cache_key)
if data is not None:
return data
except:
pass
logger.info('did not cache')
data = f(*args, **kwargs)
try:
caches[cache].set(cache_key, data)
except:
pass
return data
return wrapper
return true_decorator
then i override the to_representation method on my serializers, so it caches the serialized output per instance.
然后我覆盖了序列化程序上的 to_representation 方法，因此它会缓存每个实例的序列化输出。
class MyModelSerializer(serializers.ModelSerializer):
class Meta:
model = MyModel
exclude = ('is_deleted', 'facility',)
@cache_me('mymodel')
def to_representation(self, instance):
return super(MyModelSerializer, self).to_representation(instance)
