# Initialize your Kedro project

This section assume that [you have installed `kedro-mlflow` in your virtual environment](https://kedro-mlflow.readthedocs.io/en/latest/source/02_getting_started/01_installation/01_installation.html).

## 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](https://docs.kedro.org/en/stable/get_started/minimal_kedro_project.html#step-2-create-a-new-kedro-project).

If you do not have a real-world project, you can use a kedro example and [follow the "Quickstart in 1 mn" example](https://kedro-mlflow.readthedocs.io/en/latest/source/02_getting_started/02_quickstart/01_example_project.html) 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.

### Setting up the ``kedro-mlflow`` configuration file


``kedro-mlflow`` is [configured](https://kedro-mlflow.readthedocs.io/en/latest/source//05_API/01_python_objects/05_Configuration.html) through an ``mlflow.yml`` file. The recommended way to initialize the `mlflow.yml` is by using [the ``kedro-mlflow`` CLI](https://kedro-mlflow.readthedocs.io/en/latest/source/05_API/01_python_objects/04_CLI.html), but you can create it manually.

```{note}
Since ``kedro-mlflow>=0.11.2``, the configuration file is optional. However, the plugin will use default ``mlflow`` configuration. Specifically, the runs will be stored in a ``mlruns`` folder at the root fo the kedro project since no ``mlflow_tracking_uri`` is configured.
```

Set the working directory at the root of your kedro project:

```console
cd path/to/your/project
```

Run the init command :

```console
kedro mlflow init
```

you should see the following message:

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

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

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

### Declaring ``kedro-mlflow`` hooks

``kedro_mlflow`` hooks implementations must be registered with Kedro. There are 2 ways of registering [hooks](https://docs.kedro.org/en/stable/hooks/introduction.html).

```{important}
You must register the hook provided by ``kedro-mlflow`` (the ``MlflowHook``) to make the plugin work.
```

::::{tab-set}

:::{tab-item} `kedro>=0.16.4` - auto-discovery

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](https://docs.kedro.org/en/stable/hooks/introduction.html#disable-auto-registered-plugins-hooks) in your `settings.py` file.

:::

:::{tab-item} `kedro>=0.16.0, <=0.16.3` - register in ``settings.py``

If you have turned off plugin automatic registration, you can register its hooks manually by [adding them to ``settings.py``](https://docs.kedro.org/en/stable/hooks/introduction.html#registering-your-hook-implementations-with-kedro):

```python
# <your_project>/src/<your_project>/settings.py
from kedro_mlflow.framework.hooks import MlflowHook

HOOKS = (MlflowHook(),)
```

:::

::::