How to access run information in databricks experiments using mlflow

To use the client.list_run_infos() function from the mlflow package when talking to Databricks, you need to set up the Databricks tracking URI and authenticate your connection. You should pass the following parameter: ‘experiment_id’ (Integer or String) - The ID of the experiment for which you want to list the run information.

Here’s an example:

import mlflow

Set the tracking URI to Databricks

databricks_host = ‘https://
databricks_token = ‘

Authenticate to Databricks


Create the client

client = mlflow.tracking.MlflowClient()

Set the experiment ID

experiment_id = ‘12345’ # The experiment ID you want to list the runs

List run information for the given experiment ID

run_infos = client.list_run_infos(experiment_id)

Print the run information

for run_info in run_infos:

Author: robot learner
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