# Control Flow

Julia provides a variety of control flow constructs:

  * [Compound Expressions](@ref man-compound-expressions): `begin` and `;`.
  * [Conditional Evaluation](@ref man-conditional-evaluation): `if`-`elseif`-`else` and `?:` (ternary operator).
  * [Short-Circuit Evaluation](@ref): logical operators `&&` (“and”) and `||` (“or”), and also chained comparisons.
  * [Repeated Evaluation: Loops](@ref man-loops): `while` and `for`.
  * [Exception Handling](@ref): `try`-`catch`, [`error`](@ref) and [`throw`](@ref).
  * [Tasks (aka Coroutines)](@ref man-tasks): [`yieldto`](@ref).

The first five control flow mechanisms are standard to high-level programming languages. [`Task`](@ref)s
are not so standard: they provide non-local control flow, making it possible to switch between
temporarily-suspended computations. This is a powerful construct: both exception handling and
cooperative multitasking are implemented in Julia using tasks. Everyday programming requires no
direct usage of tasks, but certain problems can be solved much more easily by using tasks.

## [Compound Expressions](@id man-compound-expressions)

Sometimes it is convenient to have a single expression which evaluates several subexpressions
in order, returning the value of the last subexpression as its value. There are two Julia constructs
that accomplish this: `begin` blocks and `;` chains. The value of both compound expression constructs
is that of the last subexpression. Here's an example of a `begin` block:

```jldoctest
julia> z = begin
           x = 1
           y = 2
           x + y
       end
3
```

Since these are fairly small, simple expressions, they could easily be placed onto a single line,
which is where the `;` chain syntax comes in handy:

```jldoctest
julia> z = (x = 1; y = 2; x + y)
3
```

This syntax is particularly useful with the terse single-line function definition form introduced
in [Functions](@ref man-functions). Although it is typical, there is no requirement that `begin` blocks be multiline
or that `;` chains be single-line:

```jldoctest
julia> begin x = 1; y = 2; x + y end
3

julia> (x = 1;
        y = 2;
        x + y)
3
```

## [Conditional Evaluation](@id man-conditional-evaluation)

Conditional evaluation allows portions of code to be evaluated or not evaluated depending on the
value of a boolean expression. Here is the anatomy of the `if`-`elseif`-`else` conditional syntax:

```julia
if x < y
    println("x is less than y")
elseif x > y
    println("x is greater than y")
else
    println("x is equal to y")
end
```

If the condition expression `x < y` is `true`, then the corresponding block is evaluated; otherwise
the condition expression `x > y` is evaluated, and if it is `true`, the corresponding block is
evaluated; if neither expression is true, the `else` block is evaluated. Here it is in action:

```jldoctest
julia> function test(x, y)
           if x < y
               println("x is less than y")
           elseif x > y
               println("x is greater than y")
           else
               println("x is equal to y")
           end
       end
test (generic function with 1 method)

julia> test(1, 2)
x is less than y

julia> test(2, 1)
x is greater than y

julia> test(1, 1)
x is equal to y
```

The `elseif` and `else` blocks are optional, and as many `elseif` blocks as desired can be used.
The condition expressions in the `if`-`elseif`-`else` construct are evaluated until the first
one evaluates to `true`, after which the associated block is evaluated, and no further condition
expressions or blocks are evaluated.

`if` blocks are "leaky", i.e. they do not introduce a local scope. This means that new variables
defined inside the `if` clauses can be used after the `if` block, even if they weren't defined
before. So, we could have defined the `test` function above as

```jldoctest
julia> function test(x,y)
           if x < y
               relation = "less than"
           elseif x == y
               relation = "equal to"
           else
               relation = "greater than"
           end
           println("x is ", relation, " y.")
       end
test (generic function with 1 method)

julia> test(2, 1)
x is greater than y.
```

