Here is my code. It produces infinite loop, because value of something variable does not change within captured error. Is it supposed to be this way? How can I fix it so that value of something changes to FALSE?
something <- TRUE
counter <- 1
while(something){
print(counter)
tryTest = tryCatch(
{
arima(rep(1,3), order = c(1,0,0))
},
warning = function(w) {
print('this is warning')
print(w)
},
error = function(e) {
something <- FALSE
print('this is error')
print(e)
},
finally = {}
)
counter <- (counter +1)
}
This happens because the environment of something in the outer code is different from the environment of something in your lambda:
function(e) {
something <- FALSE
print('this is error')
print(e)
}
So setting something <- FALSE in your lambda actually sets a different something then in the outer code. To fix this you can either 1) make something a global variable or 2) create an environment to use something in.
1)
assign("something", TRUE, env=globalenv())
to set the variable and
get("something", env=globalenv())
to access the variable.
You can also set something inside your lambda in the same way:
assign("something", FALSE, env=globalenv())
or
2)
First create a new variable:
env=new.env()
Then set and access your variable in a similar way as before:
assign("something", TRUE, env=env)
get("something", env=env)
You can assign something inside your lambda with:
assign("something", FALSE, env=env)
Using env is possible because R copies variables to child environments. However if you set a variable in a child environment (like when you did `somethi
Related
I've read a few other SO questions about tryCatch and cuzzins, as well as the documentation:
Exception handling in R
catching an error and then branching logic
How can I check whether a function call results in a warning?
Problems with Plots in Loop
but I still don't understand.
I'm running a loop and want to skip to next if any of a few kinds of errors occur:
for (i in 1:39487) {
# EXCEPTION HANDLING
this.could.go.wrong <- tryCatch(
attemptsomething(),
error=function(e) next
)
so.could.this <- tryCatch(
doesthisfail(),
error=function(e) next
)
catch.all.errors <- function() { this.could.go.wrong; so.could.this; }
catch.all.errors;
#REAL WORK
useful(i); fun(i); good(i);
} #end for
(by the way, there is no documentation for next that I can find)
When I run this, R honks:
Error in value[[3L]](cond) : no loop for break/next, jumping to top level
What basic point am I missing here? The tryCatch's are clearly within the for loop, so why doesn't R know that?
The key to using tryCatch is realising that it returns an object. If there was an error inside the tryCatch then this object will inherit from class error. You can test for class inheritance with the function inherit.
x <- tryCatch(stop("Error"), error = function(e) e)
class(x)
"simpleError" "error" "condition"
Edit:
What is the meaning of the argument error = function(e) e? This baffled me, and I don't think it's well explained in the documentation. What happens is that this argument catches any error messages that originate in the expression that you are tryCatching. If an error is caught, it gets returned as the value of tryCatch. In the help documentation this is described as a calling handler. The argument e inside error=function(e) is the error message originating in your code.
I come from the old school of procedural programming where using next was a bad thing. So I would rewrite your code something like this. (Note that I removed the next statement inside the tryCatch.):
for (i in 1:39487) {
#ERROR HANDLING
possibleError <- tryCatch(
thing(),
error=function(e) e
)
if(!inherits(possibleError, "error")){
#REAL WORK
useful(i); fun(i); good(i);
}
} #end for
The function next is documented inside ?for`.
