Mercurial > hg > orthanc
view Resources/Samples/Python/HighPerformanceAutoRouting.py @ 930:27d256e0b458 mac
integration mainline -> mac
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Tue, 24 Jun 2014 16:47:18 +0200 |
parents | 44382c8bcd15 |
children | 8bff277e6886 |
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#!/usr/bin/python # -*- coding: utf-8 -*- # Orthanc - A Lightweight, RESTful DICOM Store # Copyright (C) 2012-2014 Medical Physics Department, CHU of Liege, # Belgium # # This program is free software: you can redistribute it and/or # modify it under the terms of the GNU General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. URL = 'http://localhost:8042' TARGET = 'sample' # # This sample code shows how to setup a simple, high-performance DICOM # auto-routing. All the DICOM instances that arrive inside Orthanc # will be sent to a remote modality. A producer-consumer pattern is # used. The target modality is specified by the TARGET variable above: # It must match an entry in the Orthanc configuration file inside the # "DicomModalities" section. # # NOTE: This sample only works with Orthanc >= 0.5.2. Make sure that # Orthanc was built with "-DCMAKE_BUILD_TYPE=Release" to get the best # performance. # import Queue import sys import time import threading import RestToolbox # # Queue that is shared between the producer and the consumer # threads. It holds the instances that are still to be sent. # queue = Queue.Queue() # # The producer thread. It monitors the arrival of new instances into # Orthanc, and pushes their ID into the shared queue. This code is # based upon the "ChangesLoop.py" sample code. # def Producer(queue): current = 0 while True: r = RestToolbox.DoGet(URL + '/changes', { 'since' : current, 'limit' : 4 # Retrieve at most 4 changes at once }) for change in r['Changes']: # We are only interested interested in the arrival of new instances if change['ChangeType'] == 'NewInstance': queue.put(change['ID']) current = r['Last'] if r['Done']: time.sleep(1) # # The consumer thread. It continuously reads the instances from the # queue, and send them to the remote modality. Each time a packet of # instances is sent, a single DICOM connexion is used, hence improving # the performance. # def Consumer(queue): TIMEOUT = 0.1 while True: instances = [] while True: try: # Block for a while, waiting for the arrival of a new # instance instance = queue.get(True, TIMEOUT) # A new instance has arrived: Record its ID instances.append(instance) queue.task_done() except Queue.Empty: # Timeout: No more data was received break if len(instances) > 0: print 'Sending a packet of %d instances' % len(instances) start = time.time() # Send all the instances with a single DICOM connexion RestToolbox.DoPost('%s/modalities/sample/store' % URL, instances) # Remove all the instances from Orthanc for instance in instances: RestToolbox.DoDelete('%s/instances/%s' % (URL, instance)) # Clear the log of the exported instances (to prevent the # SQLite database from growing indefinitely) RestToolbox.DoDelete('%s/exports' % URL) end = time.time() print 'The packet of %d instances has been sent in %d seconds' % (len(instances), end - start) # # Thread to display the progress # def PrintProgress(queue): while True: print 'Current queue size: %d' % (queue.qsize()) time.sleep(1) # # Start the various threads # progress = threading.Thread(None, PrintProgress, None, (queue, )) progress.daemon = True progress.start() producer = threading.Thread(None, Producer, None, (queue, )) producer.daemon = True producer.start() consumer = threading.Thread(None, Consumer, None, (queue, )) consumer.daemon = True consumer.start() # # Active waiting for Ctrl-C # while True: time.sleep(0.1)