def generate_in_background(generator, num_cached=10):
"""
Runs a generator in a background thread, caching up to `num_cached` items.
"""
import queue
queue = queue.Queue(maxsize=num_cached)
sentinel = object() # guaranteed unique reference
# define producer (putting items into queue)
def producer():
for item in generator:
queue.put(item)
queue.put(sentinel)
# start producer (in a background thread)
import threading
thread = threading.Thread(target=producer)
thread.daemon = True
thread.start()
# run as consumer (read items from queue, in current thread)
item = queue.get()
while item is not sentinel:
yield item
item = queue.get()
def _process_batch():
dev_grad_batch, dev_events, job_event = queue.get()
dev_coalesced = []
# Coalesce the tensors on all devices and start a local reduction
for dev_id, grad_batch, event, stream in zip(device_ids, dev_grad_batch, dev_events, reduction_streams):
with torch.cuda.device(dev_id), torch.cuda.stream(stream):
stream.wait_event(event)
coalesced = _flatten_tensors(grad_batch)
dev_coalesced.append(coalesced)
# Wait for all copies to complete before starting the NCCL kernel
for stream in reduction_streams:
stream.synchronize()
nccl.reduce(dev_coalesced, root=device_ids[0], streams=nccl_streams)
# From now on we're only going to work on the first device (from device_ids)
grad_batch = dev_grad_batch[0]
coalesced = dev_coalesced[0]
reduce_stream = reduction_streams[0]
with torch.cuda.stream(reduce_stream):
reduce_stream.wait_stream(nccl_streams[0])
coalesced /= dist.get_world_size()
dist.all_reduce(coalesced, group=group_id)
for grad, reduced in zip(grad_batch, _unflatten_tensors(coalesced, grad_batch)):
grad.copy_(reduced)
job_event.set()
def start(self):
"Start module to start reading files"
# Create new threads
thread1 = RouterThread(1, "Data Link 1", in_file1, delay1, queueList[0])
thread2 = RouterThread(2, "Data Link 2", in_file2, delay2, queueList[1])
thread3 = RouterThread(3, "Data Link 3", in_file3, delay3, queueList[2])
# Start new Threads
thread1.start()
thread2.start()
thread3.start()
# Add threads to thread list
self.threads.append(thread1)
self.threads.append(thread2)
self.threads.append(thread3)
# Wait for all threads to complete
for t in self.threads:
t.join()
print("Exiting Main Thread")
packetParser = self.PacketParser()
# Print output - Get bytes from Queue
print("Printing items from each queue -");
for queue in queueList:
while not queue.empty():
print("***********************************************************************************************************")
packetParser.parsePacket( queue.get() )
def default_filter(queue, *args):
while True:
line = queue.get()
if not line:
self.logger.debug('Process exiting (status_loop)')
break
yield line
def run(self):
while True:
message = queue.get()
logging.info("Main server recieved: %s" % (sub("\0", "!",
message)))
for con in self.conns:
con.send(message)
def blockingCallFromThread(f, *a, **kw):
"""
Run a function in the reactor from a thread, and wait for the result
synchronously, i.e. until the callback chain returned by the function get a
result.
@param f: the callable to run in the reactor thread
@type f: any callable.
@param a: the arguments to pass to C{f}.
@param kw: the keyword arguments to pass to C{f}.
@return: the result of the callback chain.
@raise: any error raised during the callback chain.