If you want to use that instead of having your main working routine inside an if, your code should look something like this:
for (i in 1:39487) {
#ERROR HANDLING
possibleError <- tryCatch(
thing(),
error=function(e) e
)
if(inherits(possibleError, "error")) next
#REAL WORK
useful(i); fun(i); good(i);
} #end for
I found other answers very confusing. Here is an extremely simple implementation for anyone who wants to simply skip to the next loop iteration in the event of an error
for (i in 1:10) {
skip_to_next <- FALSE
# Note that print(b) fails since b doesn't exist
tryCatch(print(b), error = function(e) { skip_to_next <<- TRUE})
if(skip_to_next) { next }
}
for (i in -3:3) {
#ERROR HANDLING
possibleError <- tryCatch({
print(paste("Start Loop ", i ,sep=""))
if(i==0){
stop()
}
}
,
error=function(e) {
e
print(paste("Oops! --> Error in Loop ",i,sep = ""))
}
)
if(inherits(possibleError, "error")) next
print(paste(" End Loop ",i,sep = ""))
}
The only really detailed explanation I have seen can be found here: http://mazamascience.com/WorkingWithData/?p=912
Here is a code clip from that blog post showing how tryCatch works
#!/usr/bin/env Rscript
# tryCatch.r -- experiments with tryCatch
# Get any arguments
arguments <- commandArgs(trailingOnly=TRUE)
a <- arguments[1]
# Define a division function that can issue warnings and errors
myDivide <- function(d, a) {
if (a == 'warning') {
return_value <- 'myDivide warning result'
warning("myDivide warning message")
} else if (a == 'error') {
return_value <- 'myDivide error result'
stop("myDivide error message")
} else {
return_value = d / as.numeric(a)
}
return(return_value)
}
# Evalute the desired series of expressions inside of tryCatch
result <- tryCatch({
b <- 2
c <- b^2
d <- c+2
if (a == 'suppress-warnings') {
e <- suppressWarnings(myDivide(d,a))
} else {
e <- myDivide(d,a) # 6/a
}
f <- e + 100
}, warning = function(war) {
# warning handler picks up where error was generated
print(paste("MY_WARNING: ",war))
b <- "changing 'b' inside the warning handler has no effect"
e <- myDivide(d,0.1) # =60
f <- e + 100
return(f)
}, error = function(err) {
# warning handler picks up where error was generated
print(paste("MY_ERROR: ",err))
b <- "changing 'b' inside the error handler has no effect"
e <- myDivide(d,0.01) # =600
f <- e + 100
return(f)
}, finally = {
print(paste("a =",a))
print(paste("b =",b))
print(paste("c =",c))
print(paste("d =",d))
# NOTE: Finally is evaluated in the context of of the inital
# NOTE: tryCatch block and 'e' will not exist if a warning
# NOTE: or error occurred.
#print(paste("e =",e))
}) # END tryCatch
print(paste("result =",result))
One thing I was missing, which breaking out of for loop when running a function inside a for loop in R makes clear, is this:
next doesn't work inside a function.
You need to send some signal or flag (e.g., Voldemort = TRUE) from inside your function (in my case tryCatch) to the outside.
(this is like modifying a global, public variable inside a local, private function)
Then outside the function, you check to see if the flag was waved (does Voldemort == TRUE). If so you call break or next outside the function.
I need to test package loading operations (for my multiversion package) and know that unloading namespaces and stuff is dangerous work. So I want to run every test in a fresh R session. Running my tests in parallel does not meet this demand since it will reuse slaves, and these get dirty.
So I thought callr::r would help me out. Unfortunately I am again stuck with the minimally documented reporters it seems.
The following is a minimal example. Placed in file test-mytest.R.
test_that('test 1', {
expect_equal(2+2, 5)
})
reporter_in <- testthat::get_reporter()
# -- 1 --
reporter_out <- callr::r(
function(reporter) {
reporter <- testthat::with_reporter(reporter, {
testthat::test_that("test inside", {
testthat::expect_equal('this', 'wont match')
})
})
},
args = list(reporter = reporter_in),
show = TRUE
)
# -- 2 --
testthat::set_reporter(reporter_out)
# -- 3 --
test_that('test 2', {
expect_equal(2+2, 8)
})
I called this test file using:
# to be able to check the outcome, work with a specific reporter
summary <- testthat::SummaryReporter$new()
testthat::test_file('./tests/testthat/test-mytest.R', reporter = summary)
Which seems to do what I want, but when looking at the results...
> summary$end_reporter()
== Failed ===============================================================================================
-- 1. Failure (test-load_b_pick_last_true.R:5:5): test 1 ------------------------------------------------
2 + 2 (`actual`) not equal to 5 (`expected`).
`actual`: 4
`expected`: 5
== DONE =================================================================================================
...it is only the first test that is returned.
How it works:
An ordinary test is executed.
The reporter, currently in use, is obtained (-- 1 --)
callr::r is used to call a testthat block including a test.
Within the call, I tried using set_reporter, but with_reporter is practically identical.
The callr::r call returns the reporter (tried it with get_reporter(), but with_reporter also returns the reporter (invisibly))
Now the returned reporter seems fine, but when setting it as the actual reporter with set_reporter, it seems that it is not overwriting the actual reporter.
Note that at -- 2 --, the reporter_out contains both test outcomes.
Question
I am not really sure what I expect it to do, but in the end I want the results to be added to the original reporter ((summary or) reporter_in that is, if that is not some kind of copy).
