Kedro Viz CLI reference¶
The Kedro Viz CLI provides commands to visualise Kedro pipelines, deploy them to cloud platforms, and export the visualisation data. Below is a detailed description of the available commands and options.
Commands¶
kedro viz
¶
Launches a local Kedro Viz instance to visualise a Kedro pipeline.
Usage:
kedro viz [OPTIONS]
Description:
This command launches the Kedro Viz server to visualise a Kedro pipeline. It is functionally the same as kedro viz run
. If no sub-command is provided, run
is used by default.
Options:
This command accepts all the options that are available in the kedro viz
, kedro viz run
command. See the kedro viz run
section for a complete list of options.
kedro viz run
¶
Launches a local Kedro Viz instance to visualise a Kedro pipeline.
Usage:
kedro viz run [OPTIONS]
Options:
--host <host>
Host that Kedro Viz will listen to. Defaults to
localhost
.
--port <port>
TCP port that Kedro Viz will listen to. Defaults to
4141
.
--browser / --no-browser
Whether to open the Kedro Viz interface in the default browser. The browser will open if the host is
localhost
. Defaults toTrue
.
--load-file <path>
Path to load Kedro Viz data from a directory. If provided, Kedro Viz will load the visualisation data from this path instead of generating it from the pipeline.
--save-file <path>
Path to save Kedro Viz data to a directory. If provided, the visualisation data will be saved to this path for later use.
--pipeline, -p <pipeline>
Name of the registered pipeline to visualise. If not set, the default pipeline is visualised.
--env, -e {environment>}
Kedro configuration environment. If not specified, the catalog config in
local
will be used. You can also set this through theKEDRO_ENV
environment variable.
--autoreload, -a
Enable autoreload of the Kedro Viz server when a Python or YAML file changes in the Kedro project.
--include-hooks
Include all registered hooks in the Kedro project for visualisation.
--params <params>
Specify extra parameters for the Kedro Viz run. This option supports the same format as the
params
option in the Kedro CLI.
--lite
An experimental flag to open Kedro-Viz without Kedro project dependencies.
Note
When running Kedro Viz locally with the --autoreload
option, the server will automatically restart whenever there are changes to Python, YAML, or JSON files in the Kedro project. This is particularly useful during development.
kedro viz deploy
¶
Deploy and host Kedro Viz on a specified cloud platform.
Note
The deploy
command supports deployment to AWS, Azure and GCP. Ensure that your cloud credentials and configurations are correctly set up before deploying.
Usage:
kedro viz deploy [OPTIONS]
Options:
--platform <platform>
The cloud platform to host Kedro Viz on. Supported platforms include
aws
azure
andgcp
. This option is required.
--endpoint <endpoint>
The static website hosted endpoint. This option is required.
--bucket-name <bucket-name>
The name of the bucket where Kedro Viz will be hosted. This option is required.
--include-hooks
Include all registered hooks in the Kedro project in the deployed visualisation.
--include-previews
Include previews for all datasets in the deployed visualisation.
kedro viz build
¶
Create a build directory of a local Kedro Viz instance with Kedro project data.
Usage:
kedro viz build [OPTIONS]
Options:
--include-hooks
Include all registered hooks in the Kedro project in the built visualisation.
--include-previews
Include previews for all datasets in the built visualisation.
Examples¶
Running Kedro Viz locally¶
To run Kedro Viz on your local machine, use:
kedro viz
To specify a particular pipeline and environment:
kedro viz -p my_pipeline -e dev
or
kedro viz run -p my_pipeline -e dev
Deploying Kedro Viz to AWS¶
To deploy Kedro Viz to an S3 bucket on AWS:
kedro viz deploy --platform aws --endpoint http://mybucket.s3-website-us-west-2.amazonaws.com --bucket-name mybucket
Building Kedro Viz to host on multiple platforms¶
To create a build directory with the visualisation data:
kedro viz build --include-previews