python django从命令加载缓存TfidfVectorizer并在视图中使用

Question

I would like to load a TfidfVectorizer fitted model using a Django command and then reuse it on view. So in the command

from django.core.cache import cache
from sklearn.feature_extraction.text import TfidfVectorizer
class Command(BaseCommand):
    ....
    model = TfidfVectorizer()
    modelfitted  = model.fit(data)
    cache.set('model',modelfitted)

Then in views.py I would like to call it:

def test_function(request):
    mod = cache.get('model')

the 'mod' object is None. Any idea?

Answer 1

The problem is that you are using Local-memory caching . As stated in the docs this cache is per-process :

Note that each process will have its own private cache instance, which means no cross-process caching is possible. This obviously also means the local memory cache isn't particularly memory-efficient, so it's probably not a good choice for production environments. It's nice for development.

So can't write to the cache in a managemant command and then call this value in your runserver process.

You should change you cache backend for example to Filesystem caching

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.filebased.FileBasedCache',
        'LOCATION': '/var/tmp/django_cache',
    }
}