"""
from twisted.internet import reactor
queue = queue.Queue()
def _callFromThread():
result = defer.maybeDeferred(f, *a, **kw)
result.addBoth(queue.put)
reactor.callFromThread(_callFromThread)
result = queue.get()
if isinstance(result, failure.Failure):
# This makes it easier for the debugger to get access to the instance
try:
result.raiseException()
except Exception as e:
raise e
return result
def worker(queue, args):
while True:
action = queue.get()
if action is None:
break
doaction(action, args)
queue.task_done()
def absoluteFade(indexes, rgb, fadeTime):
'''Is given a color to fade to, and executes fade'''
if not fadeTime:
fadeTime = 1 / frameRate
for c in rgb:
c = makeEightBit(c)
#Calculates how many individual fade frames are needed
alterations = int(fadeTime * frameRate)
queueList = []
queueLock.acquire()
while not queue.empty():
queueList.append(queue.get())
queue.task_done()
#Amount of frames that need to be added to queue
appends = alterations - len(queueList)
#fill out the queue with blank dictionaries to populate
if appends > 0:
for i in range(abs(appends)):
queueList.append({})
#Iterate down indexes, figure out what items in queue need to be altered
for i in indexes:
#INVESTIGATE: THIS MIGHT BE THE SOURCE OF FLASHING ISSUES AT THE START OF A COMMAND
start = pixels[i]
bridgeGenerator = bridgeValues(alterations, start, rgb)
for m in range(alterations):
queueList[m][i] = next(bridgeGenerator)
#If this command overrides a previous command to the pixel, it should wipe any commands remaining
if appends < 0:
for r in range(abs(appends)):
if i in queueList[alterations + r]:
del queueList[alterations + r][i]
while queueList:
queue.put(queueList.pop(0))
queueLock.release()
def storeResults(queue, key):
server = redis.StrictRedis()
while True:
result = queue.get()
if result == 'END':
break
server.rpush(key, json.dumps(result))
def multiCommand(commands):
maxAlterations = int(max([i[2] for i in commands]) * frameRate)
queueList = []
queueLock.acquire()
while not queue.empty():
queueList.append(queue.get())
queue.task_done()
appends = maxAlterations - len(queueList)
if appends > 0:
for i in range(abs(appends)):
queueList.append({})
for c in commands:
commandAlterations = int(c[2] * frameRate)
for i in range(c[0][0], c[0][1]):
start = pixels[i]
bridgeGenerator = bridgeValues(commandAlterations, start, c[1])
for m in range(commandAlterations):
queueList[m][i] = next(bridgeGenerator)
if appends < 0:
for r in range(abs(appends)):
if i in queueList[commandAlterations + r]:
del queueList[commandAlterations + r][i]
while queueList:
queue.put(queueList.pop(0))
queueLock.release()
def ucs(source, target, graph):
""" Uniform-cost graph search """
queue = queue.PriorityQueue() # fringe
queue.put((0, source))
parent = {source:None}
visited = {}
while not queue.empty():
(d, v_in) = queue.get()
if v_in not in visited or d < visited[v_in]:
if v_in == target:
return (d, build_path(parent, target))
for v_out in graph.adj(v_in):
cost = graph.distance(v_in, v_out) + d
if v_out not in visited:
queue.put((cost, v_out))
parent[v_out] = v_in
visited[v_in] = cost
return None
def sender(queue):
# TODO set time limit for checking
header = Header()
header.size = 1416
while(True):
#set up connection
payload = bytearray()
payload.extend(header.serialize())
count = 0
while(count < 22):
#print("have %d sludge " % (count))
hash = queue.get()
payload.extend(hash)
count += 1
try:
print("sending sludge downstream")
attempts = 0
while ( attempts < 10 ):
try:
sludge_outgoing = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sludge_outgoing.connect(("downstream", 4444))
sludge_outgoing.send(payload)
sludge_outgoing.close()
break;
except:
traceback.print_exc()
if ( attemps == 9 ):
raise Exception
attempts +=1
except:
# TODO make error log
f = open('/home/sbartholomew/sludgeOut', 'wb')
f.write(payload)
f.close()
def next_item(self):
queue = self._queue
try:
item = queue.get(block=True, timeout=5)
return item
except Exception:
return None
def run_job(self, deviceid):
queue = self._queue
while not self._shutdown:
path = None
try:
path = queue.get(timeout=1)
except:
pass
if path:
if deviceid is None:
logger.info('Running ' + path)
else:
logger.info("Running " + path + " on device " + str(deviceid))
self._setRunning(path)
runsh = os.path.join(path, 'run.sh')
jobsh = os.path.join(path, 'job.sh')
self._createJobScript(jobsh, path, runsh, deviceid)
try:
ret = check_output(jobsh)
logger.debug(ret)
except Exception as e:
logger.info('Error in simulation {}. {}'.format(path, e))
self._setCompleted(path)
queue.task_done()
continue
logger.info("Completed " + path)
self._setCompleted(path)
queue.task_done()
logger.info("Shutting down worker thread")
def run_job(obj, gpuid, jobfun, jobargs):
queue = obj.queue
while not obj.shutdown:
path = None
try:
path = queue.get(timeout=1)
except:
pass
if path:
try:
logger.info("Running " + path + " on GPU device " + str(gpuid))
obj.running(path)
try:
jobfun(*jobargs, path=path, gpuid=gpuid)
except:
obj.completed(path)
queue.task_done()
continue
logger.info("Completed " + path)
obj.completed(path)
queue.task_done()
except:
logger.error("Error running job {}".format(path))
obj.completed(path)
queue.task_done()
continue
logger.info("Shutting down worker thread")
def worker(id, queue):
while True:
try:
obj = queue.get(timeout=3)
print(id, obj)
except:
break
def runThread(self, port):
"""Router's infinite thread loop. Receives and sends packages
to hosts/routers."""
queue = self.portBuffer[port]
while True:
packet = queue.get()
self.process(port, packet)
queue.task_done()
def async_write(buffer=[]):
item = queue.get()
buffer.append(item)
if len(buffer) > 500 or queue.empty():
log.debug('Processing {} queue items.'.format(len(buffer)))
with db.transaction():
write_buffer(buffer)
buffer.clear()
def handle_update():
while True:
label, content = queue.get()
msg = json.dumps({'label': label, 'content': content})
print('>>> Sending:', msg)
print('>>> To:', clients)
for client in clients:
client.sendMessage(msg.encode('utf8'), isBinary=False)
def submit_to_olog(queue, cb):
while True:
name, doc = queue.get() # waits until document is available
try:
cb(name, doc)
except Exception as exc:
warn('This olog is giving errors. This will not be logged.'
