try {base} | R Documentation

## Try an Expression Allowing Error Recovery

### Description

`try` is a wrapper to run an expression that might fail and allow the user's code to handle error-recovery.

### Usage

    try(expr, silent = FALSE)

### Arguments

`expr` | an R expression to try.
`silent` | logical: should the report of error messages be suppressed?

### Details

`try` evaluates an expression and traps any errors that occur during the evaluation. If an error occurs then the error message is printed to the `stderr` connection unless `options("show.error.messages")` is false or the call includes `silent = TRUE`. The error message is also stored in a buffer where it can be retrieved by `geterrmessage`. (This should not be needed as the value returned in case of an error contains the error message.)

`try` is implemented using `tryCatch`; for programming, instead of `try(expr, silent = TRUE)`, something like `tryCatch(expr, error = function(e) e)` (or other simple error handler functions) may be more efficient and flexible.

### Value

The value of the expression if `expr` is evaluated without error, but an invisible object of class `"try-error"` containing the error message, and the error condition as the `"condition"` attribute, if it fails.

### See Also

`options` for setting error handlers and suppressing the printing of error messages; `geterrmessage` for retrieving the last error message. The underlying `tryCatch` provides more flexible means of catching and handling errors.

`assertCondition` in package tools is related and useful for testing.

### Examples

    ## this example will not work correctly in example(try), but
    ## it does work correctly if pasted in
    options(show.error.messages = FALSE)
    try(log("a"))
    print(.Last.value)
    options(show.error.messages = TRUE)

    ## alternatively,
    print(try(log("a"), TRUE))

    ## run a simulation, keep only the results that worked.
    set.seed(123)
    x <- stats::rnorm(50)
    doit <- function(x)
    {
        x <- sample(x, replace = TRUE)
        if(length(unique(x)) > 30) mean(x)
        else stop("too few unique points")
    }
    ## alternative 1
    res <- lapply(1:100, function(i) try(doit(x), TRUE))
    ## alternative 2
    ## Not run: res <- vector("list", 100)
    for(i in 1:100) res[[i]] <- try(doit(x), TRUE)
    ## End(Not run)
    unlist(res[sapply(res, function(x) !inherits(x, "try-error"))])

[Package base version 3.3.2 Index]