Access Pinterest Data in Anypoint Using SQL

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Pinterest MuleSoft Connector



Create a simple Mule Application that uses HTTP and SQL with the CData Mule Connector for Pinterest to create a JSON endpoint for Pinterest data.

The CData Mule Connector for Pinterest connects Pinterest data to Mule applications enabling read functionality with familiar SQL queries. The Connector allows users to easily create Mule Applications to backup, transform, report, and analyze Pinterest data.

This article demonstrates how to use the CData Mule Connector for Pinterest inside of a Mule project to create a Web interface for Pinterest data. The application created allows you to request Pinterest data using an HTTP request and have the results returned as JSON. The exact same procedure outlined below can be used with any CData Mule Connector to create a Web interface for the 200+ available data sources.

  1. Create a new Mule Project in Anypoint Studio.
  2. Add an HTTP Connector to the Message Flow.
  3. Configure the address for the HTTP Connector.
  4. Add a CData Pinterest Connector to the same flow, after the HTTP Connector.
  5. Create a new Connection (or edit an existing one) and configure the properties to connect to Pinterest (see below). Once the connection is configured, click Test Connection to ensure the connectivity to Pinterest.

    Pinterest authentication is based on the standard OAuth flow. To authenticate, you must initially create an app via the Pinterest developer platform where you can obtain an OAuthClientId, OAuthClientSecret, and CallbackURL.

    Set InitiateOAuth to GETANDREFRESH and set OAuthClientId, OAuthClientSecret, and CallbackURL based on the property values for the app you created.

    See the Help documentation for other OAuth authentication flows.

  6. Configure the CData Pinterest Connector.
    1. Set the Operation to 'Select with Streaming'.
    2. Set the Query type to Dynamic.
    3. Set the SQL query to SELECT * FROM #[message.inboundProperties.'http.query.params'.get('table')] to parse the URL parameter table and use it as the target of the SELECT query. You can customize the query further by referencing other potential URL parameters.
  7. Add a Transform Message Component to the flow.
    1. Map the Payload from the input to the Map in the output.
    2. Set the Output script to the following to convert the payload to JSON:
      %dw 1.0
      %output application/json
      ---
      payload
              
  8. To view your Pinterest data, navigate to the address you configured for the HTTP Connector (localhost:8081 by default) and pass a table name as the table URL parameter: http://localhost:8081?table=Users
    The Users data is available as JSON in your Web browser and any other tools capable of consuming JSON endpoints.

At this point, you have a simple Web interface for working with Pinterest data (as JSON data) in custom apps and a wide variety of BI, reporting, and ETL tools. Download a free, 30 day trial of the Mule Connector for Pinterest and see the CData difference in your Mule Applications today.