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Connect to live data from ClickUp with the API Driver

Connect to ClickUp

Analyze ClickUp Data in R



Use standard R functions and the development environment of your choice to analyze ClickUp data with the CData JDBC Driver for ClickUp.

Access ClickUp data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for ClickUp and the RJDBC package to work with remote ClickUp 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 ClickUp and visualize ClickUp data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to ClickUp as a JDBC Data Source

You will need the following information to connect to ClickUp as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.api.APIDriver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for ClickUp:

driver <- JDBC(driverClass = "cdata.jdbc.api.APIDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.api.jar", identifier.quote = "'")

You can now use DBI functions to connect to ClickUp and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

Start by setting the Profile connection property to the location of the ClickUp Profile on disk (e.g. C:\profiles\ClickUp.apip). Next, set the ProfileSettings connection property to the connection string for ClickUp (see below).

ClickUp API Profile Settings

In order to authenticate to ClickUp, you'll need to provide your API Key. You can find this token in your user settings, under the Apps section. At the top of the page you have the option to generate a personal token. Set the API Key to your personal token in the ProfileSettings property to connect.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the ClickUp JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.api.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:api:Profile=C:\profiles\ClickUp.apip;ProfileSettings='APIKey=my_personal_token';")

Schema Discovery

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

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the ClickUp API:

tasks <- dbGetQuery(conn,"SELECT Id, Name FROM Tasks WHERE Priority = 'High'")

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

View(tasks)

Plot ClickUp Data

You can now analyze ClickUp 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(tasks$Name, main="ClickUp Tasks", names.arg = tasks$Id, horiz=TRUE)