이 튜토리얼에서는 Python 런타임을 사용하여 Cloud Run 함수를 작성하는 과정을 설명합니다. Cloud Run Functions에는 다음과 같은 두 가지 유형이 있습니다.
표준 HTTP 요청에서 호출하는 HTTP 함수
Pub/Sub 주제의 메시지 또는 Cloud Storage 버킷의 변경사항과 같이 클라우드 인프라의 이벤트를 처리하는 데 사용되는 이벤트 기반 함수
이 샘플은 간단한 HTTP 함수를 만드는 방법을 보여줍니다.
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importfunctions_frameworkfrommarkupsafeimportescape@functions_framework.httpdefhello_http(request):"""HTTP Cloud Function. Args: request (flask.Request): The request object. <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data> Returns: The response text, or any set of values that can be turned into a Response object using `make_response` <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>. """request_json=request.get_json(silent=True)request_args=request.argsifrequest_jsonand"name"inrequest_json:name=request_json["name"]elifrequest_argsand"name"inrequest_args:name=request_args["name"]else:name="World"returnf"Hello {escape(name)}!"
이 함수 예시는 HTTP 요청에 제공된 이름을 사용하여 인사말을 반환합니다. 제공된 이름이 없으면 'Hello World!'를 반환합니다.
종속 항목 지정
Python의 종속 항목은 pip로 관리되며 requirements.txt라는 메타데이터 파일로 표현됩니다.
이 파일은 함수 코드가 포함된 main.py 파일과 동일한 디렉터리에 있어야 합니다.
이 특정 샘플을 실행하기 위해 requirements.txt를 만들 필요는 없지만 자체 종속 항목을 추가하려 한다고 가정해 보겠습니다. 방법은 다음과 같습니다.
helloworld 디렉터리에 requirements.txt 파일을 만듭니다.
requirements.txt 파일에 함수의 종속 항목을 추가합니다. 예를 들면 다음과 같습니다.
# An example requirements file, add your dependencies belowsampleproject==2.0.0
함수 배포하기
HTTP 트리거를 사용하여 함수를 배포하려면 helloworld 디렉터리에서 다음 명령어를 실행합니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-10(UTC)"],[[["\u003cp\u003eThis guide provides instructions on creating and deploying an HTTP Cloud Run function using Python (1st gen).\u003c/p\u003e\n"],["\u003cp\u003eThe process involves setting up your development environment with the gcloud CLI and preparing a \u003ccode\u003emain.py\u003c/code\u003e file that contains the Python code for your function.\u003c/p\u003e\n"],["\u003cp\u003eDependencies for the function are managed using a \u003ccode\u003erequirements.txt\u003c/code\u003e file, which lists the necessary external libraries.\u003c/p\u003e\n"],["\u003cp\u003eDeployment is executed via the gcloud CLI with a command that sets up the function as an HTTP trigger, and testing is done by accessing a URL provided upon deployment.\u003c/p\u003e\n"],["\u003cp\u003eFunction logs can be viewed using both the gcloud CLI and the Google Cloud console's Logging dashboard.\u003c/p\u003e\n"]]],[],null,["Create and deploy an HTTP Cloud Run function by using Python (1st gen)\n\nThis guide takes you through the process of writing a Cloud Run function\nusing the Python runtime. There are two types of Cloud Run functions:\n\n- An HTTP function, which you invoke from standard HTTP requests.\n- An event-driven function, which you use to handle events from your Cloud infrastructure, such as messages on a Pub/Sub topic, or changes in a Cloud Storage bucket.\n\nThe sample shows how to create a simple HTTP function.\n| **Learn more** : For more details, read about [HTTP functions](/functions/1stgendocs/writing/write-http-functions) and [event-driven functions](/functions/1stgendocs/writing/write-event-driven-functions).\n\nBefore you begin\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Cloud Functions and Cloud Build APIs.\n\n\n [Enable the APIs](https://console.cloud.google.com/flows/enableapi?apiid=cloudfunctions,cloudbuild.googleapis.com&redirect=https://cloud.google.com/functions/quickstart)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Cloud Functions and Cloud Build APIs.\n\n\n [Enable the APIs](https://console.cloud.google.com/flows/enableapi?apiid=cloudfunctions,cloudbuild.googleapis.com&redirect=https://cloud.google.com/functions/quickstart)\n\n1. [Install and initialize the gcloud CLI](/sdk/docs).\n2. Update and install `gcloud` components: \n\n ```bash\n gcloud components update\n ```\n| **Note** : Need a command prompt? You can use the [Google Cloud\n| Shell](https://console.cloud.google.com/?cloudshell=true). The Google Cloud Shell is a command line environment that already includes the Google Cloud CLI, so you don't need to install it. The Google Cloud CLI also comes preinstalled on Google Compute Engine Virtual Machines.\n3. Prepare your development environment.\n [Go to the Python setup guide](/python/docs/setup)\n\nCreate a function\n\n1. Create a directory on your local system for the function code:\n\n Linux or Mac OS X \n\n mkdir ~/helloworld\n cd ~/helloworld\n\n Windows \n\n mkdir %HOMEPATH%\\helloworld\n cd %HOMEPATH%\\helloworld\n\n2. Create a `main.py` file in the `helloworld` directory with the\n following contents:\n\n\n import functions_framework\n\n\n from markupsafe import escape\n\n @functions_framework.http\n def hello_http(request):\n \"\"\"HTTP Cloud Function.