i have one scraper which initiate the "requestes" session and fetch some data, using a IPV6, i have now 10000 ip list, I have prepared it using threading, but its giving error.
Need support to find out the issue.
import requests, queue,threading, urllib3,jso,pandas as pd, os, time, datetime,inspect
num_threads = 2
root = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
with open (root+ "/ip_list.txt") as ips:
device_ip = list(ips)
class Writer_Worker(threading.Thread):
def __init__(self, queue, df, *args, **kwargs):
if not queue:
print("Device Queue not specified")
exit(1)
self.out_q = queue
self.df = df
super().__init__(*args, **kwargs)
def run(self):
while True:
try:
device_details = self.out_q.get(timeout=3)
except queue.Empty:
return
self.df[device_details[0]] = device_details
self.out_q.task_done()
class Worker(threading.Thread):
def __init__(self, queue, out_queue, device_password, *args, **kwargs):
if not queue:
print("Device Queue not specified")
exit(1)
self.queue = queue
self.pas = device_password
self.out_q = out_queue
super().__init__(*args, **kwargs)
def run(self):
while True:
try:
device_ip = self.queue.get(timeout=3)
except queue.Empty:
return
self.connect_to_device_and_process(device_ip)
self.queue.task_done()
def connect_to_device_and_process(self, device_ip):
st = str("Online")
try:
r = requests.post("https://["+device_ip+"]/?q=index.login&mimosa_ajax=1", {"username":"configure", "password":self.pas}, verify=False)
except requests.exceptions.ConnectionError:
st = str("Offline")
self.out_q.put([device_ip,st,"","","","","","","","","","","","","","","","","",""])
return
finally:
if 'Online' in st:
r = requests.get("https://["+device_ip+"]/cgi/dashboard.php", cookies=r.cookies, verify=False)
if "Response [401]" in str(r):
st2 = str("Password Error")
self.out_q.put([device_ip,st2,"","","","","","","","","","","","","","","","","",""])
else:
data = json.loads(r.content.decode())
output5 = data ['config'] ['Spectrum_Power']
self.out_q.put([device_ip,st,output5['Auto_Power'].replace('2', 'Max Power').replace('1', 'Min Power').replace('0', 'off'),output5['AutoConfig']])
def main():
start = time.time()
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
pas = input("Enter Device Password:")
df =pd.DataFrame(columns = ["IP","Status","Auto_Power","AutoChannel"])
q = queue.Queue(len(device_ip))
for ip in device_ip:
q.put_nowait(ip)
out_q = queue.Queue(len(device_ip))
Writer_Worker(out_q, df).start()
for _ in range(num_threads):
Worker(q, out_q, pas).start()
q.join()
print(df)
df.to_excel('iBridge_C5x_Audit_Report.xlsx', sheet_name='Detail', index = False)
if __name__ == "__main__":
main()
below is the error while running the script, seeps I am unable to login to this device.
Any help is appreciable.
You should use a thread pool that distributes the work between a fixed number of threads. This is a core feature of Python since version 3.2.
from concurrent.futures import ThreadPoolExecutor
Define a function perform(ip) that performs the request for one ip
Set variable numThreads to the number of desired threads
Run the thread-pool executor:
print(f'Using {numThreads} threads')
with ThreadPoolExecutor(max_workers=numThreads) as pool:
success = all(pool.map(perform, ips))
Source: https://docs.python.org/3/library/concurrent.futures.html
On that page you find an example even better tailored to your application: https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor-example
from threading import Thread
th = Thread(target=self.fill_imdb, args=(movies_info_part, "thread " + str(count)))
th.start()
fill_imdb is my method
Related
I am exploring Klein and Deferred. In the following example I am trying to increment a number using a child process and return it via Future. I am able to receive the Future call back.
The problem is that deferred object never calls the cb() function and the request made to endpoint never returns. Please help me identify the problem.
