Initialize your Kedro project

This section assume that you have installed kedro-mlflow in your virtual environment.

Create a kedro project

This plugin must be used in an existing kedro project. If you do not have a kedro project yet, you can create it with kedro new command. See the kedro docs for a tutorial.

If you do not have a real-world project, you can use a kedro example and follow the “Getting started” example to make a demo of this plugin out of the box.

Activate kedro-mlflow in your kedro project

In order to use the kedro-mlflow plugin, you need to setup its configuration and declare its hooks. Those 2 actions are detailled in the following paragraphs.

Setting up the kedro-mlflow configuration file

kedro-mlflow is configured through an mlflow.yml file. The recommended way to initialize the mlflow.yml is by using the kedro-mlflow CLI. It is mandatory for the plugin to work.

Set the working directory at the root of your kedro project (i.e. the folder with the .kedro.yml file)

cd path/to/your/project

Run the init command :

kedro mlflow init

you should see the following message:

'conf/local/mlflow.yml' successfully updated.

Note: you can create the configuration file in another kedro environment with the --env argument:

kedro mlflow init --env=<other-environment>

Declaring kedro-mlflow hooks

kedro_mlflow hooks implementations must be registered with Kedro. There are three ways of registering hooks.

Note that you must register the two hooks provided by kedro-mlflow (MlflowPipelineHook and MlflowNodeHook) for the plugin to work.

Declaring hooks through auto-discovery (for kedro>=0.16.4) [Default behaviour]

If you use kedro>=0.16.4, kedro-mlflow hooks are auto-registered automatically by default without any action from your side. You can disable this behaviour in your .kedro.yml or your pyproject.toml file.

Declaring hooks through code, in ProjectContext (for kedro>=0.16.0, <=0.16.3)

By declaring mlflow_pipeline_hook and mlflow_node_hook in (src/package_name/ ProjectContext:

from kedro_mlflow.framework.hooks import mlflow_pipeline_hook, mlflow_node_hook

class ProjectContext(KedroContext):
    """Users can override the remaining methods from the parent class here,
    or create new ones (e.g. as required by plugins)

    project_name = "<project-name>"
    project_version = "0.16.X" # must be >=0.16.0
    hooks = (

Declaring hooks through static configuration in .kedro.yml or pyproject.toml [Only for kedro >= 0.16.5 if you have disabled auto-registration]

In case you have disabled hooks for plugin, you can add them manually by declaring mlflow_pipeline_hook and mlflow_node_hook in .kedro.yml :

project_name: "km_example"
project_version: "0.16.5"
package_name: "km_example"
  - <your-project>.hooks.project_hooks
  - kedro_mlflow.framework.hooks.mlflow_pipeline_hook
  - kedro_mlflow.framework.hooks.mlflow_node_hook

Or by declaring mlflow_pipeline_hook and mlflow_node_hook in pyproject.toml :

# <your-project>/pyproject.toml