Analyze Bitbucket Data in R via ODBC

Access Bitbucket data with pure R script and standard SQL. You can use the CData ODBC Driver for Bitbucket and the RODBC package to work with remote Bitbucket data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Bitbucket data and visualize Bitbucket data in R.

Install R

You can complement the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open (MRO).

Connect to Bitbucket as an ODBC Data Source

Information for connecting to Bitbucket follows, along with different instructions for configuring a DSN in Windows and Linux environments.

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.

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Windows

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

Linux

If you are installing the CData ODBC Driver for Bitbucket in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.

/etc/odbc.ini

[CData Bitbucket Source]
Driver = CData ODBC Driver for Bitbucket
Description = My Description
Workspace = myworkspaceslug
Schema = Information
InitiateOAuth = GETANDREFRESH

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Load the RODBC Package

To use the driver, download the RODBC package. In RStudio, click Tools -> Install Packages and enter RODBC in the Packages box.

After installing the RODBC package, the following line loads the package:

library(RODBC)

Note: This article uses RODBC version 1.3-12. Using Microsoft R Open, you can test with the same version, using the checkpoint capabilities of Microsoft's MRAN repository. The checkpoint command enables you to install packages from a snapshot of the CRAN repository, hosted on the MRAN repository. The snapshot taken Jan. 1, 2016 contains version 1.3-12.

library(checkpoint)
checkpoint("2016-01-01")

Connect to Bitbucket Data as an ODBC Data Source

You can connect to a DSN in R with the following line:

conn <- odbcConnect("CData Bitbucket Source")

Schema Discovery

The driver models Bitbucket APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

sqlTables(conn)

Execute SQL Queries

Use the sqlQuery function to execute any SQL query supported by the Bitbucket API.

issues <- sqlQuery(conn, "SELECT Title, ContentRaw FROM Issues WHERE Id = '1'", believeNRows=FALSE, rows_at_time=1)

You can view the results in a data viewer window with the following command:

View(issues)

Plot Bitbucket Data

You can now analyze Bitbucket data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2))
barplot(issues$ContentRaw, main="Bitbucket Issues", names.arg = issues$Title, horiz=TRUE)

👁 A basic bar plot. (Salesforce is shown.)