Why R in VS Code?

As a leading language for statistical computing and graphics, R has become indispensable in data science workflows. While RStudio remains popular, Visual Studio Code offers superior extensibility and cross-language support. This guide will help you harness VS Code’s modern IDE capabilities for enhanced R development.

Installing Base Software and Extensions

Install R

• Download and install R from official website
• Add R installation path to system environment variables (e.g., C:\Program Files\R\R-4.4.3\bin)
• Verify installation in terminal with R --version (Note: Restart terminals to load new environment variables)

Install VSCode Extensions

1. Open VS Code Extensions Marketplace (Ctrl+Shift+X)
2. Search and install:
   • R (by RStudio team)

Configuring R Extension

Set R Path

• Open VS Code Settings (Ctrl+,), search R: R Path
• Specify R executable path with two options:
  • Check the R installation path in the cmd command line where R
  • Check the R installation path in the R command line R.home()

Install Language Server

• Run in R terminal:
  1	install.packages("languageserver")

• If encountering permission issues:
  • Run R as administrator
  • Or install to user library

Executing R Code

Interactive Execution

1. Create/open .R file
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   # 检查 R 版本 cat("R version:", R.version.string, "\n") # 检查 R 的基本功能：打印一个简单的向量 print(c(1, 2, 3, 4, 5)) # 检查是否能成功加载一个常见包（比如 'ggplot2'） if ("ggplot2" %in% rownames(installed.packages())) { cat("ggplot2 is installed\n") } else { cat("ggplot2 is not installed\n") } # 测试绘制一个简单图形 plot(1:10, main = "Test Plot")

2. Use shortcuts:
   • Ctrl+Enter: Run current line/selection
   • Ctrl+Shift+Enter: Execute entire file
3. View results in integrated terminal

Graphical Output

• Install R package httpgd
  1	install.packages("httpgd")

• Enable R > Plot: Use Httpgd in VS Code settings
• The default drawing style in VS Code will change

Debugging R Code

Prerequisites

• Install debugger package:

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  # OPTION 1: From r-universe.dev: install.packages("vscDebugger", repos = "https://manuelhentschel.r-universe.dev") # OPTION 2: From GitHub: remotes::install_github("ManuelHentschel/vscDebugger")

• Install R Debugger extension

  • The automatically generated launch.json file will contain the R debug configuration
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    { // Use IntelliSense to learn about possible attributes. // Hover to view descriptions of existing attributes. // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 "version": "0.2.0", "configurations": [ { "type": "R-Debugger", "name": "Launch R-Workspace", "request": "launch", "debugMode": "workspace", "workingDirectory": "${workspaceFolder}" }, { "type": "R-Debugger", "name": "Debug R-File", "request": "launch", "debugMode": "file", "workingDirectory": "${workspaceFolder}", "file": "${file}" }, { "type": "R-Debugger", "name": "Debug R-Function", "request": "launch", "debugMode": "function", "workingDirectory": "${workspaceFolder}", "file": "${file}", "mainFunction": "main", "allowGlobalDebugging": false }, { "type": "R-Debugger", "name": "Debug R-Package", "request": "launch", "debugMode": "workspace", "workingDirectory": "${workspaceFolder}", "includePackageScopes": true, "loadPackages": [ "." ] }, { "type": "R-Debugger", "request": "attach", "name": "Attach to R process", "splitOverwrittenOutput": true } ] }

Debugging Workflow

1. Set Breakpoints : Click gutter area to create red markers
2. Start Session : Press F5 or select Run > Start Debugging
3. Debug Controls :
   • F5 : Continue to next breakpoint
   • F10 : Step over
   • F11 : Step into
   • Shift+F11 : Step out
   • Ctrl+Shift+F5: Restart debugging
   • Shift+F5: Stop debugging
4. Inspect debugging info :
   • View values in Variables panel
   • Track call stack in Call Stack panel
   • Execute commands in Debug Console

Debugging Example

Suppose you are debugging the following code (saved as test.R):

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calculate_sum <- function(a, b) {
  result <- a + b
  return(result)
}

x <- 5
y <- 10
total <- calculate_sum(x, y)
print(total)

1. Set a breakpoint at the line result <- a + b .
2. Press F5 to start debugging, and the program will pause at the breakpoint.
3. Press F10 to step over and observe whether the value of the result variable is calculated correctly.

Advanced Debugging Techniques

1. Conditional Breakpoints :
   • Right-click on a breakpoint, select Edit Breakpoint, and enter a condition expression (e.g., a > 5 ).
2. Logpoints :
   • Right-click on the line number, select Add Logpoint , and enter a log message (e.g., The value of variable a is {a} ).
3. Watch Expressions :
   • Add custom expressions in the Watch panel to track their values in real-time.

Additional Optimizations (Optional)

Code Completion and Formatting

• The R Extension plugin provides syntax highlighting and completion by default.
• To format code, install the styler package using install.packages("styler"), and trigger formatting in VS Code with the shortcut Shift+Alt+F.

Terminal Integration

Use radian to replace the default terminal (supports syntax highlighting). Radian is an enhanced R interactive terminal (REPL) designed to replace the default R terminal (such as Rterm or R console), providing a more modern and efficient command-line interaction experience. It is developed based on Python, combining the powerful features of R with the flexibility of the Python ecosystem, making it particularly suitable for users who frequently use the R command line for data analysis, debugging, or development.

Installation and Configuration

1. Prerequisites
   • Python 3.6+ installed and added to system PATH.
   • R installed and added to system PATH.
2. Install radian Install via Python’s package manager pip: pip install radian
3. Verify Installation Enter radian in the terminal, and if you see the colorful prompt r$>, it indicates success.
4. Integrate with VS Code
   • Modify the R terminal path in VS Code to radian (the radian path can be obtained using where radian in the cmd command line).
   • 
   • If you do not wish to use radian, simply remove the path from VS Code settings.