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[Experimental]

try_fetch() establishes handlers for conditions of a given class ("error", "warning", "message", ...). Handlers are functions that take a condition object as argument and are called when the corresponding condition class has been signalled.

A condition handler can:

  • Recover from conditions with a value. In this case the computation of expr is aborted and the recovery value is returned from try_fetch(). Error recovery is useful when you don't want errors to abruptly interrupt your program but resume at the catching site instead.

    # Recover with the value 0
    try_fetch(1 + "", error = function(cnd) 0)
  • Rethrow conditions, e.g. using abort(msg, parent = cnd). See the parent argument of abort(). This is typically done to add information to low-level errors about the high-level context in which they occurred.

    try_fetch(1 + "", error = function(cnd) abort("Failed.", parent = cnd))
  • Inspect conditions, for instance to log data about warnings or errors. In this case, the handler must return the zap() sentinel to instruct try_fetch() to ignore (or zap) that particular handler. The next matching handler is called if any, and errors bubble up to the user if no handler remains.

    log <- NULL
    try_fetch(1 + "", error = function(cnd) {
      log <<- cnd
      zap()
    })

Whereas tryCatch() catches conditions (discarding any running code along the way) and then calls the handler, try_fetch() first calls the handler with the condition on top of the currently running code (fetches it where it stands) and then catches the return value . This is a subtle difference that has implications for the debuggability of your functions. See the comparison with tryCatch() section below.

Usage

try_fetch(expr, ...)

Arguments

expr

An R expression.

...

<dynamic-dots> Named condition handlers. The names specify the condition class for which a handler will be called.

Stack overflows

A stack overflow occurs when a program keeps adding to itself until the stack memory (whose size is very limited unlike heap memory) is exhausted.

# A function that calls itself indefinitely causes stack overflows
f <- function() f()
f()
#> Error: C stack usage  9525680 is too close to the limit

Because memory is very limited when these errors happen, it is not possible to call the handlers on the existing program stack. Instead, error conditions are first caught by try_fetch() and only then error handlers are called. Catching the error interrupts the program up to the try_fetch() context, which allows R to reclaim stack memory.

The practical implication is that error handlers should never assume that the whole call stack is preserved. For instance a trace_back() capture might miss frames.

Note that error handlers are only run for stack overflows on R >= 4.2 (unreleased at the time of writing). On older versions of R the handlers are simply not run. This is because these errors do not inherit from the class stackOverflowError before R 4.2. Consider using tryCatch() instead with critical error handlers that need to capture all errors on old versions of R.

Comparison with tryCatch()

try_fetch() generalises tryCatch() and withCallingHandlers() in a single function. It reproduces the behaviour of both calling and exiting handlers depending the on the return value of the handler. If the handler returns the zap() sentinel, it is taken as a calling handler that declines to recover from a condition. Otherwise, it is taken as an exiting handler which returns a value from the catching site.

The important difference between tryCatch() and try_fetch() is that the program in expr is still fully running when an error handler is called. Because the call stack is preserved, this makes it possible to capture a full backtrace from within the handler, e.g. when rethrowing the error with abort(parent = cnd). Technically, try_fetch() is more similar to (and implemented on top of) base::withCallingHandlers() than tryCatch().