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The typical workflow for seeing changes in your community visualization is to
upload your files to GCS, then refresh your Looker Studio report. This works,
but means that you can spend a lot of time waiting to see changes. dscc-gen
enables a workflow to immediately see your visualization code changes, reducing
the time it takes to write a community visualization.
dscc-gen comes with a default local dataset that's probably not representative
of the data you want to visualize. To update this dataset to meet your needs:
Build files from ./src into ./build with
caching disabled.
npm run push:dev
Copy the files from build to your dev bucket.
npm run build:prod
Build files from ./src into ./build with
caching enabled.
npm run push:prod
Copy the files from build to your prod
bucket.
The update_message command defaults to the objectFormat. To use the
tableFormat, edit the parameters in the update_message script in
package.json from -f object to -f table.
Codelab
To learn how to use the tooling, review the dscc-gen codelab.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-09-18 UTC."],[[["\u003cp\u003e\u003ccode\u003edscc-gen\u003c/code\u003e accelerates community visualization development in Looker Studio by enabling immediate visualization of code changes.\u003c/p\u003e\n"],["\u003cp\u003eTo utilize \u003ccode\u003edscc-gen\u003c/code\u003e, ensure npm 5.2.0 or later and gsutil are installed, then execute the command \u003ccode\u003enpx @google/dscc-gen viz\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe initial setup involves configuring the local dataset, deploying a visualization to your \u003ccode\u003edev\u003c/code\u003e bucket, and connecting to a representative dataset in Looker Studio.\u003c/p\u003e\n"],["\u003cp\u003eVarious scripts are provided for development, including \u003ccode\u003estart\u003c/code\u003e, \u003ccode\u003eupdate_message\u003c/code\u003e, \u003ccode\u003ebuild:dev\u003c/code\u003e, \u003ccode\u003epush:dev\u003c/code\u003e, \u003ccode\u003ebuild:prod\u003c/code\u003e, and \u003ccode\u003epush:prod\u003c/code\u003e, each serving specific functions in the workflow.\u003c/p\u003e\n"],["\u003cp\u003eA detailed codelab is available to guide users through the process of using the \u003ccode\u003edscc-gen\u003c/code\u003e tooling.\u003c/p\u003e\n"]]],[],null,["# Write your visualizations faster with dscc-gen\n\nThe typical workflow for seeing changes in your community visualization is to\n[upload](/looker-studio/visualization/upload-viz) your files to GCS, then refresh your Looker Studio report. This works,\nbut means that you can spend a lot of time waiting to see changes. [dscc-gen](https://github.com/googledatastudio/dscc-gen)\nenables a workflow to immediately see your visualization code changes, reducing\nthe time it takes to write a community visualization.\n\nTo get started, make sure [npm 5.2.0 or later](https://www.npmjs.com/get-npm) and [gsutil](https://cloud.google.com/storage/docs/gsutil) are installed. Then,\nrun: \n\n npx @google/dscc-gen viz\n\n| **Note:** If you prefer to use yarn, pass `--yarn` as an argument.\n\nFirst Time Configuration\n------------------------\n\n`dscc-gen` comes with a default local dataset that's probably not representative\nof the data you want to visualize. To update this dataset to meet your needs:\n\n1. [Update your config](/looker-studio/visualization/config-reference) at `src/index.json`.\n2. Run `npm run update_message`. This deploys a visualization to your `dev` bucket that displays the [message](/looker-studio/visualization/library-reference) in a format that's easy to copy.\n3. [Create a new report](https://lookerstudio.google.com) and connect to a dataset that's representative of the data you want to visualize.\n4. [Add a community visualization](/looker-studio/visualization/load-viz) using your `dev` bucket as your component ID.\n5. Copy the contents of the visualization to `scripts/data/localData.js`. This data will be used when you develop locally.\n\nScripts\n-------\n\nThe following scripts are available for visualization projects created with\n`dscc-gen`.\n\n| Command | Action |\n|--------------------------|--------------------------------------------------------------------------------------------------------------------|\n| `npm run start` | Start the local server and preview your visualization |\n| `npm run update_message` | Update the message using the [objectFormat](/looker-studio/visualization/library-reference#objectformat_reference) |\n| `npm run build:dev` | Build files from `./src` into `./build` with [caching](/looker-studio/visualization/caching) disabled. |\n| `npm run push:dev` | Copy the files from `build` to your `dev` bucket. |\n| `npm run build:prod` | Build files from `./src` into `./build` with [caching](/looker-studio/visualization/caching) enabled. |\n| `npm run push:prod` | Copy the files from `build` to your `prod` bucket. |\n\n| **Caution:** Before you build \\& deploy your viz, make sure you change `const LOCAL=` in `src/index.js` to `false`.\n\nThe `update_message` command defaults to the [objectFormat](/looker-studio/visualization/library-reference#objectformat_reference). To use the\n[tableFormat](/looker-studio/visualization/library-reference#tableformat_reference), edit the parameters in the `update_message` script in\n`package.json` from `-f object` to `-f table`.\n\nCodelab\n-------\n\nTo learn how to use the tooling, review the dscc-gen [codelab](https://codelabs.developers.google.com/codelabs/community-visualization-dscc-gen/).\n\n[](https://codelabs.developers.google.com/codelabs/community-visualization-dscc-gen/)"]]
