与Flask服务器同时运行while循环 [英] Run while loop concurrently with Flask server
问题描述
from LEDs import *
myLEDs = LEDs()
done = False
未完成:
myLEDs.iterate()
想用Flask作为一个好看的ReactJS前端之间的桥梁,我可以在我的浏览器中运行(改变当前的模式等)和Python中的LED控制代码。
我有Flask工作正常,可以处理HTTP请求,等我想知道如何设置 myLEDs.iterate()$
$ b $
$ b @ app.route('/ changePattern',methods = ['POST'])
def changePattern():
n = request.json ['num']
myLEDs.setPattern(n)
返回jsonify(** locals())
if __name__ =='__main__':
app.debug = True
myLEDs.setToFrequentlyIterateAndStillTalkToFlask()
app.run()
我遇到了 celery
,这看起来好像是可以做的,但看起来像我的问题是多么简单的矫枉过正。
使用Flask矫枉过正只需要一个UI来管理我的python后端代码?有一个比芹菜更简单的库用于在后台运行的东西?
编辑
$ b 这是大型项目的一部分,一个连接到Python后端的Node-Webkit前端。如果看起来不可行,我愿意改变我的方法来使用这个应用程序。
$ pre $
进口时间
从瓶子进口Flask,jsonify
从多进程进口进程,价值
应用程序= Flask(__ name__)
tasks = [
{
'id':1,
'title':u'Buy groceries',
'description':u'Milk,Cheese,Pizza,Fruit,Tylenol',
'done':False
},
{
'id':2,
'title':u'Learn Python',
'description':u'Need在网上找到一个好的Python教程',
'done':False
}
$ b @ app.route('/ todo / api / v1.0 / tasks',methods = ['GET'])
def get_tasks ):
返回jsonify({'tasks':tasks})
def record_loop(loop_on):
而真:
如果loop_on.value == True:
print(l oop running)
time.sleep(1)
if __name__ ==__main__:
recording_on = Value('b',True)
p = process(target = record_loop,args =(recording_on,))
p.start()
app.run(debug = True,use_reloader = False)
p.join
任务部分来自这里是,来自我的多处理代码
注意use_reloader = False部分。这是避免运行循环两次所必需的。由于这个原因请参阅这里
$ b
这个功能可以通过启动服务器来测试
pre $ $ c $>
$ b
并调用
$ py $&$ $ $
curl -i http:// localhost:5000 / todo / api / v1.0 / tasks
I'm updating some LEDs using python. I've been doing this like so:
from LEDs import *
myLEDs = LEDs()
done = False
while not done:
myLEDs.iterate()
I wanted to use Flask to act as a bridge between some nice-looking ReactJS front-end I can run in my browser (to change the current pattern, etc) and the LED-controlling code in Python.
I have Flask working fine, can handle HTTP requests, etc. I'm wondering how I can set myLEDs.iterate()
to continuously run (or run on a rapid schedule) concurrently with my flask app, while still being able to communicate with one another, like so:
myLEDs = LEDs()
@app.route('/changePattern',methods=['POST'])
def changePattern():
n = request.json['num']
myLEDs.setPattern(n)
return jsonify(**locals())
if __name__ == '__main__':
app.debug = True
myLEDs.setToFrequentlyIterateAndStillTalkToFlask()
app.run()
I came across celery
, which seems like it would do the trick, but also seems like overkill for how simple my problem is.
Is using Flask overkill for simply wanting a UI to manage my python back-end code? Is there a simpler library than Celery to use for running something in the background?
Edit
This is part of a larger project to develop an app with a Node-Webkit front-end attached to a Python backend. I'm open to changing my approach to this app if it doesn't seem feasible.
Use multiprocess to run the loop in a different process as the Flask HTTP requests:
import time
from flask import Flask, jsonify
from multiprocessing import Process, Value
app = Flask(__name__)
tasks = [
{
'id': 1,
'title': u'Buy groceries',
'description': u'Milk, Cheese, Pizza, Fruit, Tylenol',
'done': False
},
{
'id': 2,
'title': u'Learn Python',
'description': u'Need to find a good Python tutorial on the web',
'done': False
}
]
@app.route('/todo/api/v1.0/tasks', methods=['GET'])
def get_tasks():
return jsonify({'tasks': tasks})
def record_loop(loop_on):
while True:
if loop_on.value == True:
print("loop running")
time.sleep(1)
if __name__ == "__main__":
recording_on = Value('b', True)
p = Process(target=record_loop, args=(recording_on,))
p.start()
app.run(debug=True, use_reloader=False)
p.join()
The tasks part is from here, multiprocessing code from me.
Note the "use_reloader=False" part. This is necessary to avoid running the loop twice. For the reason see here
The functionality can be tested by starting up the server with
python <your_name_for_the example>.py
and calling
curl -i http://localhost:5000/todo/api/v1.0/tasks
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