The variable `relation` is declared inside the `if` block, but used outside. However, when depending
on this behavior, make sure all possible code paths define a value for the variable. The following
change to the above function results in a runtime error

```jldoctest; filter = r"Stacktrace:(\n \[[0-9]+\].*)*"
julia> function test(x,y)
           if x < y
               relation = "less than"
           elseif x == y
               relation = "equal to"
           end
           println("x is ", relation, " y.")
       end
test (generic function with 1 method)

julia> test(1,2)
x is less than y.

julia> test(2,1)
ERROR: UndefVarError: `relation` not defined in local scope
Stacktrace:
 [1] test(::Int64, ::Int64) at ./none:7
```

`if` blocks also return a value, which may seem unintuitive to users coming from many other languages.
This value is simply the return value of the last executed statement in the branch that was chosen,
so

```jldoctest
julia> x = 3
3

julia> if x > 0
           "positive!"
       else
           "negative..."
       end
"positive!"
```

Note that very short conditional statements (one-liners) are frequently expressed using Short-Circuit
Evaluation in Julia, as outlined in the next section.

Unlike C, MATLAB, Perl, Python, and Ruby -- but like Java, and a few other stricter, typed languages
-- it is an error if the value of a conditional expression is anything but `true` or `false`:

```jldoctest
julia> if 1
           println("true")
       end
ERROR: TypeError: non-boolean (Int64) used in boolean context
```

This error indicates that the conditional was of the wrong type: [`Int64`](@ref) rather
than the required [`Bool`](@ref).

The so-called "ternary operator", `?:`, is closely related to the `if`-`elseif`-`else` syntax,
but is used where a conditional choice between single expression values is required, as opposed
to conditional execution of longer blocks of code. It gets its name from being the only operator
in most languages taking three operands:

```julia
a ? b : c
```

The expression `a`, before the `?`, is a condition expression, and the ternary operation evaluates
the expression `b`, before the `:`, if the condition `a` is `true` or the expression `c`, after
the `:`, if it is `false`. Note that the spaces around `?` and `:` are mandatory: an expression
like `a?b:c` is not a valid ternary expression (but a newline is acceptable after both the `?` and
the `:`).

The easiest way to understand this behavior is to see an example. In the previous example, the
`println` call is shared by all three branches: the only real choice is which literal string to
print. This could be written more concisely using the ternary operator. For the sake of clarity,
let's try a two-way version first:

```jldoctest
julia> x = 1; y = 2;

julia> println(x < y ? "less than" : "not less than")
less than

julia> x = 1; y = 0;

julia> println(x < y ? "less than" : "not less than")
not less than
```

If the expression `x < y` is true, the entire ternary operator expression evaluates to the string
`"less than"` and otherwise it evaluates to the string `"not less than"`. The original three-way
example requires chaining multiple uses of the ternary operator together:

```jldoctest
julia> test(x, y) = println(x < y ? "x is less than y"    :
                            x > y ? "x is greater than y" : "x is equal to y")
test (generic function with 1 method)

julia> test(1, 2)
x is less than y

julia> test(2, 1)
x is greater than y

julia> test(1, 1)
x is equal to y
```

To facilitate chaining, the operator associates from right to left.

It is significant that like `if`-`elseif`-`else`, the expressions before and after the `:` are
only evaluated if the condition expression evaluates to `true` or `false`, respectively:

```jldoctest
julia> v(x) = (println(x); x)
v (generic function with 1 method)

julia> 1 < 2 ? v("yes") : v("no")
yes
"yes"

julia> 1 > 2 ? v("yes") : v("no")
no
"no"
```

## Short-Circuit Evaluation

The `&&` and `||` operators in Julia correspond to logical “and” and “or” operations, respectively,
and are typically used for this purpose. However, they have an additional property of *short-circuit*
evaluation: they don't necessarily evaluate their second argument, as explained below.  (There
are also bitwise `&` and `|` operators that can be used as logical “and” and “or” *without*
short-circuit behavior, but beware that `&` and `|` have higher precedence than `&&` and `||` for evaluation order.)