'Error:' + str(exc))
def run_find_all_symbols(args, tmpdir, build_path, queue):
"""Takes filenames out of queue and runs find-all-symbols on them."""
while True:
name = queue.get()
invocation = [args.binary, name, '-output-dir='+tmpdir, '-p='+build_path]
sys.stdout.write(' '.join(invocation) + '\n')
subprocess.call(invocation)
queue.task_done()
def submit_results(queue, submit_url):
s = requests.Session()
while True:
crash_id, result = queue.get()
logger.debug('%d results waiting', queue.qsize())
logger.debug('submitting %d', crash_id)
logger.info(result)
_ = s.post(submit_url % crash_id, data=json.dumps(result), headers={'content-type': 'application/json'}).content
def run(self):
global queue
while True:
if queue.qsize() > 100:
for i in range(3):
# get是从queue中取出一个值
msg = self.name + '消费了 '+queue.get()
print(msg)
time.sleep(1)
def run(self):
queue = self.queue
while True:
try:
task = queue.get()
log.info("worker执行"+str(task))
task._execute()
except Exception as e:
log.exception(e)
def convert(queue):
cmd_flac = ["flac", "--decode", "--silent", "--stdout"]
cmd_lame = ["lame", "-h" "--preset", "224"]
while not queue.empty() and not abort.is_set():
f = queue.get()
pFlac = Popen( cmd_flac + [ f[0] ], stdout=PIPE)
pLame = Popen( cmd_lame + [ f[1] ], stdout=PIPE, stdin=pFlac.stdout, stderr=STDOUT )
stdout, stderr = pLame.communicate()
def handle(self, call, queue): while 1: if queue.empty(): pass else: m = queue.get() call(m) time.sleep(0.1)
def _process_queue(queue):
while True:
processor, args = queue.get()
logging.debug("calling %s with %d arguments: %s", processor, len(args), args)
try:
processor(*args)
except:
logging.exception("")
queue.task_done()
def consumer(queue, name):
def _print(string):
print("%s: %s" % (name, string))
while True:
widget = queue.get()
_print("will crank widget: %s" % widget)
time.sleep(random.choice((1,3,5,3,6,7)))
_print("Cranket!")
def run_task(): while True: ev, params = yield from queue.get() if ev == "log_chat": yield from do_log_chat(*params) elif ev == "clear_chat_log": yield from do_clear_chat_log(*params) elif ev == "rebuild_all": yield from do_rebuild_all() elif ev == "exit": break
def Main():
#try statement for creating the catalog database table if it does not exist, otherwise saves a boolean value that the catalog was already created
try:
create_catalog(cursor, connection)
except:
cat_created = False
success = [] #array that will be used to hold the queue values for successful queries
updated = 0 #boolean value that is used to show if catalog was updated
count = 0 #integer to hold the amount of times we iterate through the for loop that updates the catalog database
tables = [] #array to hold the tables used in the query
firstsplit = [] #array to help in the rudimentary parsing of the query
nodeid = [] #array to hold the nodeid where query was sent
hostnames = [] #array to hold the hostname where query was sent
parse = query.split(" ") #rudimentary parse of the query
#for loop the parses the query, finds every instance of table and stores the tablename into the table array variable
for x, word in enumerate(parse):
if word == "TABLE":
firstsplit.append(parse[x + 1])
#for loop that completes the second part of the parse
for x in firstsplit:
split = x.split('(', 1)
tables.append(split[0])
nodes = ConfigSectionMap("nodecount")['numnodes'] #variable to hold the total amount of nodes listed in the catalog databse
threads = [] #array to hold the parallel threads that will be created
#for loop that creates the threads to send queries to multiple servers, and then saves them to the threads array.
for x in range(1, int(nodes) + 1):
section = "node " + str(x)
threads.append(myThread(x, ConfigSectionMap(section)['hostname'], ConfigSectionMap(section)['ip'], query, queue))
(threads[-1].start()) #starts all threads
nodeid.append(x) #saves the node where the thread is sending the query to into the nodeid array
hostnames.append(ConfigSectionMap(section)['hostname']) #saves the hostname where the thread is sending the query to into the hostnames array
#for loop that joins all the threads
for t in threads:
t.join()
#while loop to save the success or fail of every thread into the success array
while not queue.empty():
success.append(queue.get())
#for loop that iterates through the success array, if a query was successfully updated it checks to see if the query contained a drop or create statement.
