Build Bitbucket-Connected Apps in Choreo

The Choreo platform from WS02 is a versatile platform designed for low-code and cloud-native engineering. Developers, even those without advanced coding skills, can leverage Choreo's user-friendly low-code environment to simplify application development. When combined with CData Connect AI, users gain immediate cloud-to-cloud access to Bitbucket data for applications. This article details the process of connecting to Bitbucket using Connect AI and building an application with real-time access to Bitbucket data within Choreo.

CData Connect AI delivers a pure cloud-to-cloud interface for Bitbucket, enabling you to construct applications within Choreo that utilize live Bitbucket data data, all without the need for data replication to a natively supported database. With its built-in optimized data processing capabilities, CData Connect AI efficiently directs all supported SQL operations, including filters and JOINs, directly to Bitbucket, capitalizing on server-side processing to swiftly provide the requested Bitbucket data.

Configure Bitbucket Connectivity for Choreo

Connectivity to Bitbucket from Choreo is made possible through CData Connect AI. To work with Bitbucket data from Choreo, we start by creating and configuring a Bitbucket connection.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Bitbucket" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Bitbucket.

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Bitbucket Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Bitbucket data from Choreo.

Connect to Bitbucket from Choreo

The steps below outline connecting to CData Connect AI from Choreo to create a new application with access to live Bitbucket data.

Creating a Construct

1. Sign in to the Choreo platform. Note: This article is from the perspective of an Anonymous user.
2. Select Components from the left sidebar and then click +Create. Next, choose Manual Trigger and then Start from scratch.
3. Give the manual trigger a Name and Description and click Create.
4. After the trigger is created, click on Edit Code.
5. The Ballerina Low-Code IDE is displayed. Choreo automatically generates a construct in the low-code diagram view. Delete this construct by highlighting it and clicking on the trashcan icon.
6. Click the + icon towards the top of the screen and select Main from the Add Constructs toolbar on the right. In the following Function Configuration form, click Save.

Adding the CData Connect AI Connector

1. Click the + icon between the Start and End ellipses and click Connector.

2. In the Connectors sidebar on the right, search for "CData". Click CData Connect to open the Connector settings pane.

3. In the Connector settings pane, enter the configuration settings:
   • Enter an Endpoint Name for your use. In this example, we use "connectEndpoint".
   • In the User field, enter the email address of the CData Connect AI user, wrapped in quotation marks (for example, "[email protected]").
   • In the Password field, enter the PAT you generated earlier, wrapped in quotation marks (for example, "SampleToken").

4. After clicking Save, the low-code editor appears with the CData Connect AI logo.

Adding a Query Action

1. Click the + icon between the new and end shapes, select Action, and then select our existing connector endpoint.

2. Select query for the connector Operation. There is now an Action pane on the right.

3. Enter a SQL query to retrieve Bitbucket data as the sqlQuery parameter for the query. For example:

   
   			SELECT * FROM Bitbucket1.Bitbucket.Issues LIMIT 10
   		

   • When writing the query, be sure to specify the Connection Name as the catalog and Data Source Name as the schema. For example, Bitbucket1.Bitbucket.
   • These parameters appear on the Connections page of your CData Connect AI dashboard.

Iterating over Bitbucket Data

1. Click the Show Source icon in the top right of the code editor.
2. Add an import statment to import the ballerina/io library:

   		
   		import ballerina/io;
   	

3. Next, add a from statement after the query action to iterate through the results of the SQL query:

		
		check from record{} result in resultStream
		do {
			io:println("Full Issues details: ", result);
		};
	

4. The code for the construct will now look similar to this:

			
			import ballerinax/cdata.connect;
			import ballerinax/cdata.connect.driver as _;
			import ballerina/io;

			public function main() returns error? {
				connect:Client connectEp = check new (user = "connect_cloud_username", password="connect_cloud_pat");

				stream<record {}, error=""?> resultStream =
				connectEp->query(sqlQuery = `SELECT * FROM Bitbucket1.Bitbucket.Issues LIMIT 10`);

				check from record{} result in resultStream
				do {
					io:println("Full Issues details: ", result);
				};
			}
		

5. Click Save to save the action. The diagram should now look similar to this:

Deploying the Program

Once you have added all of your desired actions to your program, follow these steps:

1. Commit and push your final source code in the web editor and sync those changes with the Choreo platform.
2. Click Deploy in the left navigation bar of the Choreo Console.
3. Under Build Area, click Configure & Deploy to deploy your program.
4. When prompted, enter the same CData Connect AI username and password that you used earlier and click Deploy.

You have now created an application with access to live Bitbucket data in Choreo.

Get CData Connect AI

For more information about using Choreo with CData Connect AI, see the CData Connect Ballerina Guide. To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today!