To get started, the following prerequisites are required:

\n
• Azure Functions runtime version 4.34.1, or a later version.
\n
• Python version 3.8, or a later supported version.
\n
• Python v2 programming model
\n

Then, enable HTTP streaming in your Azure Function app. HTTP streams are disabled by default. You need to enable this feature in your application settings and also update your code to use the FastAPI package. Note that when enabling HTTP streams, the function app will default to using HTTP streaming, and the original HTTP functionality will not work.

\n
1. \n

   Add the azurefunctions-extensions-http-fastapi extension package to the requirements.txt file in the project.

   \n
\n
2. \n

   Add the following code to the function_app.py file in the project, which imports the FastAPI extension:

   \n

   from azurefunctions.extensions.http.fastapi import Request, StreamingResponse

\n
3. \n

   When deploying, add the following application settings: \"PYTHON_ENABLE_INIT_INDEXING\": \"1\". If you are deploying to Linux Consumption, also add \"PYTHON_ISOLATE_WORKER_DEPENDENCIES\": \"1\".

   \n

   When running locally, you also need to add these same settings to the local.settings.json project file.

   \n
\n

Following are a few example code snippets on using HTTP streams with Azure Functions in Python.

This example is an HTTP triggered function that streams HTTP response data. You might use these capabilities to support scenarios like sending event data through a pipeline for real time visualization or detecting anomalies in large sets of data and providing instant notifications.

import time\nimport azure.functions as func\nfrom azurefunctions.extensions.http.fastapi import Request, StreamingResponse\n\napp = func.FunctionApp(http_auth_level=func.AuthLevel.ANONYMOUS)\n\n\ndef generate_count():\n    \"\"\"Generate a stream of chronological numbers.\"\"\"\n    count = 0\n    while True:\n        yield f\"counting, {count}\\n\\n\"\n        count += 1\n\n@app.route(route=\"stream\", methods=[func.HttpMethod.GET])\nasync def stream_count(req: Request) -> StreamingResponse:\n    \"\"\"Endpoint to stream of chronological numbers.\"\"\"\n    return StreamingResponse(generate_count(), media_type=\"text/event-stream\")

This example is an HTTP triggered function that receives and processes streaming data from a client in real time. It demonstrates streaming upload capabilities that can be helpful for scenarios like processing continuous data streams and handling event data from IoT devices.

import azure.functions as func\nfrom azurefunctions.extensions.http.fastapi import JSONResponse, Request\n\napp = func.FunctionApp(http_auth_level=func.AuthLevel.ANONYMOUS)\n\n\n@app.route(route=\"streaming_upload\", methods=[func.HttpMethod.POST])\nasync def streaming_upload(req: Request) -> JSONResponse:\n    \"\"\"Handle streaming upload requests.\"\"\"\n    # Process each chunk of data as it arrives\n    async for chunk in req.stream():\n        process_data_chunk(chunk)\n\n    # Once all data is received, return a JSON response indicating successful processing\n    return JSONResponse({\"status\": \"Data uploaded and processed successfully\"})\n\n\ndef process_data_chunk(chunk: bytes):\n    \"\"\"Process each data chunk.\"\"\"\n    # Add custom processing logic here\n    pass

Note, you must use an HTTP client library to make streaming calls to a function's FastAPI endpoints. The client tool or browser you're using might not natively support streaming or could only return the first chunk of data. You can use a client script like this to send streaming data to an HTTP endpoint.

To get started, the following prerequisites are required:

\n
• Azure Functions runtime version 4.34.1, or a later version.
\n
• Python version 3.8, or a later supported version.
\n
• Python v2 programming model
\n

Then, enable HTTP streaming in your Azure Function app. HTTP streams are disabled by default. You need to enable this feature in your application settings and also update your code to use the FastAPI package. Note that when enabling HTTP streams, the function app will default to using HTTP streaming, and the original HTTP functionality will not work.

\n
1. \n

   Add the azurefunctions-extensions-http-fastapi extension package to the requirements.txt file in the project.

   \n
\n
2. \n

   Add the following code to the function_app.py file in the project, which imports the FastAPI extension:

   \nfrom azurefunctions.extensions.http.fastapi import Request, StreamingResponse
\n
3. \n

   When deploying, add the following application settings: \"PYTHON_ENABLE_INIT_INDEXING\": \"1\". If you are deploying to Linux Consumption, also add \"PYTHON_ISOLATE_WORKER_DEPENDENCIES\": \"1\".

   \n

   When running locally, you also need to add these same settings to the local.settings.json project file.

   \n
\n

Following are a few example code snippets on using HTTP streams with Azure Functions in Python.

This example is an HTTP triggered function that streams HTTP response data. You might use these capabilities to support scenarios like sending event data through a pipeline for real time visualization or detecting anomalies in large sets of data and providing instant notifications.

This example is an HTTP triggered function that receives and processes streaming data from a client in real time. It demonstrates streaming upload capabilities that can be helpful for scenarios like processing continuous data streams and handling event data from IoT devices.

Note, you must use an HTTP client library to make streaming calls to a function's FastAPI endpoints. The client tool or browser you're using might not natively support streaming or could only return the first chunk of data. You can use a client script like this to send streaming data to an HTTP endpoint.