#if so, calls the proper function to update the catalog
for x in success:
if x == 1:
if parse[0] == "DROP":
remove_catalog(cursor, tables[0],connection)
updated = 1
if parse[0] == "CREATE":
add_catalog(cursor, tables[0], hostnames[count], 0, nodeid[count], 0, 0, 0, connection)
updated = 1
count += 1
#for loop checks to see if any of the queries succeeded and contained a drop or create statement, if true, prints out a catalog updated statement, and if false, prints out catalog had no updates
if updated == 1:
print(cathost + ": catalog updated.")
else:
print(cathost + ": catalog had no updates.")
connection.close() #closes the connection to the database
def launcher(logger, queue, lauchfrequency, maxruntime):
""""""
maxseconds = maxruntime * 60
time.sleep(3) # allow jobqserver to start
while True:
time.sleep(lauchfrequency)
job = queue.get(block=True, timeout=None)
if job:
jobnumber = job[1]
task_to_run = job[2]
# Start a timer thread for maxruntime error
timer_thread = threading.Timer(
maxseconds,
maxruntimeerror,
args=(logger, maxruntime, jobnumber, task_to_run),
)
timer_thread.start()
try:
t0 = datetime.datetime.now()
logger.info('Starting job %(job)s', {'job': jobnumber})
result = subprocess.call(task_to_run,
stdin=open(os.devnull, 'r'),
stdout=open(os.devnull, 'w'),
stderr=open(os.devnull, 'w'))
t1 = datetime.datetime.now()
time_taken = (t1 - t0).seconds
logger.info(
'Finished job %(job)s, elapsed time %(time_taken)s, result %(result)s',
{
'job': jobnumber,
'time_taken': time_taken,
'result': result
})
except Exception as e:
logger.error('Error starting job {}: {}'.format(jobnumber, e))
botslib.sendbotserrorreport(
'[Bots Job Queue] - Error starting job',
'Error starting job {}:\n {}\n\n {}'.format(
jobnumber, task_to_run, e))
timer_thread.cancel()
queue.task_done()
def main():
setupLogger()
# gently manage control-c interrupt
# if necessary
def control_c_handler(sig, frame):
raise Exception("Control-C received")
signal.signal(signal.SIGINT, control_c_handler)
# create queue connector
service_bus = AzureQueueManager()
service_bus.connect()
service_bus.topics() # test connection credential asking for topics
# start reading message queue
queue = queue.Queue()
queueListenerThread = Thread(target=populateMessageQueue,
args=(service_bus, 'test-topic',
'test-suscriber-1', queue, 10000))
queueListenerThread.daemon = True
queueListenerThread.start() #start collecting message form queue
# main loop
while True:
message = none
try:
message = queue.get(block=False, timeout=0)
except queue.empty:
pass
if message:
# parse
# if drone start ODB
# if satellite start GDAL
# started have to be put in queue to check if finished with relative message
# check queued processes
# if queued process ed => unlog message and remove it
pass
time.sleep(2000)
def evaluate(model, dataloader, queue, criterion, device):
logger.info('evaluate() start')
total_loss = 0.
