Create an Earthquake Data Connector

🕐 4 min read

Use cases
Instructions

The earthquake data JavaScript boilerplate is a connector connecting to earthquake data and contains simple JavaScript and HTML.

Use cases

JSON
Custom parsing
TypeScript
Good first connector

Instructions

To create your connector, we recommend that you first create a sample earthquake data connector and edit the generated files. It’s easier to get all the files and directory structure your connector needs by just using an existing example.

To create your earthquake data connector, do the following steps.

Step 1: Create a boilerplate earthquake data connector

Enter the following command to create the connector:
```
taco create my-earthquake-data-connector --boilerplate earthquake-data 
```
This creates a directory with the earthquake data boilerplate code, which is included with the toolkit.
Change directories to the my-earthquake-data-connector directory.
```
cd my-earthquake-data-connector
```
Build the connector by entering the following command:
```
taco build
```
This command clears any previous or existing build caches, then installs the dependencies, then builds the frontend code and the backend code (handlers), then copies the connector.json file (the configuration file).

Step 2: Configure your connector’s properties

In your new earthquake data connector directory, find and open the connector.json file.

{
  "name": "my-earthquake-data-connector",
  "displayName": "Earthquake Data Connector",
  "version": "1.0.0",
  "tableau-version": {
    "min": "2023.3"
  },
  "vendor": {
    "name": "vendor-name",
    "support-link": "https://vendor-name.com",
    "email": "support@vendor-name.com"
  },
  "permission": {
    "api": {
      "https://*.usgs.gov/": [
        "GET",
        "POST"
      ]
    }
  },
  "auth": {
    "type": "none"
  },
  "window": {
    "height": 800,
    "width": 600
  }
}

Make the following changes:

Change the general properties.

Name	Value
name	Your connector’s directory name
displayName	Your connector’s name. This is the name that appears in the Tableau connectors area.
version	Your connector’s version
min	The earliest Tableau version your connector supports

Change the company properties.

Name	Value
vendor.name	Your company name
vendor.support-link	Your company’s URL
vendor.email	Your company’s email

Change the permissions.

Name	Value
permission.api	The URI for the API that the connector is allowed to access, along with the methods (POST, GET, PUT, PATCH, DELETE) that the connector is allowed to use.

Verify the authentication type.

Name Value

auth.type Enter none.

For more information about authentication, see the Authentication section in the Considerations for Building Your Connector topic.

Name	Value
auth.type	Enter `none`.

Change the HTML pane size.

Name	Value
window.height	The height of the connector HTML pane
window.width	The width of the connector HTML pane

Step 3: Edit the user interface

When you open a web data connector in Tableau, the connector displays an HTML page that links to your JavaScript code and to your connector’s handlers. Optionally, this page can also display a user interface for your users to select the data that they want to download.

To create a user interface for your connector, open the /app/index.html file.

<!DOCTYPE html>
<html>

<head>
  <title>USGS Earthquake Feed</title>
  <meta http-equiv="Cache-Control" content="no-store" />
  <link rel="icon" href="data:,">
  <link href="index.css" rel="stylesheet" />
  <script src="index.ts" type="module" defer></script>
</head>

<body>
  <div class="box">
    <button type="button" id="submitButton" disabled>
      Please wait while settings load...
    </button>
  </div>
</body>

</html>

Let’s run through what the code is doing. Skipping over the standard markup for an HTML page, notice the following between the head tags:

The meta tag prevents your browser from caching the page.
The index.css file is used to simplify styling and formatting.
The index.ts file is the code for your connector.

Step 4: Edit the connector object

Now that you’ve created a user interface, it’s time to edit the TypeScript code for the connector’s button. First, open the /app/index.ts file.

function submit() {
  connector.handlerInputs = [
    {
      fetcher: 'MyFetcher',
      parser: 'MyParser',
      data: {
        url: 'https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/4.5_week.geojson',
      },
    },
  ]
  connector.submit()
}

Step 5: Update the fetcher file

If your data is complex and needs preprocessing, use the TACO Toolkit library to prepare your data. The following is the default code that the /handlers/MyFetcher.ts files uses to get the data:

import { Fetcher, FetchUtils, FetchOptions } from '@tableau/taco-toolkit/handlers'

export default class MyFetcher extends Fetcher {
  async *fetch({ handlerInput }: FetchOptions) {
    yield await FetchUtils.fetchJson(handlerInput.data.url)
  }
}

Step 6: Configure how the data is presented

Now you must define how you want to map the data to one or more or tables. This mapping of data is done in the schema.

To decide how to map your data, look at your data source. When you’re done looking at the summary of the JSON data source, make the necessary edits in the /handlers/MyParser.ts file to structure the returned data.

import { DataContainer, DataType, log, ParseOptions, Parser } from '@tableau/taco-toolkit/handlers'

interface FeatureRow {
  id: string
  properties: {
    mag: number
    title: string
  }
  geometry: {
    type: string
    coordinates: [number, number, number]
  }
}

interface FetcherResult {
  features: FeatureRow[]
}

export default class MyParser extends Parser<FetcherResult> {
  parse(fetcherResult: FetcherResult, { dataContainer }: ParseOptions): DataContainer {
    const tableName = 'My Sample Data'
    log(`parsing started for '${tableName}'`)

    const containerBuilder = Parser.createContainerBuilder(dataContainer)
    const { isNew, tableBuilder } = containerBuilder.getTable(tableName)

    if (isNew) {
      tableBuilder.setId('mySampleData')
      tableBuilder.addColumnHeaders([
        {
          id: 'id',
          dataType: DataType.String,
        },
        {
          id: 'mag',
          alias: 'magnitude',
          dataType: DataType.Float,
        },
        {
          id: 'title',
          alias: 'title',
          dataType: DataType.String,
        },
        {
          id: 'location',
          dataType: DataType.Geometry,
        },
      ])
    }

    tableBuilder.addRows(
      fetcherResult.features.map((row) => {
        return { id: row.id, mag: row.properties.mag, title: row.properties.title, location: row.geometry }
      })
    )

    return containerBuilder.getDataContainer()
  }
}

Some notes:

You don’t need to write a custom parser for CSV data or for Excel data. The TACO Toolkit contains these parsers. For more information, see Class CsvUtils and Class ExcelUtils in the SDK reference documentation.

Step 7: Build your connector

Enter these commands to build, pack, and run your new connector:

taco build

taco pack

taco run Desktop