기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.
AWS Device Farm 자동화
Device Farm에 프로그래밍 방식 액세스는 실행 예약 또는 실행, 제품군 및 테스트에 대한 아티팩트 다운로드와 같이 수행해야 하는 일반적인 작업을 자동화하는 강력한 방법입니다. AWS SDK 및 AWS CLI는 수행할 수 있는 방법을 제공합니다.
AWS SDK는 Device Farm, Amazon S3 등을 비롯한 모든 AWS 서비스에 액세스할 수 있게 합니다. 자세한 내용을 알아보려면 다음 단원을 참조하세요.
예제: AWS SDK를 사용하여 Device Farm 실행 시작 및 아티팩트 수집
다음 예제에서는 AWS SDK를 사용하여 Device Farm과 작업하는 방법을 처음부터 끝까지 설명합니다. 이 예제에서는 다음을 수행합니다.
테스트 및 애플리케이션 패키지를 Device Farm에 업로드합니다.
테스트 실행을 시작하고 완료(또는 실패)될 때까지 기다립니다.
테스트 스위트에서 생성한 모든 아티팩트를 다운로드합니다.
이 예제는 타사 requests
패키지에 따라 HTTP와 상호 작용합니다.
import boto3 import os import requests import string import random import time import datetime import time import json # The following script runs a test through Device Farm # # Things you have to change: config = { # This is our app under test. "appFilePath":"app-debug.apk", "projectArn": "arn:aws:devicefarm:us-west-2:111122223333:project:1b99bcff-1111-2222-ab2f-8c3c733c55ed", # Since we care about the most popular devices, we'll use a curated pool. "testSpecArn":"arn:aws:devicefarm:us-west-2::upload:101e31e8-12ac-11e9-ab14-d663bd873e83", "poolArn":"arn:aws:devicefarm:us-west-2::devicepool:082d10e5-d7d7-48a5-ba5c-b33d66efa1f5", "namePrefix":"MyAppTest", # This is our test package. This tutorial won't go into how to make these. "testPackage":"tests.zip" } client = boto3.client('devicefarm') unique = config['namePrefix']+"-"+(datetime.date.today().isoformat())+(''.join(random.sample(string.ascii_letters,8))) print(f"The unique identifier for this run is going to be {unique} -- all uploads will be prefixed with this.") def upload_df_file(filename, type_, mime='application/octet-stream'): response = client.create_upload(projectArn=config['projectArn'], name = (unique)+"_"+os.path.basename(filename), type=type_, contentType=mime ) # Get the upload ARN, which we'll return later. upload_arn = response['upload']['arn'] # We're going to extract the URL of the upload and use Requests to upload it upload_url = response['upload']['url'] with open(filename, 'rb') as file_stream: print(f"Uploading {filename} to Device Farm as {response['upload']['name']}... ",end='') put_req = requests.put(upload_url, data=file_stream, headers={"content-type":mime}) print(' done') if not put_req.ok: raise Exception("Couldn't upload, requests said we're not ok. Requests says: "+put_req.reason) started = datetime.datetime.now() while True: print(f"Upload of {filename} in state {response['upload']['status']} after "+str(datetime.datetime.now() - started)) if response['upload']['status'] == 'FAILED': raise Exception("The upload failed processing. DeviceFarm says reason is: \n"+(response['upload']['message'] if 'message' in response['upload'] else response['upload']['metadata'])) if response['upload']['status'] == 'SUCCEEDED': break time.sleep(5) response = client.get_upload(arn=upload_arn) print("") return upload_arn our_upload_arn = upload_df_file(config['appFilePath'], "ANDROID_APP") our_test_package_arn = upload_df_file(config['testPackage'], 'APPIUM_PYTHON_TEST_PACKAGE') print(our_upload_arn, our_test_package_arn) # Now that we have those out of the way, we can start the test run... response = client.schedule_run( projectArn = config["projectArn"], appArn = our_upload_arn, devicePoolArn = config["poolArn"], name=unique, test = { "type":"APPIUM_PYTHON", "testSpecArn": config["testSpecArn"], "testPackageArn": our_test_package_arn } ) run_arn = response['run']['arn'] start_time = datetime.datetime.now() print(f"Run {unique} is scheduled as arn {run_arn} ") try: while True: response = client.get_run(arn=run_arn) state = response['run']['status'] if state == 'COMPLETED' or state == 'ERRORED': break else: print(f" Run {unique} in state {state}, total time "+str(datetime.datetime.now()-start_time)) time.sleep(10) except: # If something goes wrong in this process, we stop the run and exit. client.stop_run(arn=run_arn) exit(1) print(f"Tests finished in state {state} after "+str(datetime.datetime.now() - start_time)) # now, we pull all the logs. jobs_response = client.list_jobs(arn=run_arn) # Save the output somewhere. We're using the unique value, but you could use something else save_path = os.path.join(os.getcwd(), unique) os.mkdir(save_path) # Save the last run information for job in jobs_response['jobs'] : # Make a directory for our information job_name = job['name'] os.makedirs(os.path.join(save_path, job_name), exist_ok=True) # Get each suite within the job suites = client.list_suites(arn=job['arn'])['suites'] for suite in suites: for test in client.list_tests(arn=suite['arn'])['tests']: # Get the artifacts for artifact_type in ['FILE','SCREENSHOT','LOG']: artifacts = client.list_artifacts( type=artifact_type, arn = test['arn'] )['artifacts'] for artifact in artifacts: # We replace : because it has a special meaning in Windows & macos path_to = os.path.join(save_path, job_name, suite['name'], test['name'].replace(':','_') ) os.makedirs(path_to, exist_ok=True) filename = artifact['type']+"_"+artifact['name']+"."+artifact['extension'] artifact_save_path = os.path.join(path_to, filename) print("Downloading "+artifact_save_path) with open(artifact_save_path, 'wb') as fn, requests.get(artifact['url'],allow_redirects=True) as request: fn.write(request.content) #/for artifact in artifacts #/for artifact type in [] #/ for test in ()[] #/ for suite in suites #/ for job in _[] # done print("Finished")