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Using highlight.io with Python FastAPI

Learn how to set up highlight.io on your Python FastAPI backend API.
1
Setup your frontend Highlight snippet with tracingOrigins.

Make sure that you followed the fullstack mapping guide.

H.init("<YOUR_PROJECT_ID>", { tracingOrigins: ['localhost', 'example.myapp.com/backend'], networkRecording: { enabled: true, recordHeadersAndBody: true, }, });
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2
Install the highlight-io python package.

Download the package from pypi and save it to your requirements. If you use a zip or s3 file upload to publish your function, you will want to make sure highlight-io is part of the build.

poetry add highlight-io[FastAPI] # or with pip pip install highlight-io[FastAPI]
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3
Initialize the Highlight SDK.

Setup the SDK to with the FastAPI integration.

from fastapi import FastAPI, Request import highlight_io from highlight_io.integrations.fastapi import FastAPIMiddleware H = highlight_io.H("YOUR_PROJECT_ID", record_logs=True) app = FastAPI() app.add_middleware(FastAPIMiddleware)
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4
Verify your installation.

Check that your installation is valid by throwing an error. Add the following code to your FastAPI app and start the FastAPI server. Visit http://127.0.0.1:5000/hello in your browser. You should see a DivideByZero error in the Highlight errors page within a few moments.

from fastapi import FastAPI, Request import highlight_io from highlight_io.integrations.fastapi import FastAPIMiddleware H = highlight_io.H("YOUR_PROJECT_ID", record_logs=True) app = FastAPI() app.add_middleware(FastAPIMiddleware) @app.get("/") async def root(request: Request): return {"message": f"This might not be a great idea {5 / 0}"}
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5
Set up logging.

With the Python SDK, your logs are reported automatically from builtin logging methods. See the Python logging setup guide for more details.