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This is a concept deep learning app created using Splunk UI toolkit.

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siddharthajuprod07/splunk-deeplearning-concept-app

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Contributing to SplunkDeepLearningAppRepo

Overview

The project contains a variety of packages that are published and versioned collectively. Each package lives in its own directory in the /packages directory. Each package is self contained, and defines its dependencies in a package.json file.

We use Yarn Workspaces and Lerna for managing and publishing multiple packages in the same repository.

Getting Started

  1. Clone the repo.
  2. Install yarn (>= 1.2) if you haven't already: npm install --global yarn.
  3. Run the setup task: yarn run setup.

After this step, the following tasks will be available:

  • start – Run the start task for each project
  • build – Create a production bundle for all projects
  • test – Run unit tests for each project
  • lint – Run JS and CSS linters for each project
  • format – Run prettier to auto-format *.js, *.jsx and *.css files. This command will overwrite files without asking, format:verify won't.

Running yarn run setup once is required to enable all other tasks. The command might take a few minutes to finish.

Developer Scripts

Commands run from the root directory will be applied to all packages. This is handy when working on multiple packages simultaneously. Commands can also be run from individual packages. This may be better for performance and reporting when only working on a single package. All of the packages have similar developer scripts, but not all scripts are implemented for every package. See the package.json of the package in question to see which scripts are available there.

For more granular control of development scripts, consider using Lerna directly.

Code Formatting

SplunkDeepLearningAppRepo uses prettier to ensure consistent code formatting. It is recommended to add a prettier plugin to your editor/ide.

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This is a concept deep learning app created using Splunk UI toolkit.

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