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1 import unittest
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2 import time
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3 import os
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4 import threading
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5 from helpers import OrthancTestCase, Helpers
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6
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597
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7 from orthanc_api_client import OrthancApiClient, generate_test_dicom_file, ChangeType
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592
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8 from orthanc_tools import OrthancTestDbPopulator
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9
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10 import pathlib
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11 import subprocess
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12 import glob
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13 here = pathlib.Path(__file__).parent.resolve()
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14
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15
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16 def worker_upload_folder(orthanc_root_url: str, folder: str, repeat: int, worker_id: int):
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17 o = OrthancApiClient(orthanc_root_url)
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18 for i in range(0, repeat):
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19 o.upload_folder(folder, ignore_errors=True)
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20
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21 def worker_anonymize_study(orthanc_root_url: str, study_id: str, repeat: int, worker_id: int):
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22 o = OrthancApiClient(orthanc_root_url)
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23
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24 for i in range(0, repeat):
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25 o.studies.anonymize(orthanc_id=study_id, delete_original=False)
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26
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597
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27 def count_changes(changes, type: ChangeType):
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28 return len([c.change_type for c in changes if c.change_type==type])
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29
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30 def worker_upload_delete_study_part(orthanc_root_url: str, folder: str, repeat: int, workers_count: int, worker_id: int):
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31 o = OrthancApiClient(orthanc_root_url)
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32
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33 all_files = glob.glob(os.path.join(folder, '*.dcm'))
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34
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35 for i in range(0, repeat):
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36 instances_ids = []
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37
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38 for i in range(0, len(all_files)):
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39 if i % workers_count == worker_id:
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40 instances_ids.extend(o.upload_file(all_files[i]))
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41
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42 for instance_id in instances_ids:
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43 o.instances.delete(orthanc_id=instance_id, ignore_errors=True)
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44
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45
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46 class TestConcurrency(OrthancTestCase):
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47
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48 @classmethod
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49 def terminate(cls):
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50
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51 if Helpers.is_docker():
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52 subprocess.run(["docker", "rm", "-f", "pg-server"])
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53 else:
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54 cls.pg_service_process.terminate()
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55
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56
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57 @classmethod
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58 def prepare(cls):
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59 test_name = "Concurrency"
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60 cls._storage_name = "concurrency"
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61
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62 print(f'-------------- preparing {test_name} tests')
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63
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64 cls.clear_storage(storage_name=cls._storage_name)
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65
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66 pg_hostname = "localhost"
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67 if Helpers.is_docker():
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68 pg_hostname = "pg-server"
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69 cls.create_docker_network("concurrency")
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70
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71 config = {
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72 "PostgreSQL" : {
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73 "EnableStorage": False,
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74 "EnableIndex": True,
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75 "Host": pg_hostname,
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76 "Port": 5432,
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77 "Database": "postgres",
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78 "Username": "postgres",
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79 "Password": "postgres",
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80 "IndexConnectionsCount": 10,
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81 "MaximumConnectionRetries" : 2000,
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82 "ConnectionRetryInterval" : 5,
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83 "TransactionMode": "READ COMMITTED",
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84 #"TransactionMode": "SERIALIZABLE",
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85 "EnableVerboseLogs": True
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86 },
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87 "AuthenticationEnabled": False,
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88 "OverwriteInstances": True,
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89 "JobsEngineThreadsCount" : {
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90 "ResourceModification": 8
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91 },
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92 }
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93
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94 config_path = cls.generate_configuration(
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95 config_name=f"{test_name}",
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96 storage_name=cls._storage_name,
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97 config=config,
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98 plugins=Helpers.plugins
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99 )
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100
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101 # launch the docker PG server
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102 print('--------------- launching PostgreSQL server ------------------')
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103
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104 cls.pg_service_process = subprocess.Popen([
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105 "docker", "run", "--rm",
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106 "-p", "5432:5432",
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107 "--network", "concurrency",
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108 "--name", "pg-server",
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109 "--env", "POSTGRES_HOST_AUTH_METHOD=trust",
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110 "postgres:15"])
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111 time.sleep(5)
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112
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113 if Helpers.break_before_preparation:
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114 print(f"++++ It is now time to start your Orthanc under tests with configuration file '{config_path}' +++++")
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115 input("Press Enter to continue")
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116 else:
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117 cls.launch_orthanc_under_tests(
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118 config_name=f"{test_name}",
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119 storage_name=cls._storage_name,
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120 config=config,
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121 plugins=Helpers.plugins,
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122 docker_network="concurrency"
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123 )
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124
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125 cls.o = OrthancApiClient(cls.o._root_url)
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126 cls.o.wait_started()
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127 cls.o.delete_all_content()
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128
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129 def check_is_empty(self):
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130 self.assertEqual(0, len(self.o.studies.get_all_ids()))
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131 self.assertEqual(0, len(self.o.series.get_all_ids()))
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132 self.assertEqual(0, len(self.o.instances.get_all_ids()))
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133
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134 stats = self.o.get_json("/statistics")
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135 self.assertEqual(0, stats.get("CountPatients"))
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136 self.assertEqual(0, stats.get("CountStudies"))
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137 self.assertEqual(0, stats.get("CountSeries"))
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138 self.assertEqual(0, stats.get("CountInstances"))
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139 self.assertEqual(0, int(stats.get("TotalDiskSize")))
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140 # time.sleep(10000)
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141 self.assertTrue(self.is_storage_empty(self._storage_name))
