问题
I'm trying to develop an API service that after collecting data continuously from different sources, elaborate that data, and keep that information ready from being requested from another service.
I'm using Flask and it's working on top of a single thread.
My problem is about the slowlines accessing the cached data. The gathering process it works pretty well, but sometimes when I ask for the data the server it's busy because in the meantime it's fetching the data from the sources.
How should I set up the thread to avoid this?
Here down I'm explain what I've done thru some simplified functions and classes.
The Fetching Service
class FetchingService():
def __init__(self,url=None,speed=None):
self.url = url
self.speed = speed # speed in seconds
self.last_updated = None # last time the service was used
def loadData(self):
time = { 'timestamp': int(time.time()) }
try:
r = requests.get(self.url) # get the data from the url
data = r.json() # if is a json
data.update({ 'status': True })
data.update(time)
return data
except:
data = { 'status': False }
data.update(time)
return data
def isTimeToUpdate(self):
if self.last_updated is not None: # check if is the time to run an update
delta = int(time.time()) - self.last_updated
if delta >= self.speed: # if passed enougth time
return True # is time to update
else:
return False # too early
else:
return False # last_updated not set
def run(self):
if self.last_updated is None:
self.last_udated = int(time.time())
if self.isTimeToUpdate():
self.loadData()
The Caching Service
class Caching():
def __init__(self,instances):
self.data = []
self.instances = instances
def run(self):
if self.instances:
for i in instances:
self.data.append(i.run())
def queryLast(self):
if self.data:
return self.data[-1]
The Thread
class myThread():
def __init__ (self,thread_time,instances):
self.speed = thread_time
self.data = None
self.instances = instances
self.dataLock = threading.Lock()
self.myThread = threading.Thread()
def primaryThread(self):
self.myThread = threading.Timer(self.speed, self.run, ())
self.myThread.start()
def run(self):
with self.dataLock:
self.data.run()
self.primaryThread()
def activate(self):
with self.dataLock:
self.data = Caching(self.instances)
self.primaryThread()
return 'active'
def queryLast(self,key,value):
with self.dataLock:
data = self.data.queryLast()
self.primaryThread()
return data
The Main
a = FetchingService(url='/api/test/',10)
b = FetchingService(url='/api/data/',5)
c = FetchingService(url='/boh/',100)
instances = [ a , b , c ]
t = myThread(1,instances)
The Flask views
@application.route('/active/', methods=['GET'])
def app_start():
result = t.activate()
return jsonify(result)
@application.route('/last/', methods=['GET'])
def app_query():
result = t.queryLast()
return jsonify(result)
来源：https://stackoverflow.com/questions/48154467/python-flask-api-service-loop-through-api-data-sources-cache-and-give-rapi