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我对使用烧瓶有点陌生，我想缓存读取腌制数据的函数的结果。我使用如下memoize功能：flask_cache

在model_chacher.py：

from flask_cache import Cache
import pickle


model_cache = Cache(config={'CACHE_TYPE': 'simple'})


class ModelCacher():
    @model_cache.memoize(50)
    def get_model(self, customer_ID):

        with open('/path/to/data.pickle', 'rb') as tf:
            model_args = pickle.load(tf)
            trained_classifier = model_args[0]

        return trained_classifier

在flask_compose.py：

from flask import Flask
from controllers.topic import controller as topic_controller
from models.modelcache.model_chacher import model_cache


app = Flask(__name__)
model_cache.init_app(app)
app.register_blueprint(topic_controller.topic_controller_blueprint)


if __name__ == '__main__':
    app.run(host="0.0.0.0", port=80, debug=True)

我打电话ModelCacher.get_model(customer_ID)给topic_controller：

from models.modelcache.model_chacher import ModelCacher
...
trained_classifier = ModelCacher.get_model(cls_str)
...

在运行flask_compose.py并发送请求后，我得到以下结果：

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1997, in __call__
    return self.wsgi_app(environ, start_response)
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1985, in wsgi_app
    response = self.handle_exception(e)
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1540, in handle_exception
    reraise(exc_type, exc_value, tb)
  File "/usr/local/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
    raise value
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1982, in wsgi_app
    response = self.full_dispatch_request()
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1614, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1517, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "/usr/local/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
    raise value
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1612, in full_dispatch_request
    rv = self.dispatch_request()
  File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1598, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "/app/controllers/topic/controller.py", line 20, in classify
    return ModelCacher.get_model(cls_str)
  File "/usr/local/lib/python3.6/site-packages/flask_cache/__init__.py", line 528, in decorated_function
    cache_key = decorated_function.make_cache_key(f, *args, **kwargs)
  File "/usr/local/lib/python3.6/site-packages/flask_cache/__init__.py", line 393, in make_cache_key
    **kwargs)
  File "/usr/local/lib/python3.6/site-packages/flask_cache/__init__.py", line 434, in _memoize_kwargs_to_args
    elif abs(i-args_len) <= len(argspec.defaults):
TypeError: object of type 'NoneType' has no len()

我的问题是：如何正确设置我的缓存？任何帮助是极大的赞赏。

编辑：什么解决了我的问题：

正如@stamaimer 指出的那样，我创建了我的实例ModelCacher并解决了问题，我也使用了缓存flask_cache.Cache而不是memoize.

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1 回答 1

0

您定义的get_model方法是实例方法而不是类方法。你ModelCacher.get_model(cls_str)在调用方法时使用。尝试用ModelCacher().get_model(cls_str). 或者您可以将其定义为全局函数。

于 2018-04-22T01:55:10.527 回答