Scope of Variables

The scope of a variable is the region of code within which a variable is visible. Variable scoping helps avoid variable naming conflicts. The concept is intuitive: two functions can both have arguments called x without the two x's referring to the same thing. Similarly, there are many other cases where different blocks of code can use the same name without referring to the same thing. The rules for when the same variable name does or doesn't refer to the same thing are called scope rules; this section spells them out in detail.

Certain constructs in the language introduce scope blocks, which are regions of code that are eligible to be the scope of some set of variables. The scope of a variable cannot be an arbitrary set of source lines; instead, it will always line up with one of these blocks. There are two main types of scopes in Julia, global scope and local scope. The latter can be nested. The constructs introducing scope blocks are:

Scope constructs

Construct	Scope type	Scope blocks it may be nested in
module, baremodule	global	global
interactive prompt (REPL)	global	global
(mutable) struct, macro	local	global
for, while, try-catch-finally, let	local	global or local
functions (either syntax, anonymous & do-blocks)	local	global or local
comprehensions, broadcast-fusing	local	global or local

Notably missing from this table are begin blocks and if blocks which do not introduce new scopes. Both types of scopes follow somewhat different rules which will be explained below.

Julia uses lexical scoping, meaning that a function's scope does not inherit from its caller's scope, but from the scope in which the function was defined. For example, in the following code the x inside foo refers to the x in the global scope of its module Bar:

julia> module Bar
           x = 1
           foo() = x
       end;

and not a x in the scope where foo is used:

julia> import .Bar

julia> x = -1;

julia> Bar.foo()
1

Thus lexical scope means that the scope of variables can be inferred from the source code alone.

Global Scope

Each module introduces a new global scope, separate from the global scope of all other modules; there is no all-encompassing global scope. Modules can introduce variables of other modules into their scope through the using or import statements or through qualified access using the dot-notation, i.e. each module is a so-called namespace. Note that variable bindings can only be changed within their global scope and not from an outside module.

julia> module A
           a = 1 # a global in A's scope
       end;

julia> module B
           module C
               c = 2
           end
           b = C.c    # can access the namespace of a nested global scope
                      # through a qualified access
           import ..A # makes module A available
           d = A.a
       end;

julia> module D
           b = a # errors as D's global scope is separate from A's
       end;
ERROR: UndefVarError: a not defined

julia> module E
           import ..A # make module A available
           A.a = 2    # throws below error
       end;
ERROR: cannot assign variables in other modules

Note that the interactive prompt (aka REPL) is in the global scope of the module Main.

Local Scope

A new local scope is introduced by most code blocks (see above table for a complete list). A local scope inherits all the variables from a parent local scope, both for reading and writing. Unlike global scopes, local scopes are not namespaces, thus variables in an inner scope cannot be retrieved from the parent scope through some sort of qualified access.

The following rules and examples pertain to local scopes. A newly introduced variable in a local scope cannot be referenced by a parent scope. For example, here the $z$ is not introduced into the top-level scope:

julia> for i = 1:10
           z = i
       end

julia> z
ERROR: UndefVarError: z not defined

Inner local scopes can, however, update variables in their parent scopes:

julia> for i = 1:1
           z = i
           for j = 1:1
               z = 0
           end
           println(z)
       end
0

Inside a local scope a variable can be forced to be a new local variable using the local keyword:

julia> for i = 1:1
           x = i + 1
           for j = 1:1
               local x = 0
           end
           println(x)
       end
2

Inside a local scope a global variable can be assigned to by using the keyword global:

julia> for i = 1:10
           global z
           z = i
       end

julia> z
10

The location of both the local and global keywords within the scope block is irrelevant. The following is equivalent to the last example (although stylistically worse):

julia> for i = 1:10
           z = i
           global z
       end

julia> z
10

The local and global keywords can also be applied to destructuring assignments, e.g. local x, y = 1, 2. In this case the keyword affects all listed variables.

