\n\u2728 Data Science Pipelines. Beautifully Designed \u2728\n \nLive Demo: https://demo.kedro.org/\n
\n\n \n\n[](https://circleci.com/gh/kedro-org/kedro-viz/tree/main)\n[](https://badge.fury.io/js/%40quantumblack%2Fkedro-viz)\n[](https://pypi.org/project/kedro-viz/)\n[](https://pypi.org/project/kedro-viz/)\n[](https://opensource.org/licenses/Apache-2.0)\n[](https://doi.org/10.5281/zenodo.4355948)\n[](https://github.com/prettier/prettier)\n\n## Introduction\n\nKedro-Viz is an interactive development tool for building data science pipelines with [Kedro](https://github.com/kedro-org/kedro). Kedro-Viz also allows users to view and compare different runs in the Kedro project.\n\n## Features\n\n- \u2728 Complete visualisation of a Kedro project and its pipelines\n- \ud83c\udfa8 Supports light & dark themes out of the box\n- \ud83d\ude80 Scales to big pipelines with hundreds of nodes\n- \ud83d\udd0e Highly interactive, filterable and searchable\n- \ud83d\udd2c Focus mode for modular pipeline visualisation\n- \ud83d\udcca Rich metadata side panel to display parameters, plots, etc.\n- \u267b\ufe0f Autoreload on code change\n- \ud83e\uddea Supports tracking and comparing runs in a Kedro project\n- \ud83c\udfa9 Many more to come\n\n## Installation\n\nThere are two ways you can use Kedro-Viz:\n\n- As a [Kedro plugin](https://kedro.readthedocs.io/en/stable/07_extend_kedro/04_plugins.html) (the most common way).\n\n To install Kedro-Viz as a Kedro plugin:\n\n ```bash\n pip install kedro-viz\n ```\n\n- As a standalone React component (for embedding Kedro-Viz in your web application).\n\n To install the standalone React component:\n\n ```bash\n npm install @quantumblack/kedro-viz\n ```\n\n## Usage\n\n### CLI Usage\n\nTo launch Kedro-Viz from the command line as a Kedro plugin, use the following command from the root folder of your Kedro project:\n\n```bash\nkedro viz\n```\n\nA browser tab opens automatically to serve the visualisation at `http://127.0.0.1:4141/`.\n\nKedro-Viz also supports the following additional arguments on the command line:\n\n```bash\nUsage: kedro viz [OPTIONS]\n\n Visualise a Kedro pipeline using Kedro-Viz.\n\nOptions:\n --host TEXT Host that viz will listen to. Defaults to\n localhost.\n\n --port INTEGER TCP port that viz will listen to. Defaults to\n 4141.\n\n --browser / --no-browser Whether to open viz interface in the default\n browser or not. Browser will only be opened if\n host is localhost. Defaults to True.\n\n --load-file FILE Path to load the pipeline JSON file\n --save-file FILE Path to save the pipeline JSON file\n --pipeline TEXT Name of the registered pipeline to visualise. If not\n set, the default pipeline is visualised\n\n -e, --env TEXT Kedro configuration environment. If not specified,\n catalog config in `local` will be used\n\n --autoreload Autoreload viz server when a Python or YAML file change in\n the Kedro project\n\n -h, --help Show this message and exit.\n```\n\n### Experiment Tracking usage\n\nTo enable [experiment tracking](https://kedro.readthedocs.io/en/stable/08_logging/02_experiment_tracking.html) in Kedro-Viz, you need to add the Kedro-Viz `SQLiteStore` to your Kedro project.\n\nThis can be done by adding the below code to `settings.py` in the `src` folder of your Kedro project.\n\n```python\nfrom kedro_viz.integrations.kedro.sqlite_store import SQLiteStore\nfrom pathlib import Path\nSESSION_STORE_CLASS = SQLiteStore\nSESSION_STORE_ARGS = {\"path\": str(Path(__file__).parents[2] / \"data\")}\n```\n\nOnce 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 [here](https://kedro.readthedocs.io/en/stable/08_logging/02_experiment_tracking.html)\n\n**Notes:**\n\n- Experiment Tracking is only available for Kedro-Viz >= 4.0.2 and Kedro >= 0.17.5\n- 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:\n\n```yaml\ntrain_evaluation.r2_score_linear_regression:\n type: tracking.MetricsDataSet\n filepath: ${base_location}/09_tracking/linear_score.json\n versioned: true\n```\n\n### Standalone React component usage\n\nTo use Kedro-Viz as a standalone React component, import the component and supply a data JSON as prop:\n\n```javascript\nimport KedroViz from '@quantumblack/kedro-viz';\n\nconst MyApp = () => (\n