Kedro-Viz
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Kedro-Viz shows you how your Kedro data pipelines are structured.
With Kedro-Viz you can:
- See how your datasets and Python functions (nodes) are resolved in Kedro so that you can understand how your data pipeline is built
- Get a clear picture when you have lots of datasets and nodes by using tags to visualise sub-pipelines
- Search for nodes and datasets
This project was bootstrapped with Create React App, for which more complete documentation is available on the project website.
How do I install and use Kedro-Viz?
For in-depth development and usage notes, see the Contribution Guidelines.
As a Kedro Python plugin
Kedro-Viz is available as a Python plugin named kedro-viz.
The following conditions must be true in order to visualise your pipeline:
- Your project directory must be available to the Kedro-Viz plugin.
- You must be using a Kedro project structure with a complete Data Catalog, nodes and pipeline structure.
To install it:
pip install kedro-viz
This will install kedro as a dependency, and add kedro viz as an additional CLI command.
To visualise your pipeline, go to your project root directory and install the project-specific dependencies by running:
kedro install
This will install the dependencies specified in requirements.txt in your Kedro environment (see the Kedro documentation for how to set up your Python virtual environment).
Finally, run the following command from the project directory to visualise your pipeline:
kedro viz
This command will run kedro_viz.server on http://127.0.0.1:4141/ which cannot be accessed from another machine.
If you are using a remote server machine or a docker container, run the following command instead.
kedro viz --host 0.0.0.0
You can change the port with --port option if needed.
As a JavaScript React component
Kedro-Viz is also available as an npm package named @quantumblack/kedro-viz. To install it:
npm install @quantumblack/kedro-viz
Then include it in your React application:
import KedroViz from '@quantumblack/kedro-viz';
const MyApp = () => <KedroViz data={json} />;
As a JavaScript React component, the project is designed to be used in two different ways:
-
Standalone application
Run
npm run buildto generate a production build as a full-page app. The built app will be placed in the/builddirectory. Data for the chart should be placed in/public/api/nodes.jsonbecause this directory is markedgitignore. -
React component
Kedro-Viz can be used as a React component that can be imported into other applications. Publishing the package will run
npm run lib, which compiles the source code in/src, and places it in the/libdirectory.
What licence do you use?
Kedro-Viz is licensed under the Apache 2.0 License.
4 maintainers
Release files for kedro-viz 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kedro-viz-2.0.0.tar.gz | 827.9 kB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kedro_viz-2.0.0-py3.6.egg | Legacy Egg format | - | - | Details |
| kedro_viz-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.5 MB
Release files / kedro-viz-2.0.0.tar.gz
| Download URL | kedro-viz-2.0.0.tar.gz |
|---|---|
| Size | 827.9 kB |
| Tags | Source |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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Release files / kedro_viz-2.0.0-py3.6.egg
| Download URL | kedro_viz-2.0.0-py3.6.egg |
|---|---|
| Size | 841.1 kB |
| Tags | Egg |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / kedro_viz-2.0.0-py3-none-any.whl
| Download URL | kedro_viz-2.0.0-py3-none-any.whl |
|---|---|
| Size | 839.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.6.8
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