Short-circuit evaluation is quite similar to conditional evaluation. The behavior is found in
most imperative programming languages having the `&&` and `||` boolean operators: in a series
of boolean expressions connected by these operators, only the minimum number of expressions are
evaluated as are necessary to determine the final boolean value of the entire chain. Some
languages (like Python) refer to them as `and` (`&&`) and `or` (`||`). Explicitly, this means
that:

  * In the expression `a && b`, the subexpression `b` is only evaluated if `a` evaluates to `true`.
  * In the expression `a || b`, the subexpression `b` is only evaluated if `a` evaluates to `false`.

The reasoning is that `a && b` must be `false` if `a` is `false`, regardless of the value of
`b`, and likewise, the value of `a || b` must be true if `a` is `true`, regardless of the value
of `b`. Both `&&` and `||` associate to the right, but `&&` has higher precedence than `||` does.
It's easy to experiment with this behavior:

```jldoctest tandf
julia> t(x) = (println(x); true)
t (generic function with 1 method)

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

julia> t(1) && t(2)
1
2
true

julia> t(1) && f(2)
1
2
false

julia> f(1) && t(2)
1
false

julia> f(1) && f(2)
1
false

julia> t(1) || t(2)
1
true

julia> t(1) || f(2)
1
true

julia> f(1) || t(2)
1
2
true

julia> f(1) || f(2)
1
2
false
```

You can easily experiment in the same way with the associativity and precedence of various combinations
of `&&` and `||` operators.

This behavior is frequently used in Julia to form an alternative to very short `if` statements.
Instead of `if <cond> <statement> end`, one can write `<cond> && <statement>` (which could be
read as: `<cond>` *and then* `<statement>`). Similarly, instead of `if ! <cond> <statement> end`,
one can write `<cond> || <statement>` (which could be read as: `<cond>` *or else* `<statement>`).

For example, a recursive factorial routine could be defined like this:

```jldoctest; filter = r"Stacktrace:(\n \[[0-9]+\].*)*"
julia> function fact(n::Int)
           n >= 0 || error("n must be non-negative")
           n == 0 && return 1
           n * fact(n-1)
       end
fact (generic function with 1 method)

julia> fact(5)
120

julia> fact(0)
1

julia> fact(-1)
ERROR: n must be non-negative
Stacktrace:
 [1] error at ./error.jl:33 [inlined]
 [2] fact(::Int64) at ./none:2
 [3] top-level scope
```

Boolean operations *without* short-circuit evaluation can be done with the bitwise boolean operators
introduced in [Mathematical Operations and Elementary Functions](@ref): `&` and `|`. These are
normal functions, which happen to support infix operator syntax, but always evaluate their arguments:

```jldoctest tandf
julia> f(1) & t(2)
1
2
false

julia> t(1) | t(2)
1
2
true
```

Just like condition expressions used in `if`, `elseif` or the ternary operator, the operands of
`&&` or `||` must be boolean values (`true` or `false`). Using a non-boolean value anywhere except
for the last entry in a conditional chain is an error:

```jldoctest
julia> 1 && true
ERROR: TypeError: non-boolean (Int64) used in boolean context
```

On the other hand, any type of expression can be used at the end of a conditional chain. It will
be evaluated and returned depending on the preceding conditionals:

```jldoctest
julia> true && (x = (1, 2, 3))
(1, 2, 3)

julia> false && (x = (1, 2, 3))
false
```

## [Repeated Evaluation: Loops](@id man-loops)

There are two constructs for repeated evaluation of expressions: the `while` loop and the `for`
loop. Here is an example of a `while` loop:

```jldoctest
julia> i = 1;

julia> while i <= 3
           println(i)
           global i += 1
       end
1
2
3
```

The `while` loop evaluates the condition expression (`i <= 3` in this case), and as long as it remains
`true`, keeps also evaluating the body of the `while` loop. If the condition expression is `false`
when the `while` loop is first reached, the body is never evaluated.