In a local scope, all variables are inherited from its parent global scope block unless:

• an assignment would result in a modified global variable, or
• a variable is specifically marked with the keyword local.

Thus global variables are only inherited for reading, not for writing:

julia> x, y = 1, 2;

julia> function foo()
           x = 2        # assignment introduces a new local
           return x + y # y refers to the global
       end;

julia> foo()
4

julia> x
1

An explicit global is needed to assign to a global variable:

julia> x = 1;

julia> function foobar()
           global x = 2
       end;

julia> foobar();

julia> x
2

Note that nested functions can modify their parent scope's local variables:

julia> x, y = 1, 2;

julia> function baz()
           x = 2 # introduces a new local
           function bar()
               x = 10       # modifies the parent's x
               return x + y # y is global
           end
           return bar() + x # 12 + 10 (x is modified in call of bar())
       end;

julia> baz()
22

julia> x, y # verify that global x and y are unchanged
(1, 2)

The reason to allow modifying local variables of parent scopes in nested functions is to allow constructing closures which have private state, for instance the state variable in the following example:

julia> let state = 0
           global counter() = (state += 1)
       end;

julia> counter()
1

julia> counter()
2

See also the closures in the examples in the next two sections. A variable, such as x in the first example and state in the second, that is inherited from the enclosing scope by the inner function is sometimes called a captured variable. Captured variables can present performance challenges discussed in performance tips.

The distinction between inheriting global scope and nesting local scope can lead to some slight differences between functions defined in local versus global scopes for variable assignments. Consider the modification of the last example by moving bar to the global scope:

julia> x, y = 1, 2;

julia> function bar()
           x = 10 # local, no longer a closure variable
           return x + y
       end;

julia> function quz()
           x = 2 # local
           return bar() + x # 12 + 2 (x is not modified)
       end;

julia> quz()
14

julia> x, y # verify that global x and y are unchanged
(1, 2)

Note that the above nesting rules do not pertain to type and macro definitions as they can only appear at the global scope. There are special scoping rules concerning the evaluation of default and keyword function arguments which are described in the Function section.

An assignment introducing a variable used inside a function, type or macro definition need not come before its inner usage:

julia> f = y -> y + a;

julia> f(3)
ERROR: UndefVarError: a not defined
Stacktrace:
[...]

julia> a = 1
1

julia> f(3)
4

This behavior may seem slightly odd for a normal variable, but allows for named functions – which are just normal variables holding function objects – to be used before they are defined. This allows functions to be defined in whatever order is intuitive and convenient, rather than forcing bottom up ordering or requiring forward declarations, as long as they are defined by the time they are actually called. As an example, here is an inefficient, mutually recursive way to test if positive integers are even or odd:

julia> even(n) = (n == 0) ? true : odd(n - 1);

julia> odd(n) = (n == 0) ? false : even(n - 1);

julia> even(3)
false

julia> odd(3)
true

Julia provides built-in, efficient functions to test for oddness and evenness called iseven and isodd so the above definitions should only be considered to be examples of scope, not efficient design.

Let Blocks

Unlike assignments to local variables, let statements allocate new variable bindings each time they run. An assignment modifies an existing value location, and let creates new locations. This difference is usually not important, and is only detectable in the case of variables that outlive their scope via closures. The let syntax accepts a comma-separated series of assignments and variable names:

julia> x, y, z = -1, -1, -1;

julia> let x = 1, z
           println("x: $x, y: $y") # x is local variable, y the global
           println("z: $z") # errors as z has not been assigned yet but is local
       end
x: 1, y: -1
ERROR: UndefVarError: z not defined

The assignments are evaluated in order, with each right-hand side evaluated in the scope before the new variable on the left-hand side has been introduced. Therefore it makes sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed:

julia> Fs = Vector{Any}(undef, 2); i = 1;

julia> while i <= 2
           Fs[i] = ()->i
           global i += 1
       end

julia> Fs[1]()
3

julia> Fs[2]()
3

Here we create and store two closures that return variable i. However, it is always the same variable i, so the two closures behave identically. We can use let to create a new binding for i:

julia> Fs = Vector{Any}(undef, 2); i = 1;

julia> while i <= 2
           let i = i
               Fs[i] = ()->i
           end
           global i += 1
       end

julia> Fs[1]()
1

julia> Fs[2]()
2

Since the begin construct does not introduce a new scope, it can be useful to use a zero-argument let to just introduce a new scope block without creating any new bindings:

julia> let
           local x = 1
           let
               local x = 2
           end
           x
       end
1

Since let introduces a new scope block, the inner local x is a different variable than the outer local x.

