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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,
},
});
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]
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)
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}"}
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.