Kedro-Viz
✨ Data Science Pipelines. Beautifully Designed ✨
Live Demo: https://demo.kedro.org/
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:
```bash
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:
```bash
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
--include-hooks A flag to include all registered hooks in your
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:
```bash
kedro viz deploy
```
```bash
Usage: kedro viz deploy [OPTIONS]
Deploy and host Kedro Viz on AWS S3.
Options:
--platform TEXT Supported Cloud Platforms like ('aws', 'azure', 'gcp')
to host Kedro Viz [required]
--endpoint TEXT Static Website hosted endpoint.(eg., For AWS - http://
.s3-website..amazonaws.com/)
[required]
--bucket-name TEXT Bucket name where Kedro Viz will be hosted [required]
--include-hooks A flag to include all registered hooks in your Kedro
Project
--include-previews A flag to include preview for all the datasets
-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:
```bash
kedro viz build
```
```bash
Usage: kedro viz build [OPTIONS]
Create build directory of local Kedro Viz instance with Kedro project data
Options:
--include-hooks A flag to include all registered hooks in your Kedro
Project
--include-previews A flag to include preview for all the datasets
-h, --help Show this message and exit.
```
### Experiment Tracking usage
To enable [experiment tracking](https://docs.kedro.org/en/stable/experiment_tracking/index.html) 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.
```python
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](https://docs.kedro.org/en/stable/experiment_tracking/index.html)
**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:
```yaml
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.
```javascript
import KedroViz from '@quantumblack/kedro-viz';
import '@quantumblack/kedro-viz/lib/styles/styles.min.css';
const MyApp = () => ;
```
To use with NextJS:
```javascript
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 = () => ;
```
The JSON can be obtained by running:
```bash
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.](https://docs.kedro.org/en/stable/visualisation/index.html)_**
## 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](https://developer.mozilla.org/en-US/docs/Learn/Common_questions/What_are_browser_developer_tools#The_JavaScript_console) to show the available flags and their values as currently set on your machine.
## Maintainers
Kedro-Viz is maintained by the [Kedro team](https://docs.kedro.org/en/stable/contribution/technical_steering_committee.html#kedro-maintainers) and a number of [contributors from across the world](https://github.com/kedro-org/Kedro-Viz/contributors).
## Contribution
If you want to contribute to Kedro-Viz, please check out our [contributing guide](./CONTRIBUTING.md).
## License
Kedro-Viz is licensed under the [Apache 2.0](https://github.com/kedro-org/kedro-viz/blob/main/LICENSE.md) 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](https://doi.org/10.5281/zenodo.4277218).