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Dispatch: As explained in Methods, you can have different versions ('methods') of a function for different argument types, in which case the argument types are used to determine which implementation is called for which arguments.(There are rare exceptions when an argument-type declaration can trigger additional compiler specializations see: Be aware of when Julia avoids specializing.) The most common reasons to declare argument types in Julia are, instead: For example, calling fib(1) will trigger the compilation of specialized version of fib optimized specifically for Int arguments, which is then re-used if fib(7) or fib(15) are called. For example, the following function computes Fibonacci numbers recursively: fib(n::Integer) = n ≤ 2 ? one(n) : fib(n-1) + fib(n-2)Īnd the ::Integer specification means that it will only be callable when n is a subtype of the abstract Integer type.Īrgument-type declarations normally have no impact on performance: regardless of what argument types (if any) are declared, Julia compiles a specialized version of the function for the actual argument types passed by the caller. You can declare the types of function arguments by appending ::TypeName to the argument name, as usual for Type Declarations in Julia. This is the same behavior found in Scheme, most Lisps, Python, Ruby and Perl, among other dynamic languages. Modifications to mutable values (such as Arrays) made within a function will be visible to the caller. Function arguments themselves act as new variable bindings (new locations that can refer to values), but the values they refer to are identical to the passed values. Julia function arguments follow a convention sometimes called 'pass-by-sharing', which means that values are not copied when they are passed to functions. Without parentheses, the expression f refers to the function object, and can be passed around like any other value: julia> g = f Īs with variables, Unicode can also be used for function names: julia> ∑(x,y) = x + y The short function syntax is accordingly quite idiomatic, considerably reducing both typing and visual noise.Ī function is called using the traditional parenthesis syntax: julia> f(2,3) Short, simple function definitions are common in Julia. In the assignment form, the body of the function must be a single expression, although it can be a compound expression (see Compound Expressions). The traditional function declaration syntax demonstrated above is equivalent to the following compact 'assignment form': julia> f(x,y) = x + y

There is a second, more terse syntax for defining a function in Julia. This function accepts two arguments x and y and returns the value of the last expression evaluated, which is x + y. The basic syntax for defining functions in Julia is: julia> function f(x,y) Julia functions are not pure mathematical functions, because they can alter and be affected by the global state of the program. In Julia, a function is an object that maps a tuple of argument values to a return value.

Instrumenting Julia with DTrace, and bpftrace.

Reporting and analyzing crashes (segfaults).

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Static analyzer annotations for GC correctness in C code.

Proper maintenance and care of multi-threading locks.

printf() and stdio in the Julia runtime.

Talking to the compiler (the :meta mechanism).

High-level Overview of the Native-Code Generation Process.Noteworthy Differences from other Languages.Multi-processing and Distributed Computing.Destructuring Assignment and Multiple Return Values.Mathematical Operations and Elementary Functions.

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