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Combine startsWith
and endsWith
with R’s pipe
In my first post, startsWith
and endsWith
were presented. In combination with R’s pipe operator, we can improve the readability even further.
w <- "Hello World!" w |> startsWith("Hell") [1] TRUE w |> endsWith("!") [1] TRUE
Proceeding with the example of the initial post, let’s see this in context of control flow.
tell_file_type <- function(filename) { if (filename |> endsWith("txt")) print("A text file.") excel_endings <- c("xlsx", "xls") if (any(filename |> endsWith(excel_endings))) print("An Excel file.") } tell_file_type("A.xlsx") [1] "An Excel file."
%in% and %not in%
The %in%
operator is commonly used. To improve the readability of something like
existing_names <- c("Lisa", "Bob") name <- "Peter" hasNewName = !(name %in% existing_names)
you can always define your own operators.
`%not in%` <- Negate(`%in%`) hasNewName = name %not in% existing_names
Obviously, the readability also depends on the choice of proper variable names. My general take on this: don’t shy away from longish variable names, if it improves code readability.
In this context, it is often useful to assign boolean values to variables. For example, instead of
if (abs_error < 1e-8) { # ... }
you should do
hasConverged <- abs_error < 1e-8 if (hasConverged) { # ... }
That is, it is ok to add redundancies in your code if it improves readability.
Sometimes, it is not immediately clear from the naming of base R functions, what they do. Of course, you are free to redefine them with a proper name.
equals_pattern = function(x, pattern, ...) grepl(pattern, x, ...) x <- "Peter" x |> equals_pattern("^P") [1] TRUE
Lastly, let’s combine all of the above.
x |> equals_pattern("^P") && x |> startsWith("z") && x %not in% existing_names [1] FALSE
That’s it for now. Let me know in the comments how you think about this topic or maybe you have another good example of readable code.
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