total_num = 0
total_dist = 0
total_length = 0
total_sent_num = 0
model.eval()
with torch.no_grad():
while True:
feats, scripts, feat_lengths, script_lengths = queue.get()
if feats.shape[0] == 0:
break
feats = feats.to(device)
scripts = scripts.to(device)
src_len = scripts.size(1)
target = scripts[:, 1:]
model.module.flatten_parameters()
logit = model(feats,
feat_lengths,
scripts,
teacher_forcing_ratio=0.0)
logit = torch.stack(logit, dim=1).to(device)
y_hat = logit.max(-1)[1]
loss = criterion(logit.contiguous().view(-1, logit.size(-1)),
target.contiguous().view(-1))
total_loss += loss.item()
total_num += sum(feat_lengths)
display = random.randrange(0, 100) == 0
dist, length = get_distance(target, y_hat, display=display)
total_dist += dist
total_length += length
total_sent_num += target.size(0)
logger.info('evaluate() completed')
return total_loss / total_num, total_dist / total_length
def evaluate(model,
dataloader,
queue,
criterion,
device,
confusion_matrix=None):
logger.info('evaluate() start')
total_loss = 0
total_num = 0
total_correct = 0
total_sent_num = 0
model.eval()
with torch.no_grad():
while True:
feats, label, feat_lengths = queue.get()
if feats.shape[0] == 0:
break
feats = feats.to(device)
label = label.to(device)
logit = model(feats, feat_lengths).to(device)
y_hat = logit.max(-1)[1]
if type(confusion_matrix) is torch.Tensor:
update_confusion_matrix(confusion_matrix,
label.cpu().numpy(),
y_hat.cpu().numpy())
correct = torch.eq(y_hat, label)
batch_correct = torch.nonzero(correct).size(0)
total_correct += batch_correct
loss = criterion(logit.contiguous(), label)
total_loss += loss.item()
total_num += logit.size(0)
total_sent_num += label.size(0)
logger.info('evaluate() completed')
return total_loss / total_num, total_correct / total_sent_num
def checkerLoop(queue):
""" This checks each incoming file. If they are not PNG files they
get deleted. This will protect against uploading HTML and XSS
This will be run as a background thread
"""
while True:
filename = queue.get()
res = subprocess.run(["file", filename],
shell=True,
timeout=15,
stdout=subprocess.PIPE)
res = res.stdout.decode('utf-8')
print(res)
if not ("PNG image data" in res or "JPEG image data" in res):
os.remove(filename)
bad_file_log.add(filename)
else:
suspicious_file_log.remove(os.path.basename(filename))
def _validate(self, model: nn.Module, queue: queue.Queue) -> float:
"""
Run training one epoch
Args:
model (torch.nn.Module): model to train
queue (queue.Queue): validation queue, containing input, targets, input_lengths, target_lengths
Returns: loss, cer
- **loss** (float): loss of validation
- **cer** (float): character error rate of validation
"""
target_list, predict_list = list(), list()
cer = 1.0
model.eval()
logger.info('validate() start')
while True:
inputs, targets, input_lengths, target_lengths = queue.get()
if inputs.shape[0] == 0:
break
inputs = inputs.to(self.device)
targets = targets[:, 1:].to(self.device)
model.to(self.device)
if isinstance(model, nn.DataParallel):
y_hats = model.module.recognize(inputs, input_lengths)
else:
y_hats = model.recognize(inputs, input_lengths)
for idx in range(targets.size(0)):
target_list.append(self.vocab.label_to_string(targets[idx]))
predict_list.append(self.vocab.label_to_string(y_hats[idx].cpu().detach().numpy()))
cer = self.metric(targets, y_hats)
self._save_result(target_list, predict_list)
logger.info('validate() completed')
return cer
def clockLoop():
'''Removes items from the queue and transmits them to the controller'''
print('Initiating Clocker')
while True:
#This was one line further down, probably a mistake
alteration = queue.get(True, None)
queueLock.acquire()
queue.task_done()
for alt in alteration:
pixels[alt] = alteration[alt]
if OLA:
listStr = str(pixels)[1:-1]
requests.post(olaUrl, data={'u': 1, 'd': listStr})
else:
for alt in alteration:
dmx.setChannel(alt, alteration[alt])
dmx.render()
queueLock.release()
time.sleep((1 / frameRate) * .75)
def run(self):
queue = self.queue
while True:
# Grab our data
callback, requests = queue.get()
# Grab prices, this is the time-consuming part
if len(requests) > 0:
Price.fetchPrices(requests)
wx.CallAfter(callback)
queue.task_done()
# After we fetch prices, go through the list of waiting items and call their callbacks
for price in requests:
callbacks = self.wait.pop(price.typeID, None)
if callbacks:
for callback in callbacks:
wx.CallAfter(callback)
def loop(self):
queue = self.new_queue()
sock = self.sock
while True:
parts = queue.get()
if parts is None:
break
try:
if len(parts) > 1:
sock.send_multipart(parts, copy=False)
else:
sock.send(parts[0], copy=False)
except zmq.ZMQError as err:
new_queue = self.new_queue()
flushed = queue.qsize()