The `for` loop makes common repeated evaluation idioms easier to write. Since counting up and
down like the above `while` loop does is so common, it can be expressed more concisely with a
`for` loop:

```jldoctest
julia> for i = 1:3
           println(i)
       end
1
2
3
```

Here the `1:3` is a [`range`](@ref) object, representing the sequence of numbers 1, 2, 3. The `for`
loop iterates through these values, assigning each one in turn to the variable `i`.
In general, the `for` construct can loop over any "iterable" object (or "container"), from a  range like `1:3` or `1:3:13` (a [`StepRange`](@ref) indicating every 3rd integer 1, 4, 7, …, 13) to more generic containers like arrays, including [iterators defined by user code](@ref man-interface-iteration)
or external packages. For containers other than ranges, the alternative
(but fully equivalent) keyword `in` or `∈` is typically used instead of `=`, since it makes
the code read more clearly:

```jldoctest
julia> for i in [1,4,0]
           println(i)
       end
1
4
0

julia> for s ∈ ["foo","bar","baz"]
           println(s)
       end
foo
bar
baz
```

Various types of iterable containers will be introduced and discussed in later sections of the
manual (see, e.g., [Multi-dimensional Arrays](@ref man-multi-dim-arrays)).

One rather
important distinction between the previous `while` loop form and the `for` loop form is the scope
during which the variable is visible. A `for` loop always introduces a new iteration variable in
its body, regardless of whether a variable of the same name exists in the enclosing scope.
This implies that on the one hand `i` need not be declared before the loop. On the other hand it
will not be visible outside the loop, nor will an outside variable of the same name be affected.
You'll either need a new interactive session instance or a different variable
name to test this:

```jldoctest
julia> for j = 1:3
           println(j)
       end
1
2
3

julia> j
ERROR: UndefVarError: `j` not defined in `Main`
```

```jldoctest
julia> j = 0;

julia> for j = 1:3
           println(j)
       end
1
2
3

julia> j
0
```

Use `for outer` to modify the latter behavior and reuse an existing local variable.

See [Scope of Variables](@ref scope-of-variables) for a detailed explanation of variable scope, [`outer`](@ref), and how it works in
Julia.

It is sometimes convenient to terminate the repetition of a `while` before the test condition
is falsified or stop iterating in a `for` loop before the end of the iterable object is reached.
This can be accomplished with the `break` keyword:

```jldoctest
julia> i = 1;

julia> while true
           println(i)
           if i >= 3
               break
           end
           global i += 1
       end
1
2
3

julia> for j = 1:1000
           println(j)
           if j >= 3
               break
           end
       end
1
2
3
```

Without the `break` keyword, the above `while` loop would never terminate on its own, and the `for` loop would iterate up to 1000. These loops are both exited early by using `break`.

In other circumstances, it is handy to be able to stop an iteration and move on to the next one
immediately. The `continue` keyword accomplishes this:

```jldoctest
julia> for i = 1:10
           if i % 3 != 0
               continue
           end
           println(i)
       end
3
6
9
```

This is a somewhat contrived example since we could produce the same behavior more clearly by
negating the condition and placing the `println` call inside the `if` block. In realistic usage
there is more code to be evaluated after the `continue`, and often there are multiple points from
which one calls `continue`.

Multiple nested `for` loops can be combined into a single outer loop, forming the cartesian product
of its iterables:

```jldoctest
julia> for i = 1:2, j = 3:4
           println((i, j))
       end
(1, 3)
(1, 4)
(2, 3)
(2, 4)
```

With this syntax, iterables may still refer to outer loop variables; e.g. `for i = 1:n, j = 1:i`
is valid.
However a `break` statement inside such a loop exits the entire nest of loops, not just the inner one.
Both variables (`i` and `j`) are set to their current iteration values each time the inner loop runs.
Therefore, assignments to `i` will not be visible to subsequent iterations:

```jldoctest
julia> for i = 1:2, j = 3:4
           println((i, j))
           i = 0
       end
(1, 3)
(1, 4)
(2, 3)
(2, 4)
```

If this example were rewritten to use a `for` keyword for each variable, then the output would
be different: the second and fourth values would contain `0`.