One workaround I can think of would be to move the actual test execution outside of the callr::r call, but gather the testcases inside.
I think it is neat, as long as you can place these helper functions (see the elaborate example) in your package, you can write tests with little overhead.
It doesn't answer how to work with the 'reporter' object though...
Simple example:
test_outcome <- callr::r(
function() {
# devtools::load_all()
list(
check1 = mypackage::sum(5,5), # some imaginary exported functions sum and name.
check2 = mypackage::name()
)
}
)
test_that('My test case', {
expect_equal(test_outcome$check1, 10)
expect_equal(test_outcome$check2, 'Siete')
})
Elaborate example
Note that from .add_test to .exp_true are only function definitions which can better be included in your package so they will be available when being loaded with devtools::load_all(). load_all also loads not-exported functions by default.
test_outcome <- callr::r(
function() {
# devtools::load_all()
# Defining helper functions
tst <- list(desc = 'My first test', tests = list())
.add_test <- function(type, A, B) {
# To show at least something about what is actually tested when returning the result, we can add the actual `.exp_...` call to the test.
call <- as.character(sys.call(-1))
tst$tests[[length(tst$tests) + 1]] <<- list(
type = type, a = A, b = B,
# (I couldn't find a better way to create a nice call string)
call = paste0(call[1], '(', paste0(collapse = ', ', call[2:length(call)]), ')'))
}
.exp_error <- function(expr, exp_msg) {
err_msg <- ''
tryCatch({expr}, error = function(err) {
err_msg <<- err$message
})
.add_test('error', err_msg, exp_msg)
}
.exp_match <- function(expr, regex) {
.add_test('match', expr, regex)
}
.exp_equal <- function(expr, ref) {
.add_test('equal', expr, ref)
}
.exp_false <- function(expr) {
.add_test('false', expr, FALSE)
}
.exp_true <- function(expr) {
.add_test('true', expr, TRUE)
}
# Performing the tests
.exp_match('My name is Siete', 'My name is .*')
.exp_equal(mypackage::sum(5,5), 10) # some imaginary exported functions sum and name.
.exp_match(mypackage::name(), 'Siete')
.exp_false('package:testthat' %in% search())
return(tst)
},
show = TRUE)
# Performing the actual testthat tests:
.run_test_batch <- function(test_outcome) {
test_that(test_outcome$desc, {
for (test in test_outcome$tests) {
# 'test' is a list with the fields 'type', 'a', 'b' and 'call'.
# Where 'type' can contain 'match', 'error', 'true', 'false' or 'equal'.
if (test$type == 'equal') {
with(test, expect_equal(a, b, label = call))
} else if (test$type == 'true') {
expect_true( test$a, label = test$call)
} else if (test$type == 'false') {
expect_false(test$a, label = test$call)
} else if (test$type %in% c('match', 'error')) {
with(test, expect_match(a, b, label = call))
}
}
})
}
.run_test_batch(test_outcome)
When moving the functions to your package you would need the following initialize function too.
tst <- new.env(parent = emptyenv())
tst$desc = ''
tst$tests = list()
.initialize_test <- function(desc) {
tst$desc = desc
tst$tests = list()
}
It works as follows:
An empty list is created: tst
By calling .exp_... functions, tests are added to that list
The list with tests is returned by the function in callr::r
Then we loop over the list and execute every test
Is there a way to set options within an environment? Something like
tmp_env = new.env()
within(tmp_env, options(mc.core = 16))
with(tmp_env, {
# run parallel code here
})
I want to switch between using options(mc.core = 16) and options(mc.core = 1) explicitly and don't want to accidentally set off a parallelized computation.
Use a function or other closure (e.g., local()) to set the option, and use on.exit() to guarantee restoration on exit
fun = function() {
old.opt = options(mc.cores=12)
on.exit(options(old.opt))
## do work
}
You could get fancy with something like (based on with.default)
withp = function(expr, cores=4) {
old.opt = options(mc.cores=cores)
on.exit(options(old.opt))
eval(substitute(expr), enclos=parent.frame())
}
and use
withp({
message("hello")
res <- mclapply(1:20, function(i) Sys.getpid())
table(unlist(res))
}, cores=3)
I have to call a function that throws an error if the arguments didn't satisfy many conditions.
The conditions are so complicated that I cannot try to satisfy them 100% of the time (I would have to re-type all the conditions the function checks internally).
Instead, I should just retry calling with different arguments (as many times as necessary to fill my table).
