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@@ -10,9 +10,8 @@ Python functions -- brought to you by the Google Cloud Functions team.
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The Functions Framework lets you write lightweight functions that run in many
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different environments, including:
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* [Google Cloud Functions](https://cloud.google.com/functions/)
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* [Google Cloud Run Functions](https://cloud.google.com/functions/)
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* Your local development machine
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* [Cloud Run and Cloud Run for Anthos](https://cloud.google.com/run/)
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* [Knative](https://github.com/knative/)-based environments
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The framework allows you to go from:
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## Run your function on serverless platforms
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### Google Cloud Functions
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### Google Cloud Run functions
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This Functions Framework is based on the [Python Runtime on Google Cloud Functions](https://cloud.google.com/functions/docs/concepts/python-runtime).
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On Cloud Functions, using the Functions Framework is not necessary: you don't need to add it to your `requirements.txt` file.
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After you've written your function, you can simply deploy it from your local machine using the `gcloud` command-line tool. [Check out the Cloud Functions quickstart](https://cloud.google.com/functions/docs/quickstart).
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### Cloud Run/Cloud Run on GKE
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Once you've written your function and added the Functions Framework to your `requirements.txt` file, all that's left is to create a container image. [Check out the Cloud Run quickstart](https://cloud.google.com/run/docs/quickstarts/build-and-deploy) for Python to create a container image and deploy it to Cloud Run. You'll write a `Dockerfile` when you build your container. This `Dockerfile` allows you to specify exactly what goes into your container (including custom binaries, a specific operating system, and more). [Here is an example `Dockerfile` that calls Functions Framework.](https://github.com/GoogleCloudPlatform/functions-framework-python/blob/main/examples/cloud_run_http)
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If you want even more control over the environment, you can [deploy your container image to Cloud Run on GKE](https://cloud.google.com/run/docs/quickstarts/prebuilt-deploy-gke). With Cloud Run on GKE, you can run your function on a GKE cluster, which gives you additional control over the environment (including use of GPU-based instances, longer timeouts and more).
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### Container environments based on Knative
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Cloud Run and Cloud Run on GKE both implement the [Knative Serving API](https://www.knative.dev/docs/). The Functions Framework is designed to be compatible with Knative environments. Just build and deploy your container to a Knative environment.
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| `--source` | `FUNCTION_SOURCE` | The path to the file containing your function. Default: `main.py` (in the current working directory) |
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| `--debug` | `DEBUG` | A flag that allows to run functions-framework to run in debug mode, including live reloading. Default: `False` |
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## Enable Google Cloud Function Events
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## Enable Google Cloud Run function Events
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The Functions Framework can unmarshall incoming
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Google Cloud Functions [event](https://cloud.google.com/functions/docs/concepts/events-triggers#events) payloads to `event` and `context` objects.
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Google Cloud Run functions [event](https://cloud.google.com/functions/docs/concepts/events-triggers#events) payloads to `event` and `context` objects.
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These will be passed as arguments to your function when it receives a request.
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Note that your function must use the `event`-style function signature:
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