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Kedro-Viz


Kedro-Viz Pipeline Visualisation

✨ Data Science Pipelines. Beautifully Designed ✨
Live Demo: https://demo.kedro.org/


CircleCI Documentation Python Version PyPI version Downloads npm version License code style: prettier Slack Organisation

Introduction

Kedro-Viz is an interactive development tool for building data science pipelines with Kedro. Kedro-Viz also allows users to view and compare different runs in the Kedro project.

Features

  • ✨ Complete visualisation of a Kedro project and its pipelines
  • 🎨 Supports light & dark themes out of the box
  • 🚀 Scales to big pipelines with hundreds of nodes
  • 🔎 Highly interactive, filterable and searchable
  • 🔬 Focus mode for modular pipeline visualisation
  • 📊 Rich metadata side panel to display parameters, plots, etc.
  • 📊 Supports all types of Plotly charts
  • ♻️ Autoreload on code change
  • 🧪 Supports tracking and comparing runs in a Kedro project
  • 🎩 Many more to come

Installation

There are two ways you can use Kedro-Viz:

  • As a Kedro plugin (the most common way).

    To install Kedro-Viz as a Kedro plugin:

    pip install kedro-viz

  • As a standalone React component (for embedding Kedro-Viz in your web application).

    To install the standalone React component:

    npm install @quantumblack/kedro-viz

Usage

Compatibility with Kedro and Kedro-datasets

Ensure your Kedro, Kedro-Viz and Kedro-datasets versions are supported by referencing the following table:

Python Version Last Supported
Kedro Kedro-Viz Kedro-datasets
3.6 0.17.7 4.1.1 -
3.7 0.18.14 6.7.0 1.8.0
3.8 Latest 7.1.0 1.8.0
>= 3.9 Latest Latest Latest
​

CLI Usage

To launch Kedro-Viz from the command line as a Kedro plugin, use the following command from the root folder of your Kedro project:

kedro viz run

A browser tab opens automatically to serve the visualisation at http://127.0.0.1:4141/.

Kedro-Viz also supports the following additional arguments on the command line:

Usage: kedro viz run [OPTIONS]

  Visualise a Kedro pipeline using Kedro-Viz.

Options:
  --host TEXT               Host that viz will listen to. Defaults to
                            localhost.

  --port INTEGER            TCP port that viz will listen to. Defaults to
                            4141.

  --browser / --no-browser  Whether to open viz interface in the default
                            browser or not. Browser will only be opened if
                            host is localhost. Defaults to True.

  --load-file FILE          Path to load kedro-viz data from a directory
  --save-file FILE          Path to save kedro-viz data to a directory 
  --pipeline TEXT           Name of the registered pipeline to visualise. If not
                            set, the default pipeline is visualised

  -e, --env TEXT            Kedro configuration environment. If not specified,
                            catalog config in `local` will be used

  --autoreload              Autoreload viz server when a Python or YAML file change in
                            the Kedro project

  --ignore-plugins          A flag to ignore all installed plugins in the Kedro Project
  
  --params TEXT             Specify extra parameters that you want to pass to
                            the context initializer. Items must be separated
                            by comma, keys - by colon, example:
                            param1:value1,param2:value2. Each parameter is
                            split by the first comma, so parameter values are
                            allowed to contain colons, parameter keys are not.
                            To pass a nested dictionary as parameter, separate
                            keys by '.', example: param_group.param1:value1.

  -h, --help                Show this message and exit.

To deploy Kedro-Viz from the command line as a Kedro plugin, use the following command from the root folder of your Kedro project:

kedro viz deploy
Usage: kedro viz deploy [OPTIONS]

  Deploy and host Kedro Viz on AWS S3.

Options:
  --region TEXT       AWS region where your S3 bucket is located  [required]
  --bucket-name TEXT  AWS S3 bucket name where Kedro Viz will be hosted
                      [required]
  -h, --help          Show this message and exit.

To create a build directory of your local Kedro-Viz instance with static data from the command line, use the following command from the root folder of your Kedro project:

kedro viz build

Experiment Tracking usage

To enable experiment tracking in Kedro-Viz, you need to add the Kedro-Viz SQLiteStore to your Kedro project.

This can be done by adding the below code to settings.py in the src folder of your Kedro project.

from kedro_viz.integrations.kedro.sqlite_store import SQLiteStore
from pathlib import Path
SESSION_STORE_CLASS = SQLiteStore
SESSION_STORE_ARGS = {"path": str(Path(__file__).parents[2] / "data")}

Once the above set-up is complete, tracking datasets can be used to track relevant data for Kedro runs. More information on how to use tracking datasets can be found in the experiment tracking documentation

Notes:

  • Experiment Tracking is only available for Kedro-Viz >= 4.0.2 and Kedro >= 0.17.5
  • Prior to Kedro 0.17.6, when using tracking datasets, you will have to explicitly mark the datasets as versioned for it to show up properly in Kedro-Viz experiment tracking tab. From Kedro >= 0.17.6, this is done automatically:
train_evaluation.r2_score_linear_regression:
  type: tracking.MetricsDataset
  filepath: ${base_location}/09_tracking/linear_score.json
  versioned: true

Standalone React component usage

To use Kedro-Viz as a standalone React component, you can follow the example below. However, please note that Kedro-Viz does not support server-side rendering (SSR). If you're using Next.js or another SSR framework, you should be aware of this limitation.

import KedroViz from '@quantumblack/kedro-viz';
import '@quantumblack/kedro-viz/lib/styles/styles.min.css';

const MyApp = () => <KedroViz data={json} />;

To use with NextJS:

import '@quantumblack/kedro-viz/lib/styles/styles.min.css';
import dynamic from 'next/dynamic';

const NoSSRKedro = dynamic(() => import('@quantumblack/kedro-viz'), {
  ssr: false,
});

const MyApp = () => <NoSSRKedro data={json} />;

The JSON can be obtained by running:

kedro viz run --save-file=filename

We also recommend wrapping the Kedro-Viz component with a parent HTML/JSX element that has a specified height (as seen in the above example) in order for Kedro-Viz to be styled properly.

Our documentation contains additional examples on how to visualise with Kedro-Viz.

Feature Flags

Kedro-Viz uses features flags to roll out some experimental features. The following flags are currently in use:

Flag Description
sizewarning From release v3.9.1. Show a warning before rendering very large graphs (default true)
expandAllPipelines From release v4.3.2. Expand all modular pipelines on first load (default false)

To enable or disable a flag, click on the settings icon in the toolbar and toggle the flag on/off.

Kedro-Viz also logs a message in your browser's developer console to show the available flags and their values as currently set on your machine.

Maintainers

Kedro-Viz is maintained by the Kedro team and a number of contributors from across the world.

Contribution

If you want to contribute to Kedro-Viz, please check out our contributing guide.

License

Kedro-Viz is licensed under the Apache 2.0 License.

Citation

If you're an academic, Kedro-Viz can also help you, for example, as a tool to visualise how your publication's pipeline is structured. Find our citation reference on Zenodo.