In other languages I can write a catch block around the call.
However, in R tryCatch seems to work differently: you can give code with finally=, but after executing the finally-code the outer function terminates anyway.
Here is a minimal example:
sometimesError <- function() {
if(runif(1)<0.1) stop("err")
return(1)
}
fct <- function() {
theSum <- 0
while(theSum < 20) {
tryCatch( theSum <- theSum + sometimesError() )
}
return(theSum)
}
fct() # this should always evaluate to 20, never throw error
( I have read "Is there a way to source() and continue after an error?", and some other posts but I dont think they apply here. They achieve that the source'd code continues statement-by-statement regardless of error as if it were executing at the top level. I, on the other side, am happy with the called function terminating and it is the caller-code that should continue )
You can pass a function to the error argument of tryCatch to specify what should happen when there is an error. In this case, you could just return 0 when there is an error
fct <- function() {
theSum <- 0
while(theSum < 20) {
theSum <- theSum + tryCatch(sometimesError(), error=function(e) 0)
}
return(theSum)
}
As #rawr mentioned in the comments, you could also replace tryCatch with try in this case.
fct <- function() {
theSum <- 0
while(theSum < 20) {
try(theSum <- theSum + sometimesError(), silent=TRUE)
}
return(theSum)
}
I'm aware of the function on.exit in R, which is great. It runs the expression when the calling function exits, either normally or as the result of an error.
What I'd like is for the expression only to be run if the calling function returns normally, but not in the case of an error. I have multiple points where the function could return normally, and multiple points where it could fail. Is there a way to do this?
myfunction = function() {
...
on.exit( if (just exited normally without error) <something> )
...
if (...) then return( point 1 )
...
if (...) then return( point 2 )
...
if (...) then return( point 3 )
...
return ( point 4 )
}
The whole point of on.exit() is exactly to be run regardless of the exit status. Hence it disregards any error signal. This is afaik equivalent to the finally statement of the tryCatch function.
If you want to run code only on normal exit, simply put it at the end of your code. Yes, you'll have to restructure it a bit using else statements and by creating only 1 exit point, but that's considered good coding practice by some.
Using your example, that would be:
myfunction = function() {
...
if (...) then out <- point 1
...
else if (...) then out <- point 2
...
else if (...) then out <- point 3
...
else out <- point 4
WhateverNeedsToRunBeforeReturning
return(out)
}
Or see the answer of Charles for a nice implementation of this idea using local().
If you insist on using on.exit(), you can gamble on the working of the traceback mechanism to do something like this :
test <- function(x){
x + 12
}
myFun <- function(y){
on.exit({
err <- if( exists(".Traceback")){
nt <- length(.Traceback)
.Traceback[[nt]] == sys.calls()[[1]]
} else {FALSE}
if(!err) print("test")
})
test(y)
}
.Traceback contains the last call stack resulting in an error. You have to check whether the top call in that stack is equal to the current call, and in that case your call very likely threw the last error. So based on that condition you can try to hack yourself a solution I'd never use myself.
Just wrap the args of all your return function calls with the code that you want done. So your example becomes:
foo = function(thing){do something; return(thing)}
myfunction = function() {
...
if (...) then return( foo(point 1) )
...
if (...) then return( foo(point 2) )
...
if (...) then return( foo(point 3) )
...
return ( foo(point 4) )
}
Or just make each then clause into two statements. Using on.exit to lever some code into a number of places is going to cause spooky action-at-a-distance problems and make the baby Dijkstra cry (read Dijkstra's "GOTO considered harmful" paper).
Bit more readable version of my comment on #Joris' answer:
f = function() {
ret = local({
myvar = 42
if (runif(1) < 0.5)
return(2)
stop('oh noes')
}, environment())
# code to run on success...
print(sprintf('myvar is %d', myvar))
ret
}
I guess there is not a clean way yet. I usually create an OK variable at the beginning as FALSE and turn it to TRUE at the end. I prefer on.exit over isolating all my code into a tryCatch.
myfun = function() {
OK=F # the flag "OK" will be FALSE until the function ends OK
conn = my.db.connection.function()
dbBegin(conn)
on.exit({
if(OK) dbCommit(conn) else dbRollback(conn)
dbDisconnect(conn)
})
# ... Your code. You can edit database as a transaction.
# if anything fails in R or in the database a rollback will occur
OK=T # only if the code came to the end everything went ok, so we set the flag OK as TRUE
return(NULL)
}