Mercurial > hg > orthanc-tests
view NewTests/Concurrency/test_concurrency.py @ 601:3e15e950c462
new transfer tests in the concurrency section
author | Alain Mazy <am@osimis.io> |
---|---|
date | Fri, 19 Jan 2024 15:03:47 +0100 |
parents | b9ae7c59fee9 |
children | 6ba2ff41ea52 |
line wrap: on
line source
import unittest import time import os import threading from helpers import OrthancTestCase, Helpers from orthanc_api_client import OrthancApiClient, ChangeType from orthanc_api_client import helpers as OrthancHelpers from orthanc_tools import OrthancTestDbPopulator import pathlib import subprocess import glob here = pathlib.Path(__file__).parent.resolve() def worker_upload_folder(orthanc_root_url: str, folder: str, repeat: int, worker_id: int): o = OrthancApiClient(orthanc_root_url) for i in range(0, repeat): o.upload_folder(folder, ignore_errors=True) def worker_anonymize_study(orthanc_root_url: str, study_id: str, repeat: int, worker_id: int): o = OrthancApiClient(orthanc_root_url) for i in range(0, repeat): o.studies.anonymize(orthanc_id=study_id, delete_original=False) def count_changes(changes, type: ChangeType): return len([c.change_type for c in changes if c.change_type==type]) def worker_upload_delete_study_part(orthanc_root_url: str, folder: str, repeat: int, workers_count: int, worker_id: int): o = OrthancApiClient(orthanc_root_url) all_files = glob.glob(os.path.join(folder, '*.dcm')) for i in range(0, repeat): instances_ids = [] for i in range(0, len(all_files)): if i % workers_count == worker_id: # each thread takes a part instances_ids.extend(o.upload_file(all_files[i])) for instance_id in instances_ids: o.instances.delete(orthanc_id=instance_id, ignore_errors=True) def worker_upload_delete_test_dicoms(orthanc_root_url: str, files_count: int, worker_id: int): o = OrthancApiClient(orthanc_root_url) instances_ids = [] counter = 0 for i in range(0, files_count): counter += 1 dicom_file = OrthancHelpers.generate_test_dicom_file(width=4, height=4, tags = { "PatientID" : f"{worker_id}", "StudyInstanceUID" : f"{worker_id}", "SeriesInstanceUID" : f"{worker_id}.{counter%10}" }) instances_ids.extend(o.upload(dicom_file)) study_id = o.instances.get_parent_study_id(instances_ids[0]) o.studies.delete(orthanc_id=study_id) class TestConcurrency(OrthancTestCase): @classmethod def terminate(cls): if Helpers.is_docker(): subprocess.run(["docker", "rm", "-f", "pg-server"]) else: cls.pg_service_process.terminate() @classmethod def prepare(cls): test_name = "Concurrency" cls._storage_name = "concurrency" print(f'-------------- preparing {test_name} tests') cls.clear_storage(storage_name=cls._storage_name) pg_hostname = "localhost" if Helpers.is_docker(): pg_hostname = "pg-server" cls.create_docker_network("concurrency") config = { "PostgreSQL" : { "EnableStorage": False, "EnableIndex": True, "Host": pg_hostname, "Port": 5432, "Database": "postgres", "Username": "postgres", "Password": "postgres", "IndexConnectionsCount": 10, "MaximumConnectionRetries" : 2000, "ConnectionRetryInterval" : 5, "TransactionMode": "READ COMMITTED", #"TransactionMode": "SERIALIZABLE", "EnableVerboseLogs": True }, "AuthenticationEnabled": False, "OverwriteInstances": True, "JobsEngineThreadsCount" : { "ResourceModification": 8 }, } config_path = cls.generate_configuration( config_name=f"{test_name}", storage_name=cls._storage_name, config=config, plugins=Helpers.plugins ) # launch the docker PG server print('--------------- launching PostgreSQL server ------------------') cls.pg_service_process = subprocess.Popen([ "docker", "run", "--rm", "-p", "5432:5432", "--network", "concurrency", "--name", "pg-server", "--env", "POSTGRES_HOST_AUTH_METHOD=trust", "postgres:15"]) time.sleep(5) if Helpers.break_before_preparation: print(f"++++ It is now time to start your Orthanc under tests with configuration file '{config_path}' +++++") input("Press Enter to continue") else: cls.launch_orthanc_under_tests( config_name=f"{test_name}", storage_name=cls._storage_name, config=config, plugins=Helpers.plugins, docker_network="concurrency" ) cls.o = OrthancApiClient(cls.o._root_url) cls.o.wait_started() cls.o.delete_all_content() def check_is_empty(self): self.assertEqual(0, len(self.o.studies.get_all_ids())) self.assertEqual(0, len(self.o.series.get_all_ids())) self.assertEqual(0, len(self.o.instances.get_all_ids())) stats = self.o.get_json("/statistics") self.assertEqual(0, stats.get("CountPatients")) self.assertEqual(0, stats.get("CountStudies")) self.assertEqual(0, stats.get("CountSeries")) self.assertEqual(0, stats.get("CountInstances")) self.assertEqual(0, int(stats.get("TotalDiskSize"))) # time.sleep(10000) self.assertTrue(self.is_storage_empty(self._storage_name)) # all changes shall have been deleted as well changes, last_change, done = self.o.get_changes(since=0, limit=100000) self.assertTrue(done) self.assertEqual(0, len(changes)) def execute_workers(self, worker_func, worker_args, workers_count): workers = [] for i in range(0, workers_count): t = threading.Thread(target=worker_func, args=worker_args + (i, )) workers.append(t) t.start() for t in workers: t.join() def test_concurrent_uploads_same_study(self): self.o.delete_all_content() self.clear_storage(storage_name=self._storage_name) start_time = time.time() workers_count = 20 repeat_count = 1 # massively reupload the same study multiple times with OverwriteInstances set to true # Make sure the studies, series and instances are created only once self.execute_workers( worker_func=worker_upload_folder, worker_args=(self.o._root_url, here / "../../Database/Knee", repeat_count,), workers_count=workers_count) elapsed = time.time() - start_time print(f"TIMING test_concurrent_uploads_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s") self.assertTrue(self.o.is_alive()) self.assertEqual(1, len(self.o.studies.get_all_ids())) self.assertEqual(2, len(self.o.series.get_all_ids())) self.assertEqual(50, len(self.o.instances.get_all_ids())) stats = self.o.get_json("/statistics") self.assertEqual(1, stats.get("CountPatients")) self.assertEqual(1, stats.get("CountStudies")) self.assertEqual(2, stats.get("CountSeries")) self.assertEqual(50, stats.get("CountInstances")) self.assertEqual(4118738, int(stats.get("TotalDiskSize"))) self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids()) self.check_is_empty() def test_concurrent_anonymize_same_study(self): self.o.delete_all_content() self.clear_storage(storage_name=self._storage_name) self.o.upload_folder(here / "../../Database/Knee") study_id = self.o.studies.get_all_ids()[0] start_time = time.time() workers_count = 4 repeat_count = 10 # massively anonymize the same study. This generates new studies and is a # good way to simulate ingestion of new studies self.execute_workers( worker_func=worker_anonymize_study, worker_args=(self.o._root_url, study_id, repeat_count,), workers_count=workers_count) elapsed = time.time() - start_time print(f"TIMING test_concurrent_anonymize_same_study with {workers_count} workers and {repeat_count}x repeat: {elapsed:.3f} s") self.assertTrue(self.o.is_alive()) self.assertEqual(1 + workers_count * repeat_count, len(self.o.studies.get_all_ids())) self.assertEqual(2 * (1 + workers_count * repeat_count), len(self.o.series.get_all_ids())) self.assertEqual(50 * (1 + workers_count * repeat_count), len(self.o.instances.get_all_ids())) stats = self.o.get_json("/statistics") self.assertEqual(1 + workers_count * repeat_count, stats.get("CountPatients")) self.assertEqual(1 + workers_count * repeat_count, stats.get("CountStudies")) self.assertEqual(2 * (1 + workers_count * repeat_count), stats.get("CountSeries")) self.assertEqual(50 * (1 + workers_count * repeat_count), stats.get("CountInstances")) changes, last_change, done = self.o.get_changes(since=0, limit=100000) self.assertTrue(done) self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_PATIENT)) self.assertEqual(1 + workers_count * repeat_count, count_changes(changes, ChangeType.NEW_STUDY)) self.assertEqual(2 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_SERIES)) self.assertEqual(50 * (1 + workers_count * repeat_count), count_changes(changes, ChangeType.NEW_INSTANCE)) start_time = time.time() self.o.instances.delete(orthanc_ids=self.o.instances.get_all_ids()) elapsed = time.time() - start_time print(f"TIMING test_concurrent_anonymize_same_study deletion took: {elapsed:.3f} s") self.check_is_empty() def test_upload_delete_same_study_from_multiple_threads(self): self.o.delete_all_content() self.clear_storage(storage_name=self._storage_name) start_time = time.time() overall_repeat = 10 for i in range(0, overall_repeat): workers_count = 5 repeat_count = 3 # massively upload and delete the same study. Each worker is writing a part of the instances and deleting them. # We are trying to have multiple workers deleting the last instance of a study at the same time. self.execute_workers( worker_func=worker_upload_delete_study_part, worker_args=(self.o._root_url, here / "../../Database/Knee/T1", repeat_count, workers_count, ), workers_count=workers_count) self.check_is_empty() elapsed = time.time() - start_time 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") def test_upload_multiple_studies_from_multiple_threads(self): self.o.delete_all_content() self.clear_storage(storage_name=self._storage_name) start_time = time.time() overall_repeat = 3 for i in range(0, overall_repeat): files_count = 25 workers_count = 10 # massively upload and delete all studies from the test detabase. Each worker is writing all instances from a folder and then deletes them. # This test is only measuring performances. self.execute_workers( worker_func=worker_upload_delete_test_dicoms, worker_args=(self.o._root_url, files_count, ), workers_count=workers_count) self.check_is_empty() elapsed = time.time() - start_time print(f"TIMING test_upload_multiple_studies_from_multiple_threads with {workers_count} workers and {files_count} files and repeat {overall_repeat}x: {elapsed:.3f} s") # transfers + dicomweb