queue = new_queue
log.error(
f'Error send ZMQ: {err!r}. Flushed {flushed} messages')
self.new_queue()
def queue_consumer(queue: queue.Queue, url_count: int, results_callback):
i = 0
result_count = 0
with progressbar.ProgressBar(max_value=url_count, redirect_stdout=True) as bar:
while True:
finished = queue.get()
if type(finished) == ImageInfo:
results_callback(finished)
result_count += 1
elif type(finished) == str:
results_callback(finished, error=True)
else:
queue.task_done()
break
queue.task_done()
bar.update(i)
i += 1
def searchContract(queue, collection, parser):
while not exitFlag:
queueLock.acquire()
if not queue.empty():
#address = queue.get()
#queueLock.release()
#result = collection.find({"address": address})
contract = queue.get()
queueLock.release()
#byteCode = queue.get()
#queueLock.release()
#result = collection.find({"byteCode": byteCode}).sort("balance", pymongo.DESCENDING).limit(1)
#if result.count() > 0:
# contract = list(result)[0]
#print('Writing contract to file: '+contract['address'])
file_path = CONTRACT_FOLDER + str(contract['address'])
#file_path = CONTRACT_FOLDER+str(contract['contractName'])
extension = ""
counter = 1
# Write byte code to file
if BYTECODE:
writeLock.acquire()
while os.path.exists(file_path + extension + ".bin"):
counter += 1
extension = "_" + str(counter)
file = open(file_path + extension + ".bin", "w")
file.write(parser.unescape(contract['byteCode']))
file.close()
writeLock.release()
# Write source code to file
else:
writeLock.acquire()
while os.path.exists(file_path + extension + ".sol"):
counter += 1
extension = "_" + str(counter)
file = open(file_path + extension + ".sol", "w")
file.write(parser.unescape(contract['sourceCode']))
file.close()
writeLock.release()
else:
queueLock.release()
def searchRange(self, root, k1, k2):
# write your code here
import queue
if root is None:
return []
queue = queue.Queue()
queue.put(root)
result = []
while not queue.empty():
node = queue.get()
if node.val <= k2 and node.val >= k1:
result.append(node.val)
if node.left:
queue.put(node.left)
if node.right:
queue.put(node.right)
return result
def BFS(queue, game, celltype):
matrix = game.env.grid
current_index = queue.get()
current_x, current_y = current_index[0], current_index[1]
element = matrix[current_y, current_x]
if element == celltype: return [current_y, current_x]
for n in range(current_x - 1, current_x + 2):
for m in range(current_y - 1, current_y + 2):
if not (n==current_x and m==current_y) \
and n>-1 and m>-1 \
and n<matrix.shape[0] and m<matrix.shape[1] \
and (n,m) not in queue.queue :
queue.put((n, m))
return BFS(queue, game, celltype)
def consume_output_queue(queue):
""" Gets message objects from queue and sends them
message objects are of the following form: {"sleep":0, "channel":"", "text":"", "blocks":[]} """
while True:
data = queue.get()
if 'text' in data:
response = webclient.chat_postMessage(channel=data['channel'],
text=data['text'])
elif 'blocks' in data:
response = webclient.chat_postMessage(channel=data['channel'],
blocks=data['blocks'])
else:
raise RuntimeError("Bad output message")
if not response['ok']:
raise RuntimeError("Slack error: {}".format(response['error']))
if 'sleep' in data:
sleep(data['sleep'])
def _loop(self, qid):
if not self._is_valid_qid(qid):
return
data = self._queues[qid]
if not data["active"]:
return
queue = data["queue"]
consumer = data["consumer"]
unpack_result = data["unpack_result"]
exception_handler = data["exception_handler"]
latency = data["latency"]
if not queue.empty():
result = queue.get()
self._dispatch_result(result, consumer, unpack_result,
exception_handler)
if result is QueueTail:
return
next_call = lambda self=self, qid=qid: self._loop(qid)
self._tk.after(latency, func=next_call)
def insert_url(thread_name, queue, table):
while not EXIT_FLAG:
QUEUE_LOCK.acquire()
if not WORK_QUEUE.empty():
try:
url = queue.get()
QUEUE_LOCK.release()
count = list(
database_util.search_sql(
'select count(*) url from ' + table + ' where url=%s',
url)[1])[0][0]
if count == 0:
sql = 'insert into ' + table + ' set url=%s'
database_util.update_sql(sql, url)
except Exception as err:
print('thread_queue update_price err:' + str(err))
else:
QUEUE_LOCK.release()
time.sleep(1)
def new_function(*args, **kwargs):
"""
Create a queue, create a queuefun from original_function and make the
new queuefun the target of a thread, passing the thread target
original_function's args and kwargs. Then instantiate a new Tk Toplevel
Frame called master and a new waitWidget with the queue and master.
Start master's mainloop which exits when the original_function's
results are fed to the queue. Destroy master and return the
original_function's results.
