Running R Package Tests Without Building or Installing: Best Practices and Alternatives

Understanding R Package Testing

R is a popular programming language for statistical computing and data visualization. One of the essential features of R is its package system, which allows users to extend the functionality of the language by creating custom packages. However, testing these packages can be a challenge.

What are Package Tests?

Package tests are a crucial component of any R package. They ensure that the package works correctly and does not introduce any new bugs or issues when used in different environments. In this article, we will explore how to run R package tests without building or installing the package first.

The Problem with R CMD Check

R CMD check is a command-line tool that comes with R, which provides a sanity check for packages before they are installed on CRAN (the Comprehensive R Archive Network). This sanity check includes various tests, such as:

Checking the package’s dependencies
Verifying the existence of documentation files
Testing the package’s examples
Running unit tests

However, running these tests requires building and installing the package first. Once the package is installed, R CMD check will automatically run its tests.

Why Can’t We Just Run Tests Without Building or Installing?

There are a few reasons why we can’t simply run tests without building or installing:

Dependency Resolution: When we build a package, R resolves its dependencies and downloads any required packages. However, when we run tests independently, R doesn’t have the same level of knowledge about the package’s dependencies.
Package Structure: Packages are organized in a specific way. Building a package requires that all necessary files (e.g., source code, documentation) be present in their correct locations.

Alternative Approaches

While there is no standard alternative to R CMD check for unit testing provided by base R, we can use various workarounds and tools to run tests independently:

1. Using devtools

devtools is a package that provides a set of utilities for building and testing R packages. One of its key features is the testthat package.

## Installing testthat
install.packages("testthat")

Once installed, we can run tests using:

## Running tests with testthat
library(testthat)
test_dir("tests/")

2. Custom Scripts and Packages

If you expect to develop multiple packages and want to stay independent from non-base-R packages, consider automating the above processes with custom scripts or packages.

For example, we can create a script called run_tests.sh that runs all tests in a package directory:

#!/bin/bash

# Navigate to package directory
cd /path/to/package/directory

# Run tests using testthat
library(testthat)
test_dir("tests/")

We can then schedule this script to run automatically whenever we want to test our packages.

Best Practices for Package Testing

While running tests independently is possible, it’s essential to follow best practices for package testing:

Use testthat: As mentioned earlier, testthat provides a robust set of tools for unit testing R packages.
Organize tests in tests/ directory: This ensures that tests are executed correctly and don’t interfere with other parts of the package.
Keep dependencies up-to-date: Make sure to update your package’s dependencies regularly to avoid issues during testing.

Conclusion

Running R package tests without building or installing the package first is possible, but it requires careful planning and attention to detail. By using tools like testthat and custom scripts, we can automate these processes and stay independent from non-base-R packages. Remember to follow best practices for package testing to ensure that your packages are reliable and maintainable.

Recommended Resources

Note: The above article is a detailed guide to running R package tests without building or installing the package first. It covers various topics, including alternative approaches, best practices for testing, and tools like testthat and custom scripts. The article also includes code examples and references additional resources for further learning.

Last modified on 2023-11-18