Multiple containers can be iterated over at the same time in a single `for` loop using [`zip`](@ref):

```jldoctest
julia> for (j, k) in zip([1 2 3], [4 5 6 7])
           println((j,k))
       end
(1, 4)
(2, 5)
(3, 6)
```

Using [`zip`](@ref) will create an iterator that is a tuple containing the subiterators for the containers passed to it.
The `zip` iterator will iterate over all subiterators in order, choosing the ``i``th element of each subiterator in the
``i``th iteration of the `for` loop. Once any of the subiterators run out, the `for` loop will stop.

## Exception Handling

When an unexpected condition occurs, a function may be unable to return a reasonable value to
its caller. In such cases, it may be best for the exceptional condition to either terminate the
program while printing a diagnostic error message, or if the programmer has provided code to handle
such exceptional circumstances then allow that code to take the appropriate action.

### Built-in `Exception`s

`Exception`s are thrown when an unexpected condition has occurred. The built-in `Exception`s listed
below all interrupt the normal flow of control.

| `Exception`                   |
|:----------------------------- |
| [`ArgumentError`](@ref)       |
| [`BoundsError`](@ref)         |
| [`CompositeException`](@ref)  |
| [`DimensionMismatch`](@ref)   |
| [`DivideError`](@ref)         |
| [`DomainError`](@ref)         |
| [`EOFError`](@ref)            |
| [`ErrorException`](@ref)      |
| [`FieldError`](@ref)          |
| [`InexactError`](@ref)        |
| [`InitError`](@ref)           |
| [`InterruptException`](@ref)  |
| `InvalidStateException`       |
| [`KeyError`](@ref)            |
| [`LoadError`](@ref)           |
| [`OutOfMemoryError`](@ref)    |
| [`ReadOnlyMemoryError`](@ref) |
| [`RemoteException`](@ref)     |
| [`MethodError`](@ref)         |
| [`OverflowError`](@ref)       |
| [`Meta.ParseError`](@ref)     |
| [`SystemError`](@ref)         |
| [`TypeError`](@ref)           |
| [`UndefRefError`](@ref)       |
| [`UndefVarError`](@ref)       |
| [`StringIndexError`](@ref)    |

For example, the [`sqrt`](@ref) function throws a [`DomainError`](@ref) if applied to a negative
real value:

```jldoctest
julia> sqrt(-1)
ERROR: DomainError with -1.0:
sqrt was called with a negative real argument but will only return a complex result if called with a complex argument. Try sqrt(Complex(x)).
Stacktrace:
[...]
```

You may define your own exceptions in the following way:

```jldoctest
julia> struct MyCustomException <: Exception end
```

### The [`throw`](@ref) function

Exceptions can be created explicitly with [`throw`](@ref). For example, a function defined only
for non-negative numbers could be written to [`throw`](@ref) a [`DomainError`](@ref) if the argument
is negative:

```jldoctest; filter = r"Stacktrace:(\n \[[0-9]+\].*)*"
julia> f(x) = x>=0 ? exp(-x) : throw(DomainError(x, "argument must be non-negative"))
f (generic function with 1 method)

julia> f(1)
0.36787944117144233

julia> f(-1)
ERROR: DomainError with -1:
argument must be non-negative
Stacktrace:
 [1] f(::Int64) at ./none:1
```

Note that [`DomainError`](@ref) without parentheses is not an exception, but a type of exception.
It needs to be called to obtain an `Exception` object:

```jldoctest
julia> typeof(DomainError(nothing)) <: Exception
true

julia> typeof(DomainError) <: Exception
false
```

Additionally, some exception types take one or more arguments that are used for error reporting:

```jldoctest
julia> throw(UndefVarError(:x))
ERROR: UndefVarError: `x` not defined
```

This mechanism can be implemented easily by custom exception types following the way [`UndefVarError`](@ref)
is written:

```jldoctest
julia> struct MyUndefVarError <: Exception
           var::Symbol
       end

julia> Base.showerror(io::IO, e::MyUndefVarError) = print(io, e.var, " not defined")
```

!!! note
    When writing an error message, it is preferred to make the first word lowercase. For example,

    `size(A) == size(B) || throw(DimensionMismatch("size of A not equal to size of B"))`

    is preferred over

    `size(A) == size(B) || throw(DimensionMismatch("Size of A not equal to size of B"))`.

