How to Pass Arguments to Function Using substitute() in R

Learn how to create a function wrapper in R that accurately passes code snippets to `reprex::reprex()` by using `substitute()`. Effortlessly capture and evaluate your code with these essential tips!
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How to Pass Arguments to Function Using substitute() in R

When programming in R, especially when working with functions, you may encounter situations where you want to pass code snippets as arguments. This is often complicated by the fact that R utilizes lazy evaluation, which means that arguments are not immediately evaluated. This discussion will focus on how to create a function wrapper that correctly passes code to reprex::reprex() using the substitute() function to achieve expected results.

The Problem Explained

Suppose you want to create a wrapper function that seamlessly passes input code to R's reprex() for further processing. A minimal working example (MWE) involves an internal function, internal_foo(), which uses substitute() to return an expression unaltered. The challenge arises when this function is called indirectly through a wrapper.

Example Code: Understanding the Issue

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Here, the output would show the code block with variable assignments and plot commands as expected. However, when creating a wrapper:

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This results in an output that does not match the expected structure due to the lazy evaluation of x. The deparse() function is not achieving the desired outcome because the original expression is not preserved.

The Solution: Creating an Effective Wrapper

To address this issue, we can modify our wrapper function to accept a variable number of arguments using ... (ellipsis). This way, we can directly feed the expressions to the reprex() function provided by the reprex package.

Revised Wrapper Function

Here is a refined version of your second wrapper that successfully captures and processes the code:

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What This Code Does

The wrapper2 function uses ... to catch multiple arguments without needing to know them in advance.

It calls reprex::reprex() correctly, passing along the functions and data while ensuring they are evaluated as intended.

Expected Results

Upon running the revised code within the default R environment, you would see:

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This indicates that both the inner calls and the wrapper produce identical outputs, effectively capturing and evaluating the original input code.

Conclusion

Passing arguments to functions in R through wrappers can pose challenges due to lazy evaluation. However, by using the substitute() function and carefully constructing your wrapper to take advantage of ellipsis (...), you can ensure your code is processed correctly.

Feel free to utilize the examples above to implement your own wrappers for reprex() or similar functions, and improve your R coding efficiency!