Automatisieren der AWS-Gerätefarm - AWS Device Farm

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Automatisieren der AWS-Gerätefarm

Der programmatische Zugriff auf Device Farm ist eine leistungsstarke Methode, um die allgemeinen Aufgaben zu automatisieren, die Sie erledigen müssen, wie z. B. das Planen eines Laufs oder das Herunterladen der Artefakte für einen Lauf, eine Suite oder einen Test. Dies ist mithilfe des AWS SDK und der AWS CLI möglich.

DieAWSSDK bietet Zugriff auf alleAWSService, einschließlich Device Farm, Amazon S3 und mehr. Weitere Informationen finden Sie unter

Beispiel: Verwendung desAWSSDK zum Starten einer Gerätefarm, zum Ausführen und Sammeln von Artefakten

Das folgende Beispiel zeigt von Anfang bis Ende, wie Sie das verwenden könnenAWSSDK für die Arbeit mit Device Farm. Dieses Beispiel erledigt Folgendes:

  • Lädt Test- und Anwendungspakete auf Device Farm hoch

  • Startet einen Testlauf und wartet auf seinen Abschluss (oder einen Fehler)

  • Lädt alle von den Testsuiten produzierten Artefakte herunter

Dieses Beispiel hängt für die Interaktion mit HTTP vom requests-Drittanbieterpaket ab.

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")