Following is my server.py code
from klein import Klein
from twisted.internet.defer import inlineCallbacks, returnValue
import Process4
if __name__ == '__main__':
app = Klein()
#app.route('/visit')
#inlineCallbacks
def get_num_visit(request):
try:
resp = yield Process4.get_visitor_num()
req.setResponseCode(200)
returnValue('Visited = {}'.format(resp))
except Exception as e:
req.setResponseCode(500)
returnValue('error {}'.format(e))
print('starting server')
app.run('0.0.0.0', 5005)
Following is Process4.py code
from multiprocessing import Process
from concurrent.futures import Future
from time import sleep
from twisted.internet.defer import Deferred
def foo(x):
result = x+1
sleep(3)
return result
class MyProcess(Process):
def __init__(self, target, args):
super().__init__()
self.target = target
self.args = args
self.f = Future()
self.visit = 0
def run(self):
r = foo(self.visit)
self.f.set_result(result=r)
def cb(result):
print('visitor number {}'.format(result))
return result
def eb(err):
print('error occurred {}'.format(err))
return err
def future_to_deferred(future):
d = Deferred()
def callback(f):
e = f.exception()
if e:
d.errback(e)
else:
d.callback(f.result())
future.add_done_callback(callback)
return d
def get_visitor_num():
p1 = MyProcess(target=foo, args=None)
d = future_to_deferred(p1.f)
p1.start()
d.addCallback(cb)
d.addErrback(eb)
sleep(1)
return d
Edit 1
Adding callbacks before starting the process p1 solves the problem of calling cb() function. But still the http request made to the endpoint does not return.
It turns out that setting future result self.f.set_result(result=r) in the run() method triggers the callback() method in the child process, where no thread is waiting for the result to be returned!
So to get the callback() function triggered in the MainProcess I had to get the result from the child-process using a multiprocess Queue using a worker thread in the MainProcess and then set the future result.
#notorious.no Thanks for reply. One thing which I noticed is that reactor.callFromThread does switches result from worker thread to MainThread in my modified code however d.callback(f.result()) works just fine but returns result from worker thread.
Following is the modified working code
server.py
from klein import Klein
from twisted.internet.defer import inlineCallbacks, returnValue
import Process4
if __name__ == '__main__':
app = Klein()
visit_count = 0
#app.route('/visit')
#inlineCallbacks
def get_num_visit(req):
global visit_count
try:
resp = yield Process4.get_visitor_num(visit_count)
req.setResponseCode(200)
visit_count = resp
returnValue('Visited = {}'.format(resp))
except Exception as e:
req.setResponseCode(500)
returnValue('error {}'.format(e))
print('starting server')
app.run('0.0.0.0', 5005)
Process4.py
from multiprocessing import Process, Queue
from concurrent.futures import Future
from time import sleep
from twisted.internet.defer import Deferred
import threading
from twisted.internet import reactor
def foo(x, q):
result = x+1
sleep(3)
print('setting result, {}'.format(result))
q.put(result)
class MyProcess(Process):
def __init__(self, target, args):
super().__init__()
self.target = target
self.args = args
self.visit = 0
def run(self):
self.target(*self.args)
def future_to_deferred(future):
d = Deferred()
def callback(f):
e = f.exception()
print('inside callback {}'.format(threading.current_thread().name))
if e:
print('calling errback')
d.errback(e)
# reactor.callFromThread(d.errback, e)
else:
print('calling callback with result {}'.format(f.result()))
# d.callback(f.result())
reactor.callFromThread(d.callback, f.result())
future.add_done_callback(callback)
return d
def wait(q,f):
r = q.get(block=True)
f.set_result(r)
def get_visitor_num(x):
def cb(result):
print('inside cb visitor number {} {}'.format(result, threading.current_thread().name))
return result
def eb(err):
print('inside eb error occurred {}'.format(err))
return err
f = Future()
q = Queue()
p1 = MyProcess(target=foo, args=(x,q,))
wait_thread = threading.Thread(target=wait, args=(q,f,))
wait_thread.start()
defr = future_to_deferred(f)
defr.addCallback(cb)
defr.addErrback(eb)
p1.start()
print('returning deferred')
return defr
Below is the code that I have that downloads various URLS into each separate thread, I was in attempt to make some changes before I implement the thread pool but with this change the queue is coming to be empty and download is not beginning.