"""
queue = queue.Queue()
queuefun = setqueue(original_function, queue)
thread = Thread(target=queuefun, args=args, kwargs=kwargs)
thread.start()
master = Toplevel()
waitBox = waitWidget(queue, master)
waitBox.mainloop()
master.destroy()
return queue.get()
def process_datastream(self, queue):
while ((len(self.dataMatrix[0])< self.max_samples and not self.continuous_mode) or \
(self.read_samples_continuously and self.continuous_mode)):
while not queue.empty():
timestamp, channel_data = queue.get()
if not self.quiet:
print(
f"timestamp:{timestamp} sample_number: {sample_number}| ",
end='')
for channel_number, sample in enumerate(channel_data):
print(f"{channel_number + 1}:{sample}", end='')
if not self.pause_toggle:
with open("../data/" + self.fileName, 'a') as file:
file.writelines(
str(timestamp) + '\t' +
'\t'.join(str(j) for j in channel_data) + '\n')
self.dataMatrix[0].append(timestamp)
for channel_number, sample in enumerate(channel_data):
self.dataMatrix[channel_number + 1].append(sample)
def next_request(self):
if queue.qsize() == 0 and len(self._crawling) == 0: # 所有调度都完成
self._close.callback(None)
return
if len(self._crawling) >= self._max_currentcy:
return
while len(self._crawling) < self._max_currentcy:
try:
request = queue.get(block=False)
self._crawling.append(request)
d_defer = getPage(request.url.encode('utf-8'))
# 页面下载完成 get_reponse_callback 调用用户spider中自定义的parse方法 并且将新请求加入到调度器
d_defer.addCallback(self.get_reponse_callback, request)
d_defer.addCallback(
lambda _: reactor.callLater(0, self.next_request))
except Exception as e:
return
def bfs(self, start, end):
import queue
queue = queue.Queue()
visited = set()
queue.put(start)
distance = 1
while not queue.empty():
qsize = queue.qsize()
for i in range(qsize):
word = queue.get()
visited.add(word)
if word == end:
return distance
for new_word in self.get_next_word(word):
if new_word not in visited:
queue.put(new_word)
distance += 1
return 0
def run(self, queue):
fileIndex = self.lastIndex
createFile(clientId=self.clientId)
# while True:
if not queue.empty():
r = self.speech_recognizer
audio = queue.get()
logging.debug('Getting ' + str(audio) + ' : ' +
str(queue.qsize()) + ' items in queue')
# audio = 'recording-%i.wav' % fileIndex
path = self.clientId + "/" + audio
if os.path.isfile(path):
print('we are reading ' + path)
try:
with sr.AudioFile(path) as source:
audio = r.record(source)
except IOError as e:
print(e)
pass
try:
text = r.recognize_google(audio, language="en-US")
writeToFile(text + "\n", self.clientId, "a+")
print('Done!')
print(text)
fileIndex += 1
if text == "audio stop":
fileIndex = 0
except sr.UnknownValueError:
writeToFile(
"Google Speech Recognition could not understand audio"
+ "\n", self.clientId, "a+")
except sr.RequestError:
writeToFile(
"Could not request results from Google Speech Recognition service",
self.clientId, "a+")
except Exception as e:
print(e)
else:
print("no more files to transcribe for %s ......... " %
self.clientId)
return queue
def run_job(obj, ngpu, acemd, datadir):
import sys
queue = obj.queue
while not obj.shutdown:
path = None
try:
path = queue.get(timeout=1)
except:
pass
if path:
try:
logger.info("Running " + path + " on GPU " + str(ngpu))
obj.running(path)
cmd = 'cd {}; {} --device {} input > log.txt 2>&1'.format(os.path.normpath(path), acemd, ngpu)
try:
check_output(cmd, shell=True)
except CalledProcessError:
logger.error('Error in ACEMD for path: {}. Check the {} file.'.format(path, os.path.join(path, 'log.txt')))
obj.completed(path)
queue.task_done()
continue
# If a datadir is provided, copy finished trajectories there. Only works for xtc files.
if datadir is not None:
if not os.path.isdir(datadir):
os.mkdir(datadir)
simname = os.path.basename(os.path.normpath(path))
odir = os.path.join(datadir, simname)
os.mkdir(odir)
finishedtraj = glob(os.path.join(path, '*.xtc'))
logger.info("Moving simulation {} to {}.".format(finishedtraj[0], odir))
move(finishedtraj[0], odir)
logger.info("Completed " + path)
obj.completed(path)
queue.task_done()
except:
logger.error("Error running job")
obj.completed(path)
queue.task_done()
continue
logger.info("Shutting down worker thread")
def validate(self, model, queue):
"""
Run training one epoch
Args:
model (torch.nn.Module): model to train
queue (queue.Queue): validation queue, containing input, targets, input_lengths, target_lengths
Returns: loss, cer
- **loss** (float): loss of validation
- **cer** (float): character error rate of validation
"""
cer = 1.0
model.eval()
logger.info('validate() start')
with torch.no_grad():
while True:
inputs, scripts, input_lengths, script_lengths = queue.get()
if inputs.shape[0] == 0:
break
inputs = inputs.to(self.device)
scripts = scripts.to(self.device)
targets = scripts[:, 1:]
model.module.flatten_parameters()
output = model(inputs,
input_lengths,
teacher_forcing_ratio=0.0)[0]
logit = torch.stack(output, dim=1).to(self.device)
hypothesis = logit.max(-1)[1]
cer = self.metric(targets, hypothesis)
del inputs, input_lengths, scripts, targets, output, logit, hypothesis
logger.info('validate() completed')
return cer
def evaluate(model, dataloader, queue, criterion, device):
total_loss = 0.