For Loops and Comprehensions

for loops, while loops, and Comprehensions have the following behavior: any new variables introduced in their body scopes are freshly allocated for each loop iteration, as if the loop body were surrounded by a let block:

julia> Fs = Vector{Any}(undef, 2);

julia> for j = 1:2
           Fs[j] = ()->j
       end

julia> Fs[1]()
1

julia> Fs[2]()
2

A for loop or comprehension iteration variable is always a new variable:

julia> function f()
           i = 0
           for i = 1:3
           end
           return i
       end;

julia> f()
0

However, it is occasionally useful to reuse an existing local variable as the iteration variable. This can be done conveniently by adding the keyword outer:

julia> function f()
           i = 0
           for outer i = 1:3
           end
           return i
       end;

julia> f()
3

Constants

A common use of variables is giving names to specific, unchanging values. Such variables are only assigned once. This intent can be conveyed to the compiler using the const keyword:

julia> const e  = 2.71828182845904523536;

julia> const pi = 3.14159265358979323846;

Multiple variables can be declared in a single const statement:

julia> const a, b = 1, 2
(1, 2)

The const declaration should only be used in global scope on globals. It is difficult for the compiler to optimize code involving global variables, since their values (or even their types) might change at almost any time. If a global variable will not change, adding a const declaration solves this performance problem.

Local constants are quite different. The compiler is able to determine automatically when a local variable is constant, so local constant declarations are not necessary, and in fact are currently not supported.

Special top-level assignments, such as those performed by the function and struct keywords, are constant by default.

Note that const only affects the variable binding; the variable may be bound to a mutable object (such as an array), and that object may still be modified. Additionally when one tries to assign a value to a variable that is declared constant the following scenarios are possible:

• if a new value has a different type than the type of the constant then an error is thrown:

julia> const x = 1.0
1.0

julia> x = 1
ERROR: invalid redefinition of constant x

• if a new value has the same type as the constant then a warning is printed:

julia> const y = 1.0
1.0

julia> y = 2.0
WARNING: redefining constant y
2.0

• if an assignment would not result in the change of variable value no message is given:

julia> const z = 100
100

julia> z = 100
100

The last rule applies for immutable objects even if the variable binding would change, e.g.:

julia> const s1 = "1"
"1"

julia> s2 = "1"
"1"

julia> pointer.([s1, s2], 1)
2-element Array{Ptr{UInt8},1}:
 Ptr{UInt8} @0x00000000132c9638
 Ptr{UInt8} @0x0000000013dd3d18

julia> s1 = s2
"1"

julia> pointer.([s1, s2], 1)
2-element Array{Ptr{UInt8},1}:
 Ptr{UInt8} @0x0000000013dd3d18
 Ptr{UInt8} @0x0000000013dd3d18

However, for mutable objects the warning is printed as expected:

julia> const a = [1]
1-element Array{Int64,1}:
 1

julia> a = [1]
WARNING: redefining constant a
1-element Array{Int64,1}:
 1

Note that although sometimes possible, changing the value of a const variable is strongly discouraged, and is intended only for convenience during interactive use. Changing constants can cause various problems or unexpected behaviors. For instance, if a method references a constant and is already compiled before the constant is changed then it might keep using the old value:

julia> const x = 1
1

julia> f() = x
f (generic function with 1 method)

julia> f()
1

julia> x = 2
WARNING: redefining constant x
2

julia> f()
1