AWS SDK를 사용하여 Device Farm을 사용하여 모바일 디바이스 패키지 업로드 및 테스트

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다음 코드 예제에서는 Device Farm으로 모바일 장치 패키지를 업로드하고 테스트하는 방법을 보여줍니다.

Python

SDK for Python (Boto3)

참고

GitHub에 더 많은 내용이 있습니다. AWS 코드 예시 리포지토리에서 전체 예시를 찾고 설정 및 실행하는 방법을 배워보세요.

컴파일된 Android 애플리케이션 및 테스트 패키지를 Device Farm에 업로드하고, 테스트를 시작하고, 테스트가 완료될 때까지 기다린 다음 결과를 보고합니다.

import boto3
import os
import requests
import string
import random
import datetime
import time

# Update this dict with your own values before you run the example:
config = {
    # This is our app under test.
    "appFilePath": "app-debug.apk",
    "projectArn": "arn:aws:devicefarm:us-west-2:111222333444:project:581f5703-e040-4ac9-b7ae-0ba007bfb8e6",
    # Since we care about the most popular devices, we'll use a curated pool.
    "testSpecArn": "arn:aws:devicefarm:us-west-2::upload:20fcf771-eae3-4137-aa76-92e17fb3131b",
    "poolArn": "arn:aws:devicefarm:us-west-2::devicepool:4a869d91-6f17-491f-9a95-0a601aee2406",
    "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 '{unique}'. All uploads will be prefixed "
    f"with this."
)


def upload_df_file(filename, type_, mime="application/octet-stream"):
    upload_response = client.create_upload(
        projectArn=config["projectArn"],
        name=unique + "_" + os.path.basename(filename),
        type=type_,
        contentType=mime,
    )
    upload_arn = upload_response["upload"]["arn"]
    # Extract the URL of the upload and use Requests to upload it.
    upload_url = upload_response["upload"]["url"]
    with open(filename, "rb") as file_stream:
        print(
            f"Uploading {filename} to Device Farm as "
            f"{upload_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(f"Couldn't upload. Requests says: {put_req.reason}")
    started = datetime.datetime.now()
    while True:
        print(
            f"Upload of {filename} in state {upload_response['upload']['status']} "
            f"after " + str(datetime.datetime.now() - started)
        )
        if upload_response["upload"]["status"] == "FAILED":
            raise Exception(
                f"The upload failed processing. Device Farm says the reason is: \n"
                f"{+upload_response['upload']['message']}"
            )
        if upload_response["upload"]["status"] == "SUCCEEDED":
            break
        time.sleep(5)
        upload_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)

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} ")

state = "UNKNOWN"
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 "
                f"time {datetime.datetime.now() - start_time}"
            )
            time.sleep(10)
except:
    client.stop_run(arn=run_arn)
    exit(1)

print(f"Tests finished in state {state} after {datetime.datetime.now() - start_time}")
# Pull all the logs.
jobs_response = client.list_jobs(arn=run_arn)
# Save the output somewhere, using the unique value.
save_path = os.path.join(os.getcwd(), "results", unique)
os.mkdir(save_path)
# Save the last run information.
for job in jobs_response["jobs"]:
    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:
                    # 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(f"Downloading {artifact_save_path}")
                    with open(artifact_save_path, "wb") as fn:
                        with requests.get(
                            artifact["url"], allow_redirects=True
                        ) as request:
                            fn.write(request.content)
print("Finished")

• API 세부 정보는 AWS SDK for Python (Boto3) API 참조의 다음 주제를 참조하십시오.

  • CreateUpload

  • GetRun

  • GetUpload

  • ListArtifacts

  • ListJobs

  • ListSuites

  • ListTests

  • ScheduleRun

  • StopRun