batch = 0
# set model to eval mode
model.eval()
# begin logging
logger.info('evaluate() start')
begin = time.time()
with torch.no_grad():
while True:
batch += 1
if queue.empty():
logger.debug('queue is empty')
# input, target tensor shapes: (batch_size, n_mfcc, n_frames)
inputs, targets = queue.get()
batch_size = inputs.shape[0]
# if no data from queue, end evaluation
if batch_size == 0:
break
# load tensors to device
inputs = inputs.to(device)
targets = targets.to(device)
# output tensor shape: (batch_size, n_mfcc, n_frames)
# forward pass
output = model(inputs).to(device)
# compute loss
loss = criterion(output.contiguous().view(-1), targets.contiguous().view(-1))
total_loss += loss.item()
# finish logging
logger.info('evaluate() completed')
return total_loss / batch
def _fn(*args, **kwargs):
for i in range(int(1e6)):
assert not queue.empty(), \
"trying to get() from an empty queue will deadlock"
priority, next_trace = queue.get()
try:
ftr = poutine.trace(poutine.escape(poutine.replay(fn, next_trace),
functools.partial(sample_escape,
next_trace)))
return ftr(*args, **kwargs)
except NonlocalExit as site_container:
site_container.reset_stack()
for tr in poutine.util.enum_extend(ftr.trace.copy(),
site_container.site):
# add a little bit of noise to the priority to break ties...
queue.put((tr.log_prob_sum().item() - torch.rand(1).item() * 1e-2, tr))
raise ValueError("max tries ({}) exceeded".format(str(1e6)))
def get_comment(queue, table, page_no):
while not EXIT_FLAG:
QUEUE_LOCK.acquire()
if not WORK_QUEUE.empty():
try:
sku = queue.get()
QUEUE_LOCK.release()
_spider = jd_spider.Spider()
result = _spider.get_comment(table, sku, page_no)
# if result[0] != -1:
# result = _spider.get_after_comment(table,sku,page_no)
if result[0] != -1:
sql = 'update ' + table + ' set update_comment_time=%s where sku=%s '
data = [datetime.datetime.now(), sku]
database_util.update_sql(sql, data)
except Exception as err:
print('thread_queue get_comment err:' + str(err))
else:
QUEUE_LOCK.release()
time.sleep(1)
def refresh_router(self, queue_name='result_task'):
'''
回调数据打包
'''
try:
messages = queue.get(queue_name, self.batch_size)
logger.debug("refresh_router %s .work process messages begin, count: %d " %(queue_name, len(messages)))
for body in messages:
#logger.debug('---------'+ body +'-------------------')
task = json.loads(body)
#if isinstance(task, str):
#task = json.loads(task)
#logger.debug(task)
logger.debug('router for refresh: %s' % task.get('session_id'))
self.merge_refresh(task)
for key in self.merged_refresh.iterkeys():
self.update_refresh_result(self.merged_refresh.get(key))
logger.info("refresh_router %s .work process messages end, count: %d " %(queue_name, len(messages)))
except Exception,e:
logger.warning('refresh_router %s work error:%s' %(queue_name, traceback.format_exc(e)))
def th_fn(queue, path1, face_client, res_list, count, th_nb):
countframes = 0
while not queue.empty():
ret, frame = queue.get()
print(count)
if not ret:
break
if (countframes % 2) == 0:
resized = cv2.resize(frame, (720, 509))
path2 = "./static/frame" + str(th_nb) + ".jpg"
cv2.imwrite(path2, resized)
try:
compute(path1, path2, face_client, res_list, count, th_nb)
except:
pass
countframes += 1
count -= thread_nb
def baidu_ocr():
# 接收图片
img = request.files.get('file')
queue.put((img.read()))
if img:
time.sleep(random.uniform(1.5, 2.05))
part = queue.get()
@retry(stop_max_attempt_number=5)
def sent_ocr():
try:
ocr_result = client.basicGeneral(part)
return ocr_result
except Exception as e:
raise Exception('BaiDuOCR发生了错误，原因为:{}'.format(e))
result = sent_ocr()
return result
return 400
def worker(queue, user, size, outdir, total):
while True:
try:
photo = queue.get(False)
except Queue.Empty:
break
media_url = photo[1]
urllib3_download(media_url, size, outdir)
with lock:
global downloaded
downloaded += 1
d = {
'media_url': os.path.basename(media_url),
'user': user,
'index': downloaded + 1 if downloaded < total else total,
'total': total,
}
progress = PROGRESS_FORMATTER % d
sys.stdout.write('\r%s' % progress)
sys.stdout.flush()