import Queue
import urllib2
import os
import utils as _fdUtils
import signal
import sys
import time
import threading
class ThreadedFetch(threading.Thread):
""" docstring for ThreadedFetch
"""
def __init__(self, queue, out_queue):
super(ThreadedFetch, self).__init__()
self.queueItems = queue.get()
self.__url = self.queueItems[0]
self.__saveTo = self.queueItems[1]
self.outQueue = out_queue
def run(self):
fileName = self.__url.split('/')[-1]
path = os.path.join(DESKTOP_PATH, fileName)
file_size = int(_fdUtils.getUrlSizeInBytes(self.__url))
while not STOP_REQUEST.isSet():
urlFh = urllib2.urlopen(self.__url)
_log.info("Download: %s" , fileName)
with open(path, 'wb') as fh:
file_size_dl = 0
block_sz = 8192
while True:
buffer = urlFh.read(block_sz)
if not buffer:
break
file_size_dl += len(buffer)
fh.write(buffer)
status = r"%10d [%3.2f%%]" % (file_size_dl, file_size_dl * 100. / file_size)
status = status + chr(8)*(len(status)+1)
sys.stdout.write('%s\r' % status)
time.sleep(.05)
sys.stdout.flush()
if file_size_dl == file_size:
_log.info("Download Completed %s%% for file %s, saved to %s",
file_size_dl * 100. / file_size, fileName, DESKTOP_PATH)
below is the main function that does the call and initiation.
def main(appName):
args = _fdUtils.getParser()
urls_saveTo = {}
# spawn a pool of threads, and pass them queue instance
# each url will be downloaded concurrently
for i in range(len(args.urls)):
t = ThreadedFetch(queue, out_queue)
t.daemon = True
t.start()
try:
for url in args.urls:
urls_saveTo[url] = args.saveTo
# urls_saveTo = {urls[0]: args.saveTo, urls[1]: args.saveTo, urls[2]: args.saveTo}
# populate queue with data
for item, value in urls_saveTo.iteritems():
queue.put([item, value])
# wait on the queue until everything has been processed
queue.join()
print '*** Done'
except (KeyboardInterrupt, SystemExit):
lgr.critical('! Received keyboard interrupt, quitting threads.')
You create the queue and then the first thread which immediately tries to fetch an item from the still empty queue. The ThreadedFetch.__init__() method isn't run asynchronously, just the run() method when you call start() on a thread object.
Store the queue in the __init__() and move the get() into the run() method. That way you can create all the threads and they are blocking in their own thread, giving you the chance to put items into the queue in the main thread.
class ThreadedFetch(threading.Thread):
def __init__(self, queue, out_queue):
super(ThreadedFetch, self).__init__()
self.queue = queue
self.outQueue = out_queue
def run(self):
url, save_to = self.queue.get()
# ...
For this example the queue is unnecessary by the way as every thread gets exactly one item from the queue. You could pass that item directly to the thread when creating the thread object:
class ThreadedFetch(threading.Thread):
def __init__(self, url, save_to, out_queue):
super(ThreadedFetch, self).__init__()
self.url = url
self.save_to = save_to
self.outQueue = out_queue
def run(self):
# ...
And when the ThreadedFetch class really just consists of the __init__() and run() method you may consider moving the run() method into a function and start that asynchronously.
def fetch(url, save_to, out_queue):
# ...
# ...
def main():
# ...
thread = Thread(target=fetch, args=(url, save_to, out_queue))
thread.daemon = True
thread.start()
Im using the following code to multithread urlib2. However what is the best way to limit the number of threads that it consumes ??