    However, sometimes it makes sense to keep the uppercase first letter, for instance if an argument
    to a function is a capital letter:

    `size(A,1) == size(B,2) || throw(DimensionMismatch("A has first dimension..."))`.

### Errors

The [`error`](@ref) function is used to produce an [`ErrorException`](@ref) that interrupts
the normal flow of control.

Suppose we want to stop execution immediately if the square root of a negative number is taken.
To do this, we can define a fussy version of the [`sqrt`](@ref) function that raises an error
if its argument is negative:

```jldoctest fussy_sqrt; filter = r"Stacktrace:(\n \[[0-9]+\].*)*"
julia> fussy_sqrt(x) = x >= 0 ? sqrt(x) : error("negative x not allowed")
fussy_sqrt (generic function with 1 method)

julia> fussy_sqrt(2)
1.4142135623730951

julia> fussy_sqrt(-1)
ERROR: negative x not allowed
Stacktrace:
 [1] error at ./error.jl:33 [inlined]
 [2] fussy_sqrt(::Int64) at ./none:1
 [3] top-level scope
```

If `fussy_sqrt` is called with a negative value from another function, instead of trying to continue
execution of the calling function, it returns immediately, displaying the error message in the
interactive session:

```jldoctest fussy_sqrt; filter = r"Stacktrace:(\n \[[0-9]+\].*)*"
julia> function verbose_fussy_sqrt(x)
           println("before fussy_sqrt")
           r = fussy_sqrt(x)
           println("after fussy_sqrt")
           return r
       end
verbose_fussy_sqrt (generic function with 1 method)

julia> verbose_fussy_sqrt(2)
before fussy_sqrt
after fussy_sqrt
1.4142135623730951

julia> verbose_fussy_sqrt(-1)
before fussy_sqrt
ERROR: negative x not allowed
Stacktrace:
 [1] error at ./error.jl:33 [inlined]
 [2] fussy_sqrt at ./none:1 [inlined]
 [3] verbose_fussy_sqrt(::Int64) at ./none:3
 [4] top-level scope
```

### The `try/catch` statement

The `try/catch` statement allows for `Exception`s to be tested for, and for the
graceful handling of things that may ordinarily break your application. For example,
in the below code the function for square root would normally throw an exception. By
placing a `try/catch` block around it we can mitigate that here. You may choose how
you wish to handle this exception, whether logging it, return a placeholder value or
as in the case below where we just printed out a statement. One thing to think about
when deciding how to handle unexpected situations is that using a `try/catch` block is
much slower than using conditional branching to handle those situations.
Below there are more examples of handling exceptions with a `try/catch` block:

```jldoctest
julia> try
           sqrt("ten")
       catch e
           println("You should have entered a numeric value")
       end
You should have entered a numeric value
```

`try/catch` statements also allow the `Exception` to be saved in a variable. The following
contrived example calculates the square root of the second element of `x` if `x`
is indexable, otherwise assumes `x` is a real number and returns its square root:

```jldoctest
julia> sqrt_second(x) = try
           sqrt(x[2])
       catch y
           if isa(y, DomainError)
               sqrt(complex(x[2], 0))
           elseif isa(y, BoundsError)
               sqrt(x)
           else
               rethrow() # ensure other exceptions can bubble up the call stack
           end
       end
sqrt_second (generic function with 1 method)

julia> sqrt_second([1 4])
2.0

julia> sqrt_second([1 -4])
0.0 + 2.0im

julia> sqrt_second(9)
3.0

julia> sqrt_second(-9)
ERROR: DomainError with -9.0:
sqrt was called with a negative real argument but will only return a complex result if called with a complex argument. Try sqrt(Complex(x)).
Stacktrace:
[...]

julia> sqrt_second([1 nothing])
ERROR: MethodError: no method matching sqrt(::Nothing)
The function `sqrt` exists, but no method is defined for this combination of argument types.
[...]
```

