Access HTTP Request Metadata#

You can access the metadata of HTTP requests from “Python function” and “Custom prediction (Python)” endpoints by using the dku_http_request_metadata variable within your custom code.

The dku_http_request_metadata variable is an object with the following properties:

headers - an instance of wsgiref.headers.Headers that holds headers used in a request.
path - a relative URL’s path as a string to which the client sent an HTTP request. Example: "/public/api/v1/python-service/py-func/run".

The feature is disabled by default and can be enabled by an infrastructure admin in the following ways:

Use the “Enable dku_http_request_metadata variable” setting in the general settings of the Kubernetes cluster, Azure ML, Amazon SageMaker, Snowflake Snowpark, and Google Vertex AI infrastructures.
On a Static Dataiku API node infrastructure, add the following key-value pair to an API node’s <api-node-root-dir>/config/server.json file
```
"isRequestMetadataEnabled": true
```
The variable is always enabled when running test queries in the API Designer

Python function#

def api_py_function():
    # Your custom logic for handling specific header values
    if not dku_http_request_metadata.headers.get("Authorization"):
        raise Exception("Received no Authorization header")

    # Python function logic
    result = ...

    return result

Custom prediction (classification)#

The dku_http_request_metadata is accessible from the predict method

from  dataiku.apinode.predict.predictor import ClassificationPredictor
import pandas as pd
class MyPredictor(ClassificationPredictor):
    def predict(self, features_df):
        # Your custom logic for handling specific header values
        if not dku_http_request_metadata.headers.get("Authorization"):
            raise Exception("Received no Authorization header")

        # Prediction logic
        predictions = ...
        return (predictions, None)

Custom prediction (regression)#

The dku_http_request_metadata is accessible from the predict method

from  dataiku.apinode.predict.predictor import RegressionPredictor
import pandas as pd
class MyPredictor(RegressionPredictor):
    def predict(self, features_df):
        # Your custom logic for handling specific header values
        if not dku_http_request_metadata.headers.get("Authorization"):
            raise Exception("Received no Authorization header")

        # Prediction logic
        predictions = ...
        return (predictions, None)