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.
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.
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
.
- Host that Kedro Viz will listen to. Defaults to
-
--port <port>
- TCP port that Kedro Viz will listen to. Defaults to
4141
.
- TCP port that Kedro Viz will listen to. Defaults to
-
--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
.
- Whether to open the Kedro Viz interface in the default browser. The browser will open if the host is
-
--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.
- Kedro configuration environment. If not specified, the catalog config in
-
--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.
- Specify extra parameters for the Kedro Viz run. This option supports the same format as the
-
--lite
- An experimental flag to open Kedro-Viz without Kedro project dependencies.
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.
Deploy and host Kedro Viz on a specified cloud platform.
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.
- The cloud platform to host Kedro Viz on. Supported platforms include
-
--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.
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.
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
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
To create a build directory with the visualisation data:
kedro viz build --include-previews