Listing and deleting a selection of projects#

Prerequisites#

Dataiku >= 13.4
A Python code environment with dash package installed (see the documentation for more details)

Note

The code in this tutorial has been tested with two configurations:

python==3.9 with dash==2.7.0
python==3.11 with dash==3.1.1

but other versions could work.

Introduction#

Occasionally, you should clean up and remove unused projects on a development instance. This tutorial will show you how to build a Dash application that lists all the projects in a Data Table. This list will be selectable, and we will add a button to delete the selected projects.

Building the webapp#

Creating the webapp#

Please start with an empty Dash web app. For instructions on creating an empty Dash web app, refer to this tutorial.

Creating the Data Table#

Let’s start with the following Code 1

Code 1: Create the Data Table#

from dash import html, dash_table
import dataiku
import pandas as pd
import logging

logger = logging.getLogger(__name__)
logger.info('start webapp')

client = dataiku.api_client()


def get_projects():
    """
    Returns a pandas dataframe containing the key, name, and short description for each project
    """
    projects = client.list_projects()
    keys = [proj['projectKey'] for proj in projects]
    names = [proj['name'] for proj in projects]
    desc = [proj.get('shortDesc', 'No description found.') for proj in projects]
    data = {
        "key": keys,
        "name": names,
        "description": desc
    }

    return pd.DataFrame(data)


projects_table = dash_table.DataTable(
    id='projects_table',
    columns=[{"name": i, "id": i, "selectable": True} for i in get_projects().columns],
    data=get_projects().to_dict('records'),
    row_selectable='multi',
    selected_rows=[],
    editable=True
)

# build your Dash app
app.layout = html.Div([
    html.H1("List of projects"),
    projects_table
])

We start retrieving the project list using the list_projects() method from the dataikuapi.DSSClient class. That’s the purpose of the get_project() function.

The creation of the DataTable from Dash uses two important parameters.

row_selectable='multi' will add a checkbox on each row to enable the multi-selection of projects.
editable=True will allow the update of the project list after each delete action.

Adding a delete mechanism#

At that point, we need a button to trigger the delete action of the selected projects. To be sure the user is aware of the action, we will encapsulate the button in a Dash component called ConfirmDialogProvider

app.layout = html.Div([
    html.H1("List of projects"),
    projects_table,
    dcc.ConfirmDialogProvider(
        children=html.Button('Delete', id='delete-button', n_clicks=0),
        id='warning-delete',
        message='Are you sure you want to delete the selected project(s)?'
    )
])

Note

In this section, you will need new import instructions. If you need help on this topic, have a look at the complete code.

The user’s confirmation will then trigger a Dash Callback that will handle the selection deletion and the update of the DataTable.

@callback(
    Output('projects_table', 'data'),
    Output('projects_table', 'selected_rows'),
    Input('warning-delete', 'submit_n_clicks'),
    State('projects_table', 'selected_rows'),
    prevent_initial_call=True
)
def delete_projects(submit_n_clicks, selected_rows):
    """
    Callback triggered when the user click on the delete button
    This will delete all the selected projects.
    Returns the updated list of projects and reset the selection
    """
    projects = get_projects()
    for key in projects.iloc[selected_rows]['key'].to_list():
        project = client.get_project(key)
        project.delete(clear_managed_datasets=True, clear_output_managed_folders=True, clear_job_and_scenario_logs=True)
        logger.info(f"project {key} deleted")
    updated_projects = projects.loc[~projects.index.isin(selected_rows)].to_dict('records')

    return updated_projects, []

The callback is triggered when the user clicks on the delete button. The Input parameter defines the element change that will trigger the callback. Note the use of Dash State. This State parameter will allow access to the list of selected rows without triggering the callback, as it would have been with an Input parameter. The callback will return the updated list of projects, defined by the first Output parameter, and reset the selection as defined by the second Output parameter.

Wrapping up#

Congratulations! You now have a web application that will help you to clean an instance by removing a selection of projects. You can improve it with a refresh button that will update the list of projects.

Here is the complete code of the web application:

Reference documentation#

Classes#

`dataikuapi.DSSClient`(host[, api_key, ...])	Entry point for the DSS API client
`dataikuapi.dss.project.DSSProject`(client, ...)	A handle to interact with a project on the DSS instance.

Functions#

`delete`([clear_managed_datasets, ...])	Delete the project
`get_project`(project_key)	Get a handle to interact with a specific project.
`list_projects`()	List the projects