class ApiMultiThreadHelper:
def __init__(self,api_calls):
self.q = Queue.Queue()
self.api_datastore = {}
self.api_calls = api_calls
self.userpass = '#####'
def query_api(self,q,api_query):
self.q.put(self.issue_request(api_query))
def issue_request(self,api_query):
self.api_datastore.update({api_query:{}})
for lookup in ["call1","call2"]:
query = api_query+lookup
request = urllib2.Request(query)
request.add_header("Authorization", "Basic %s" % self.userpass)
f = urllib2.urlopen(request)
response = f.read()
f.close()
self.api_datastore[api_query].update({lookup:response})
return True
def go(self):
threads = []
for i in self.api_calls:
t = threading.Thread(target=self.query_api, args = (self.q,i))
t.start()
threads.append(t)
for t in threads:
t.join()
You should use a thread pool. Here's my implementation I've made years ago (Python 3.x friendly):
import traceback
from threading import Thread
try:
import queue as Queue # Python3.x
except ImportError:
import Queue
class ThreadPool(object):
def __init__(self, no=10):
self.alive = True
self.tasks = Queue.Queue()
self.threads = []
for _ in range(no):
t = Thread(target=self.worker)
t.start()
self.threads.append(t)
def worker(self):
while self.alive:
try:
fn, args, kwargs = self.tasks.get(timeout=0.5)
except Queue.Empty:
continue
except ValueError:
self.tasks.task_done()
continue
try:
fn(*args, **kwargs)
except Exception:
# might wanna add some better error handling
traceback.print_exc()
self.tasks.task_done()
def add_job(self, fn, args=[], kwargs={}):
self.tasks.put((fn, args, kwargs))
def join(self):
self.tasks.join()
def deactivate(self):
self.alive = False
for t in self.threads:
t.join()
You can also find a similar class in multiprocessing.pool module (don't ask me why it is there). You can then refactor your code like this:
def go(self):
tp = ThreadPool(20) # <-- 20 thread workers
for i in self.api_calls:
tp.add_job(self.query_api, args=(self.q, i))
tp.join()
tp.deactivate()
Number of threads is now defined a priori.
I'm trying to start a data queue server under a managing process (so that it can later be turned into a service), and while the data queue server function works fine in the main process, it does not work in a process created using multiprocessing.Process.
The dataQueueServer and dataQueueClient code is based on the code from the multiprocessing module documentation here.
When run on its own, dataQueueServer works well. However, when run using a multiprocessing.Process's start() in mpquueue, it doesn't work (when tested with the client). I am using the dataQueueClient without changes to test both cases.
The code does reach the serve_forever in both cases, so I think the server is working, but something is blocking it from communicating back to the client in the mpqueue case.
I have placed the loop that runs the serve_forever() part under a thread, so that it can be stoppable.
Here is the code:
mpqueue # this is the "manager" process trying to spawn the server in a child process
import time
import multiprocessing
import threading
import dataQueueServer
class Printer():
def __init__(self):
self.lock = threading.Lock()
def tsprint(self, text):
with self.lock:
print text
class QueueServer(multiprocessing.Process):
def __init__(self, name = '', printer = None):
multiprocessing.Process.__init__(self)
self.name = name
self.printer = printer
self.ml = dataQueueServer.MainLoop(name = 'ml', printer = self.printer)
def run(self):
self.printer.tsprint(self.ml)
self.ml.start()
def stop(self):
self.ml.stop()
if __name__ == '__main__':
printer = Printer()
qs = QueueServer(name = 'QueueServer', printer = printer)
printer.tsprint(qs)
printer.tsprint('starting')
qs.start()
printer.tsprint('started.')
printer.tsprint('Press Ctrl-C to quit')
try:
while True:
time.sleep(60)
except KeyboardInterrupt:
printer.tsprint('\nTrying to exit cleanly...')