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142
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143 # all changes shall have been deleted as well
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144 changes, last_change, done = self.o.get_changes(since=0, limit=100000)
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145 self.assertTrue(done)
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146 self.assertEqual(0, len(changes))
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147
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148
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149 def execute_workers(self, worker_func, worker_args, workers_count):
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150 workers = []
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151 for i in range(0, workers_count):
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152 t = threading.Thread(target=worker_func, args=worker_args + (i, ))
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153 workers.append(t)
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154 t.start()
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155
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156 for t in workers:
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157 t.join()
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158
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159 def test_concurrent_uploads_same_study(self):
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160 self.o.delete_all_content()
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161 self.clear_storage(storage_name=self._storage_name)
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162
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163 start_time = time.time()
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164 workers_count = 20
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165 repeat_count = 1
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166
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167 # massively reupload the same study multiple times with OverwriteInstances set to true
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168 # Make sure the studies, series and instances are created only once
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169 self.execute_workers(
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170 worker_func=worker_upload_folder,
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171 worker_args=(self.o._root_url, here / "../../Database/Knee", repeat_count,),
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172 workers_count=workers_count)
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173
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174 elapsed = time.time() - start_time
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593
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175 print(f"TIMING test_concurrent_uploads_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s")
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176
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177 self.assertTrue(self.o.is_alive())
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178
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179 self.assertEqual(1, len(self.o.studies.get_all_ids()))
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180 self.assertEqual(2, len(self.o.series.get_all_ids()))
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181 self.assertEqual(50, len(self.o.instances.get_all_ids()))
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182
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183 stats = self.o.get_json("/statistics")
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184 self.assertEqual(1, stats.get("CountPatients"))
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185 self.assertEqual(1, stats.get("CountStudies"))
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186 self.assertEqual(2, stats.get("CountSeries"))
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187 self.assertEqual(50, stats.get("CountInstances"))
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188 self.assertEqual(4118738, int(stats.get("TotalDiskSize")))
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189
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190 self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids())
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191
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192 self.check_is_empty()
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193
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194 def test_concurrent_anonymize_same_study(self):
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195 self.o.delete_all_content()
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196 self.clear_storage(storage_name=self._storage_name)
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197
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198 self.o.upload_folder(here / "../../Database/Knee")
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199 study_id = self.o.studies.get_all_ids()[0]
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200
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201 start_time = time.time()
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202 workers_count = 4
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203 repeat_count = 10
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204
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205 # massively anonymize the same study. This generates new studies and is a
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206 # good way to simulate ingestion of new studies
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207 self.execute_workers(
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208 worker_func=worker_anonymize_study,
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209 worker_args=(self.o._root_url, study_id, repeat_count,),
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210 workers_count=workers_count)
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211
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212 elapsed = time.time() - start_time
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213 print(f"TIMING test_concurrent_anonymize_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s")
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214
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215 self.assertTrue(self.o.is_alive())
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216
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217 self.assertEqual(1 + workers_count * repeat_count, len(self.o.studies.get_all_ids()))
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218 self.assertEqual(2 * (1 + workers_count * repeat_count), len(self.o.series.get_all_ids()))
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219 self.assertEqual(50 * (1 + workers_count * repeat_count), len(self.o.instances.get_all_ids()))
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220
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221 stats = self.o.get_json("/statistics")
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222 self.assertEqual(1 + workers_count * repeat_count, stats.get("CountPatients"))
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223 self.assertEqual(1 + workers_count * repeat_count, stats.get("CountStudies"))
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224 self.assertEqual(2 * (1 + workers_count * repeat_count), stats.get("CountSeries"))
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225 self.assertEqual(50 * (1 + workers_count * repeat_count), stats.get("CountInstances"))
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226 changes, last_change, done = self.o.get_changes(since=0, limit=100000)
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227 self.assertTrue(done)
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228
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229 self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_PATIENT))
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230 self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_STUDY))
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231 self.assertEqual(2 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_SERIES))
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232 self.assertEqual(50 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_INSTANCE))
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233
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234 start_time = time.time()
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235
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236 self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids())
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237
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238 elapsed = time.time() - start_time
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239 print(f"TIMING test_concurrent_anonymize_same_study deletion took: {elapsed:.3f} s")
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240
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241 self.check_is_empty()
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242
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243
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244 def test_upload_delete_same_study_from_multiple_threads(self):
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245 self.o.delete_all_content()
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246 self.clear_storage(storage_name=self._storage_name)
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247
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248 start_time = time.time()
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249 overall_repeat = 10
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250
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251 for i in range(0, 10):
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252 workers_count = 5
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253 repeat_count = 3
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594
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254
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255 # massively upload and delete the same study. Each worker is writing a part of the instances and deleting them.
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256 # We are trying to have multiple workers deleting the last instance of a study at the same time.
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257 self.execute_workers(
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258 worker_func=worker_upload_delete_study_part,
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259 worker_args=(self.o._root_url, here / "../../Database/Knee/T1", repeat_count, workers_count, ),
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260 workers_count=workers_count)
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261
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262 self.check_is_empty()
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263
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264 elapsed = time.time() - start_time
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265 print(f"TIMING test_upload_delete_same_study_from_multiple_threads with {workers_count} workers and {repeat_count}x repeat ({overall_repeat}x): {elapsed:.3f} s")
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266
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267
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268 # transfers + dicomweb |
