在flask中返回即时响应，但在新线程中完成处理 [英] Returning an immediate response in flask, but finishing the processing in a new thread

问题描述

我有一个从10秒开始的过程，但是在10秒之后，我不需要将信息返回给用户，而是将其记录在dynamoDB上，这就是为什么我希望用户不必等待10秒相反，我希望在发布请求后立即获得成功"响应.

I have a process from 10 seconds, but after the 10 seconds, I don't need to return the information to the user but write it down on a dynamoDB, that's why I would like the user doesn't have to wait 10 seconds. Instead, I would like an immediate "Success" response after the post request.

我阅读了几篇文章，并在这带有拆解回调，但没有示例.

I read a couple of posts and in this one, the answer was with a Teardown Callback, but there wasn't an example.

然后，我阅读了此，但是它没有帮助我与我的问题.

I read then this, but it doesn't help me with my problem.

我当然阅读了 teardown-callbacks 和此模式，但我不知道如何使用它.

I read of course teardown-callbacks and this pattern but I don't know how I could use it another way.

我的代码如下:

@app.route('/ocr/read_image', methods=['POST'])
def get_text():    
    return jsonify('Success')

@app.teardown_request
def teardown_request(response):        
    time.sleep(10)

它实际上返回成功"消息，但仅在10秒之后.

It actually returns the "Success" Message but just after the 10 seconds.

有没有办法在10秒之前返回成功"消息?

Is there a way to return the "Succes" Message before the 10 seconds?

我一直在阅读，芹菜也许是可行的，但如果可以的话，我会尽量避免.

I've been reading that it's maybe possible with celery but I would love avoid it if I can.

有人知道怎么做吗?

推荐答案

正如Ardaglio所说，最好的方法是使用多线程.

As Ardaglio said, the best way was using multithreading.

我没有使用Celery，因为我认为它非常复杂，而且我的问题也很容易解决.

I didn't use Celery, because I think it's pretty complicated and my problem is quite easy for it.

所以，我正在使用线程:

So, I'm using Thread:

from threading import Thread

@app.route('/ocr/read_image', methods=['POST'])
def get_text():    
    Thread(target=continue_processing).start()
    return jsonify('Success')

def continue_processing():
    time.sleep(10)
    print('Hi')

但是，您必须小心.我将Keras与Tensorflow作为后端一起使用，如果使用它，则会出现一个很好的值错误 ValueError:Tensor Tensor()不是此图的元素.

But, you gotta be careful. I'm using Keras with Tensorflow as Backend, and if you use it so, you will have a nice value error ValueError: Tensor Tensor()is not an element of this graph.

因此，为了避免在线程内出现它，您必须在创建模型后保存图:

So, to avoid it inside a Thread, you've to save the Graph after the model is made:

GRAPH = tf.get_default_graph()

，然后您必须通过以下方式在异步过程中使用它:

and then you've to use it inside the asynchron process this way:

with GRAPH.as_default():
    do something with your model 

希望它可以对某人有所帮助.

Hope it could be help someone.

这篇关于在flask中返回即时响应，但在新线程中完成处理的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！