qs.stop()
printer.tsprint('stopped')
dataQueueServer
import time
import threading
from multiprocessing.managers import BaseManager
from multiprocessing import Queue
HOST = ''
PORT = 50010
AUTHKEY = 'authkey'
## Define some helper functions for use by the main process loop
class Printer():
def __init__(self):
self.lock = threading.Lock()
def tsprint(self, text):
with self.lock:
print text
class QueueManager(BaseManager):
pass
class MainLoop(threading.Thread):
"""A thread based loop manager, allowing termination signals to be sent
to the thread"""
def __init__(self, name = '', printer = None):
threading.Thread.__init__(self)
self._stopEvent = threading.Event()
self.daemon = True
self.name = name
if printer is None:
self.printer = Printer()
else:
self.printer = printer
## create the queue
self.queue = Queue()
## Add a function to the handler to return the queue to clients
self.QM = QueueManager
self.QM.register('get_queue', callable=lambda:self.queue)
self.queue_manager = self.QM(address=(HOST, PORT), authkey=AUTHKEY)
self.queue_server = self.queue_manager.get_server()
def __del__(self):
self.printer.tsprint( 'closing...')
def run(self):
self.printer.tsprint( '{}: started serving'.format(self.name))
self.queue_server.serve_forever()
def stop(self):
self.printer.tsprint ('{}: stopping'.format(self.name))
self._stopEvent.set()
def stopped(self):
return self._stopEvent.isSet()
def start():
printer = Printer()
ml = MainLoop(name = 'ml', printer = printer)
ml.start()
return ml
def stop(ml):
ml.stop()
if __name__ == '__main__':
ml = start()
raw_input("\nhit return to stop")
stop(ml)
And a client:
dataQueueClient
import datetime
from multiprocessing.managers import BaseManager
n = 0
N = 10**n
HOST = ''
PORT = 50010
AUTHKEY = 'authkey'
def now():
return datetime.datetime.now()
def gen(n, func, *args, **kwargs):
k = 0
while k < n:
yield func(*args, **kwargs)
k += 1
class QueueManager(BaseManager):
pass
QueueManager.register('get_queue')
m = QueueManager(address=(HOST, PORT), authkey=AUTHKEY)
m.connect()
queue = m.get_queue()
def load(msg, q):
return q.put(msg)
def get(q):
return q.get()
lgen = gen(N, load, msg = 'hello', q = queue)
t0 = now()
while True:
try:
lgen.next()
except StopIteration:
break
t1 = now()
print 'loaded %d items in ' % N, t1-t0
t0 = now()
while queue.qsize() > 0:
queue.get()
t1 = now()
print 'got %d items in ' % N, t1-t0
So it seems like the solution is simple enough: Don't use serve_forever(), and use manager.start() instead.
According to Eli Bendersky, the BaseManager (and it's extended version SyncManager) already spawns the server in a new process (and looking at the multiprocessing.managers code confirms this). The problem I have been experiencing stems from the form used in the example, in which the server is started under the main process.
I still don't understand why the current example doesn't work when run under a child process, but that's no longer an issue.