\n Args:\n request (flask.Request): The request o\u003cbject.\n https://flask.palletsprojects.com/en/1.1.x/api/#incomi\u003eng-request-data\n Returns:\n The response text, or any set of values that can be turned into a\n Response object using `make_res\u003cponse`\n https://flask.palletsprojects.com/en/1.1.x/api/#flas\u003ek.make_response.\n \"\"\"\n request_json = request.get_json(silent=True)\n request_args = request.args\n\n if request_json and \"name\" in request_json:\n name = request_json[\"name\"]\n elif request_args and \"name\" in request_args:\n name = request_args[\"name\"]\n else:\n name = \"World\"\n return f\"Hello {escape(name)}!\"\n\n This example function takes a name supplied in the HTTP request and returns\n a greeting, or \"Hello World!\" when no name is supplied.\n | **Note:** Cloud Run functions looks for deployable functions in `main.py` by default. Use the [`--source`](/sdk/gcloud/reference/functions/deploy#--source) flag when [deploying your function via `gcloud`](#deploying_the_function) to specify a different directory containing a `main.py` file.\n\nSpecify dependencies\n\nDependencies in Python are managed with [pip](https://pip.pypa.io/en/stable/)\nand expressed in a metadata file called\n[`requirements.txt`](https://pip.pypa.io/en/stable/user_guide/#requirements-files).\nThis file must be in the same directory as the `main.py` file that contains\nyour function code.\n\nYou don't need to create a `requirements.txt` to run this particular sample,\nbut suppose you wanted to add your own dependencies. Here's how you would do it:\n\n1. Create a `requirements.txt` file in the `helloworld` directory.\n\n2. Add the function's dependency, to your `requirements.txt` file, for example:\n\n # An example requirements file, add your dependencies below\n sampleproject==2.0.0\n\n| **Learn more** : For more details, read about [specifying dependencies](/functions/1stgendocs/writing/specifying-dependencies-python).\n\nDeploy the function\n\nTo deploy the function with an HTTP trigger, run the following\ncommand in the `helloworld` directory: \n\n```sh\ngcloud functions deploy hello_http --no-gen2 --runtime python312 --trigger-http --allow-unauthenticated\n```\n\nThe `--allow-unauthenticated` flag lets you reach the function\n[without authentication](/functions/1stgendocs/securing/managing-access-iam#allowing_unauthenticated_http_function_invocation).\nTo require\n[authentication](/functions/1stgendocs/securing/authenticating#developers), omit the\nflag.\n| **Learn more** : For more details, read about [deploying Cloud Run functions](/functions/1stgendocs/deploy#basics).\n\nTest the function\n\n1. When the function finishes deploying, take note of the `httpsTrigger.url`\n property or find it using the following command:\n\n gcloud functions describe hello_http\n\n It should look like this: \n\n ```\n https://GCP_REGION-PROJECT_ID.cloudfunctions.net/hello_http\n ```\n2. Visit this URL in your browser. You should see a \"Hello World!\" message.\n\n Try passing a name in the HTTP request, for example by using the following\n URL: \n\n ```\n https://GCP_REGION-PROJECT_ID.cloudfunctions.net/hello_http?name=NAME\n ```\n\n You should see the message \"Hello \u003cvar translate=\"no\"\u003eNAME\u003c/var\u003e!\"\n\nView logs\n\nLogs for Cloud Run functions are viewable using the Google Cloud CLI, and in the\nCloud Logging UI.\n\nUse the command-line tool\n\nTo view logs for your function with the gcloud CLI, use the\n[`logs read`](/sdk/gcloud/reference/functions/logs/read) command, followed by\nthe name of the function: \n\n```bash\ngcloud functions logs read hello_http\n```\n\nThe output should resemble the following: \n\n```bash\nLEVEL NAME EXECUTION_ID TIME_UTC LOG\nD hello_http pdb5ys2t022n 2019-09-18 23:29:09.791 Function execution started\nD hello_http pdb5ys2t022n 2019-09-18 23:29:09.798 Function execution took 7 ms, finished with status code: 200\n```\n| **Note:** There is typically a slight delay between when log entries are created and when they show up in Cloud Logging.\n\nUse the Logging dashboard\n\nYou can also view logs for Cloud Run functions from the\n[Google Cloud console](https://console.cloud.google.com/project/_/logs?service=cloudfunctions.googleapis.com).\n| **Learn more** : For more details, read about [writing, viewing, and responding to logs](/functions/1stgendocs/monitoring/logging)."]]
