Plugins & Extending Dataiku

Hi @MNOP
,

You can create a plugin with an R Shiny webapp to be displayed in the Visual ML analysis view.

From your Shiny weabpp, you will select "Convert to plugin webapp" from your R shiny webapp:

In the newly created plugin webapp.json file, you will need to ensure that the roles are defined for ANALYSIS, like so:

    "roles": [
        {
            "type": "SAVED_MODEL",
            "contentType": "prediction",
            "backendTypes": ["PY_MEMORY"],
            "predictionTypes": ["BINARY_CLASSIFICATION"],
            "targetParamsKey": "modelId",
            "pathParamsKey": "versionId"
        },
        {
          "type": "ANALYSIS",
          "contentType": "prediction",
          "backendTypes": ["PY_MEMORY"],
          "predictionTypes": ["BINARY_CLASSIFICATION"],
          "targetParamsKey": "trainedModelFullModelId"
        }
    ]

You will also need to create an R code environment for your plugin. You can do so by creating a new "R" code environment from the "Summary" tab of your plugin:

Then, you'll want to makes sure that any required R packages are listed in your plugin's rPackages.txt file, and you'll need to then build your code environment back on the "Summary" tab of the plugin, after you've fully set up the code environment specs like so:

Here is an example of the basic shiny webapp example converted to a plugin that is available in the Visual ML Analysis screen:

I'm attaching an example of this plugin in case it's helpful as a reference point.

Thanks!
Sarina  

Hi @MNOP
,

You can create a plugin with an R Shiny webapp to be displayed in the Visual ML analysis view.

From your Shiny weabpp, you will select "Convert to plugin webapp" from your R shiny webapp:

In the newly created plugin webapp.json file, you will need to ensure that the roles are defined for ANALYSIS, like so:

    "roles": [
        {
            "type": "SAVED_MODEL",
            "contentType": "prediction",
            "backendTypes": ["PY_MEMORY"],
            "predictionTypes": ["BINARY_CLASSIFICATION"],
            "targetParamsKey": "modelId",
            "pathParamsKey": "versionId"
        },
        {
          "type": "ANALYSIS",
          "contentType": "prediction",
          "backendTypes": ["PY_MEMORY"],
          "predictionTypes": ["BINARY_CLASSIFICATION"],
          "targetParamsKey": "trainedModelFullModelId"
        }
    ]

You will also need to create an R code environment for your plugin. You can do so by creating a new "R" code environment from the "Summary" tab of your plugin:

Then, you'll want to makes sure that any required R packages are listed in your plugin's rPackages.txt file, and you'll need to then build your code environment back on the "Summary" tab of the plugin, after you've fully set up the code environment specs like so:

Here is an example of the basic shiny webapp example converted to a plugin that is available in the Visual ML Analysis screen:

I'm attaching an example of this plugin in case it's helpful as a reference point.

Thanks!
Sarina  

Hi @MNOP
,

Please see my response on your post here for an example:
https://community.dataiku.com/t5/Plugins-Extending-Dataiku/Web-app-as-a-plugin-usign-R-Shiny/td-p/40982

Thank you,
Sarina