Here's the working (and much simplified from OP) code to manage multiple queue servers:
Server:
from multiprocessing import Queue
from multiprocessing.managers import SyncManager
HOST = ''
PORT0 = 5011
PORT1 = 5012
PORT2 = 5013
AUTHKEY = 'authkey'
name0 = 'qm0'
name1 = 'qm1'
name2 = 'qm2'
description = 'Queue Server'
def CreateQueueServer(HOST, PORT, AUTHKEY, name = None, description = None):
name = name
description = description
q = Queue()
class QueueManager(SyncManager):
pass
QueueManager.register('get_queue', callable = lambda: q)
QueueManager.register('get_name', callable = name)
QueueManager.register('get_description', callable = description)
manager = QueueManager(address = (HOST, PORT), authkey = AUTHKEY)
manager.start() # This actually starts the server
return manager
# Start three queue servers
qm0 = CreateQueueServer(HOST, PORT0, AUTHKEY, name0, description)
qm1 = CreateQueueServer(HOST, PORT1, AUTHKEY, name1, description)
qm2 = CreateQueueServer(HOST, PORT2, AUTHKEY, name2, description)
raw_input("return to end")
Client:
from multiprocessing.managers import SyncManager
HOST = ''
PORT0 = 5011
PORT1 = 5012
PORT2 = 5013
AUTHKEY = 'authkey'
def QueueServerClient(HOST, PORT, AUTHKEY):
class QueueManager(SyncManager):
pass
QueueManager.register('get_queue')
QueueManager.register('get_name')
QueueManager.register('get_description')
manager = QueueManager(address = (HOST, PORT), authkey = AUTHKEY)
manager.connect() # This starts the connected client
return manager
# create three connected managers
qc0 = QueueServerClient(HOST, PORT0, AUTHKEY)
qc1 = QueueServerClient(HOST, PORT1, AUTHKEY)
qc2 = QueueServerClient(HOST, PORT2, AUTHKEY)
# Get the queue objects from the clients
q0 = qc0.get_queue()
q1 = qc1.get_queue()
q2 = qc2.get_queue()
# put stuff in the queues
q0.put('some stuff')
q1.put('other stuff')
q2.put({1:123, 2:'abc'})
# check their sizes
print 'q0 size', q0.qsize()
print 'q1 size', q1.qsize()
print 'q2 size', q2.qsize()
# pull some stuff and print it
print q0.get()
print q1.get()
print q2.get()
Adding an additional server to share a dictionary with the information of the running queue servers so that consumers can easily tell what's available where is easy enough using that model. One thing to note, though, is that the shared dictionary requires slightly different syntax than a normal dictionary: dictionary[0] = something will not work. You need to use dictionary.update([(key, value), (otherkey, othervalue)]) and dictionary.get(key) syntax, which propagates across to all other clients connected to this dictionary..
I wrote simple web site crowler with threadpool. The problem is: then crawler is get all over site it must finish, but in real it wait for something in the end,and script dont finished, why this happend?
from Queue import Queue
from threading import Thread
import sys
from urllib import urlopen
from BeautifulSoup import BeautifulSoup, SoupStrainer
import re
from Queue import Queue, Empty
from threading import Thread
visited = set()
queue = Queue()
class Worker(Thread):
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
Thread.__init__(self)
self.tasks = tasks
self.daemon = True
self.start()
def run(self):
while True:
func, args, kargs = self.tasks.get()
print "startcall in thread",self
print args
try: func(*args, **kargs)
except Exception, e: print e
print "stopcall in thread",self
self.tasks.task_done()
class ThreadPool:
"""Pool of threads consuming tasks from a queue"""
def __init__(self, num_threads):
self.tasks = Queue(num_threads)
for _ in range(num_threads): Worker(self.tasks)
def add_task(self, func, *args, **kargs):
"""Add a task to the queue"""
self.tasks.put((func, args, kargs))
def wait_completion(self):
"""Wait for completion of all the tasks in the queue"""
self.tasks.join()
def process(pool,host,url):
try:
print "get url",url
#content = urlopen(url).read().decode(charset)
content = urlopen(url).read()
except UnicodeDecodeError:
return
for link in BeautifulSoup(content, parseOnlyThese=SoupStrainer('a')):
#print "link",link
try:
href = link['href']
except KeyError:
continue
if not href.startswith('http://'):
href = 'http://%s%s' % (host, href)
if not href.startswith('http://%s%s' % (host, '/')):
continue
if href not in visited:
visited.add(href)
pool.add_task(process,pool,host,href)
print href
def start(host,charset):
pool = ThreadPool(7)
pool.add_task(process,pool,host,'http://%s/' % (host))
pool.wait_completion()
start('simplesite.com','utf8')
The problem I see is that you never quit the while in run. So, it will block forever. You need to break that loop when the jobs are done.
You could try to :
1) insert
if not func: break
after task.get(...) in run.
2) append
pool.add_task(None, None, None)
at the end of process.
This is a way for process to notify the pool that he has no more task to process.