Build Bitbucket-Connected Web Apps with Axios and CData Connect AI

Axios is a JavaScript library that allows developers to make HTTP requests to servers from a web browser or Node.js. When paired with CData Connect AI, you get access to live Bitbucket data for your web apps. This article shows how to connect to Bitbucket and build web apps in Axios with access to live Bitbucket data.

Connect to Bitbucket from Axios

To work with Bitbucket in Axios, we need to connect to Bitbucket from Connect AI, provide user access to the connection, and create a Workspace for the Bitbucket data.

Connect to Bitbucket from Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

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.

Configure Bitbucket Endpoints for Axios

After connecting to Bitbucket, create a workspace for your desired table(s).

1. Navigate to the Workspaces page and click Add to create a new Workspace (or select an existing workspace).
2. Click Add to add new assets to the Workspace.
3. Select the Bitbucket connection (e.g. Bitbucket1) and click Next.
4. Select the table(s) you wish to work with and click Confirm.
5. Make note of the OData Service URL for your workspace, e.g. https://cloud.cdata.com/api/odata/{workspace_name}

With the connection, PAT, and Workspace configured, you are ready to connect to Bitbucket data from Axios.

Connect to Bitbucket Data in Axios Workflows

To establish a connection from Axios to CData Connect AI using the OData protocol, follow these steps.

1. Create a project directory for your web app. For example: ~/connect_cloud/
2. Open a terminal, navigate the the project directory and initialize a node project using the command:

   npm init -y

3. Install the Axios dependency in the project using the following command:

   npm install axios

4. In your project directory, create a file called server.js that contains the following code. Provide your CData Connect AI username (e.g. [email protected]) and PAT (the PAT you created in the prerequisites). You must also provide a query for your data, such as SELECT * FROM Bitbucket1.SCHEMA.Issues.

   server.js code

   
         const axios = require('axios')
   
         const user = '[email protected]'
         const pat = '***********************************';
   
         //Your API endpoint
         const url = 'https://cloud.cdata.com/api/odata/{workspace_name}';
   
         //Your data to be sent in the POST request
         const data = {
         "query":"SELECT * FROM {workspace_name}.SCHEMA.Issues"
         };
   
         axios.post(url, data, {
         auth: {
         username: user,
         password: pat
         }
         })
         .then(response => {
         const rows = response.data.results[0].rows;
         const schema = response.data.results[0].schema;
   
         //Create an array of column names
         const columnNames = schema.map(col => col.columnName);
   
         //Loop through each row and log the column name with its value
         rows.forEach(row => {
         const rowObject = {};
         row.forEach((value, index) => {
         const columnName = columnNames[index];
         rowObject[columnName] = value;
         });
         console.log(rowObject);
         })
         })
         .catch(error => {
         console.error('Error:', error);
         });
       

5. In the terminal, execute the following command to run the server:

   node server.js

   The query results will appear:

   
       { ID: 1, VALUE: -2 }
       { ID: 2, VALUE: 1 }
       { ID: 11, VALUE: null }
       { ID: 3, VALUE: 2 }
       { ID: 4, VALUE: 5 }
       ...

Simplified Access to Bitbucket Data from Cloud Applications

At this point, you have a direct connection to live Bitbucket data from Axios. For more information on gaining simplified access to data from more than 100 SaaS, Big Data, and NoSQL sources in cloud applications like Axios, refer to our Connect AI page.