Use [`rethrow`](@ref) as above to continue unwinding the stack with the original exception so that
higher-level exception handlers can deal with the exception. When filtering by exception type
as above, it is often important to include `else rethrow()` so that other types of exceptions
are not hidden from the caller.

Note that the symbol following `catch` will always be interpreted as a name for the exception,
so care is needed when writing `try/catch` expressions on a single line. The following code will
*not* work to return the value of `x` in case of an error:

```julia
try bad() catch x end
```

Instead, use a semicolon or insert a line break after `catch`:

```julia
try bad() catch; x end

try bad()
catch
    x
end
```

The power of the `try/catch` construct lies in the ability to unwind a deeply nested computation
immediately to a much higher level in the stack of calling functions. There are situations where
no error has occurred, but the ability to unwind the stack and pass a value to a higher level
is desirable. Julia provides the [`backtrace`](@ref), [`catch_backtrace`](@ref)
and [`current_exceptions`](@ref) functions for more advanced error handling.

### `else` Clauses

!!! compat "Julia 1.8"
    This functionality requires at least Julia 1.8.

In some cases, one may not only want to appropriately handle the error case, but also want to run
some code only if the `try` block succeeds. For this, an `else` clause can be specified after the
`catch` block that is run whenever no error was thrown previously. The advantage over including
this code in the `try` block instead is that any further errors don't get silently caught by the
`catch` clause.

```julia
local x
try
    x = read("file", String)
catch
    # handle read errors
else
    # do something with x
end
```

!!! note
    The `try`, `catch`, `else`, and `finally` clauses each introduce their own scope blocks, so if
    a variable is only defined in the `try` block, it can not be accessed by the `else` or `finally`
    clause:
    ```jldoctest
    julia> try
               foo = 1
           catch
           else
               foo
           end
    ERROR: UndefVarError: `foo` not defined in `Main`
    Suggestion: check for spelling errors or missing imports.
    ```
    Use the [`local` keyword](@ref local-scope) outside the `try` block to make the variable
    accessible from anywhere within the outer scope.

### `finally` Clauses

In code that performs state changes or uses resources like files, there is typically clean-up
work (such as closing files) that needs to be done when the code is finished. Exceptions potentially
complicate this task, since they can cause a block of code to exit before reaching its normal
end. The `finally` keyword provides a way to run some code when a given block of code exits, regardless
of how it exits.

For example, here is how we can guarantee that an opened file is closed:

```julia
f = open("file")
try
    # operate on file f
finally
    close(f)
end
```

When control leaves the `try` block (for example due to a `return`, or just finishing normally),
`close(f)` will be executed. If the `try` block exits due to an exception, the exception will
continue propagating. A `catch` block may be combined with `try` and `finally` as well. In this
case the `finally` block will run after `catch` has handled the error.

When evaluating a `try/catch/else/finally` expression, the value of the entire
expression is the value of the last block executed, excluding the `finally`
block. For example:

```jldoctest
julia> try
           1
       finally
           2
       end
1

julia> try
           error("")
       catch
           1
       else
           2
       finally
           3
       end
1

julia> try
           0
       catch
           1
       else
           2
       finally
           3
       end
2
```

## [Tasks (aka Coroutines)](@id man-tasks)

Tasks are a control flow feature that allows computations to be suspended and resumed in a flexible
manner. We mention them here only for completeness; for a full discussion see
[Asynchronous Programming](@ref man-asynchronous).
