scoping

Why does the following not give an error? for (int i=0; i<10; ++i) // outer loop { for (int i=0; i<10;++i) // inner loop { //...do something } //...do something else } The way I understand it, variables in braces ({...}) are in scope only within these braces. But the inner loop is inside the braces of the outer loop. So as soon as I declare int i=0 for the inner loop, shouldn't I get an error about multiple definitions? You are actually making a new variable with the same name as another variable. Since they are in different scopes this is allowed, and the variable in the inner scope "owns"

This question comes from a range of other questions that all deal with essentially the same problem. For some strange reason, using a function within another function sometimes fails in the sense that variables defined within the local environment of the first function are not found back in the second function. The classical pattern in pseudo-code : ff <- function(x){ y <- some_value some_function(y) } ff(x) Error in eval(expr, envir, enclos) : object 'y' not found First I thought it had something to do with S4 methods and the scoping in there, but it also happens with other functions. I've

I've been trying to get my head around shallow binding and deep binding, wikipedia doesn't do a good job of explaining it properly. Say I have the following code, what would the output be if the language uses dynamic scoping with a) deep binding b) shallow binding? x: integer := 1 y: integer := 2 procedure add x := x + y procedure second(P:procedure) x:integer := 2 P() procedure first y:integer := 3 second(add) ----main starts here--- first() write_integer(x) Deep binding binds the environment at the time the procedure is passed as an argument Shallow binding binds the environment at the time

EDIT: Looks like this is a very old "bug" or, actually, feature. See, e.g., this mail I am trying to understand the Python scoping rules. More precisely, I thought that I understand them but then I found this code here : x = "xtop" y = "ytop" def func(): x = "xlocal" y = "ylocal" class C: print(x) print(y) y = 1 func() In Python 3.4 the output is: xlocal ytop If I replace the inner class by a function then it reasonably gives UnboundLocalError . Could you explain me why it behaves this strange way with classes and what is the reason for such choice of scoping rules? TL;DR : This behaviour has

I'm trying to gain some memory saving in a C++ program and I want to know if I can use blocks as a scope for variables (as in Perl). Let's say I have a huge object that performs some computations and gives a result, does it makes sense to do: InputType input; ResultType result; { // Block of code MyHugeObject mho; result = mho.superHeavyProcessing(); } /* My other code ... */ Can I expect the object to be destroyed when exiting the block? Yes, you can. The destructor will be called as soon as the variable falls out of scope and it should release the heap-allocated memory. Yes absolutely, and

All the crazy Java scoping rules are making my head spin and the public static void nonsense isn't helping matters. So far all the programming languages I have used either lexical scoping or some approximation of it without any access modifiers, i.e. inner stuff captures outer stuff and has access to the outer stuff as long as the inner stuff exists. So how do I make sense of the scoping rules for inner classes in Java? Do they get access to variables declared in the outer class or is there some weird edge cases I have to worry about because of all the public static private stuff floating

I'd like to give a params argument to a function and then attach it so that I can use a instead of params$a everytime I refer to the list element a. run.simulation<-function(model,params){ attach(params) # # Use elements of params as parameters in a simulation detach(params) } Is there a problem with this? If I have defined a global variable named c and have also defined an element named c of the list "params" , whose value would be used after the attach command? Noah has already pointed out that using attach is a bad idea, even though you see it in some examples and books. There is a way

I am still struggling with R scoping and environments. I would like to be able to construct simple helper functions that get called from my 'main' functions that can directly reference all the variables within those main functions - but I don't want to have to define the helper functions within each of my main functions. helpFunction<-function(){ #can I add a line here to alter the environment of this helper function to that of the calling function? return(importantVar1+1) } mainFunction<-function(importantVar1){ return(helpFunction()) } mainFunction(importantVar1=3) #so this should output 4

I'm trying to use foreach to do multicore computing in R. A <-function(....) { foreach(i=1:10) %dopar% { B() } } then I call function A in the console. The problem is I'm calling a function Posdef inside B that is defined in another script file which I source. I had to put Posdef in the list of export argument of foreach : .export=c("Posdef") . However I get the following error: Error in { : task 3 failed - "could not find function "Posdef"" Why cant R find this defined function? The short answer is that this was a bug in parallel backends such as doSNOW , doParallel and doMPI , but it has