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Julia 调用C和Fortran代码

# Calling C and Fortran Code

Though most code can be written in Julia, there are many high-quality, mature libraries for numerical
computing already written in C and Fortran. To allow easy use of this existing code, Julia makes
it simple and efficient to call C and Fortran functions. Julia has a "no boilerplate" philosophy:
functions can be called directly from Julia without any "glue" code, code generation, or compilation
-- even from the interactive prompt. This is accomplished just by making an appropriate call with
ccall syntax, which looks like an ordinary function call.

The code to be called must be available as a shared library. Most C and Fortran libraries ship
compiled as shared libraries already, but if you are compiling the code yourself using GCC (or
Clang), you will need to use the -shared and -fPIC options. The machine instructions generated
by Julia's JIT are the same as a native C call would be, so the resulting overhead is the same
as calling a library function from C code. (Non-library function calls in both C and Julia can
be inlined and thus may have even less overhead than calls to shared library functions. When both
libraries and executables are generated by LLVM, it is possible to perform whole-program optimizations
that can even optimize across this boundary, but Julia does not yet support that. In the future,
however, it may do so, yielding even greater performance gains.)

Shared libraries and functions are referenced by a tuple of the form (:function, "library")
or ("function", "library") where function is the C-exported function name. library refers
to the shared library name: shared libraries available in the (platform-specific) load path will
be resolved by name, and if necessary a direct path may be specified.

A function name may be used alone in place of the tuple (just :function or "function"). In
this case the name is resolved within the current process. This form can be used to call C library
functions, functions in the Julia runtime, or functions in an application linked to Julia.

By default, Fortran compilers generate mangled
names
(for example,
converting function names to lowercase or uppercase, often appending an
underscore), and so to call a Fortran function via ccall you must pass
the mangled identifier corresponding to the rule followed by your Fortran
compiler. Also, when calling a Fortran function, all inputs must be passed as
pointers to allocated values on the heap or stack. This applies not only to
arrays and other mutable objects which are normally heap-allocated, but also to
scalar values such as integers and floats which are normally stack-allocated and
commonly passed in registers when using C or Julia calling conventions.

Finally, you can use ccall to actually generate a call to the library function. Arguments
to ccall are as follows:

  1. A (:function, "library") pair, which must be written as a literal constant,

    OR

    a function pointer (for example, from dlsym).

  2. Return type (see below for mapping the declared C type to Julia)

    • This argument will be evaluated at compile-time, when the containing method is defined.
  3. A tuple of input types. The input types must be written as a literal tuple, not a tuple-valued
    variable or expression.

    • This argument will be evaluated at compile-time, when the containing method is defined.
  4. The following arguments, if any, are the actual argument values passed to the function.

As a complete but simple example, the following calls the clock function from the standard C
library:

julia> t = ccall((:clock, "libc"), Int32, ())
2292761

julia> t
2292761

julia> typeof(ans)
Int32

clock takes no arguments and returns an Int32. One common gotcha is that a 1-tuple must be
written with a trailing comma. For example, to call the getenv function to get a pointer to
the value of an environment variable, one makes a call like this:

julia> path = ccall((:getenv, "libc"), Cstring, (Cstring,), "SHELL")
Cstring(@0x00007fff5fbffc45)

julia> unsafe_string(path)
"/bin/bash"

Note that the argument type tuple must be written as (Cstring,), rather than (Cstring). This
is because (Cstring) is just the expression Cstring surrounded by parentheses, rather than
a 1-tuple containing Cstring:

julia> (Cstring)
Cstring

julia> (Cstring,)
(Cstring,)

In practice, especially when providing reusable functionality, one generally wraps ccall
uses in Julia functions that set up arguments and then check for errors in whatever manner the
C or Fortran function indicates them, propagating to the Julia caller as exceptions. This is especially
important since C and Fortran APIs are notoriously inconsistent about how they indicate error
conditions. For example, the getenv C library function is wrapped in the following Julia function,
which is a simplified version of the actual definition from env.jl:

function getenv(var::AbstractString)
val = ccall((:getenv, "libc"),
Cstring, (Cstring,), var)
if val == C_NULL
error("getenv: undefined variable: ", var)
end
unsafe_string(val)
end


The C `getenv` function indicates an error by returning `NULL`, but other standard C functions
indicate errors in various different ways, including by returning -1, 0, 1 and other special values.
This wrapper throws an exception clearly indicating the problem if the caller tries to get a non-existent
environment variable:

julia> getenv("SHELL")
"/bin/bash"

julia> getenv("FOOBAR")
getenv: undefined variable: FOOBAR


Here is a slightly more complex example that discovers the local machine's hostname:


function gethostname()
    hostname = Vector{UInt8}(undef, 128)
    ccall((:gethostname, "libc"), Int32,
          (Ptr{UInt8}, Csize_t),
          hostname, sizeof(hostname))
    hostname[end] = 0; # ensure null-termination
    return unsafe_string(pointer(hostname))
end

This example first allocates an array of bytes, then calls the C library function gethostname
to fill the array in with the hostname, takes a pointer to the hostname buffer, and converts the
pointer to a Julia string, assuming that it is a NUL-terminated C string. It is common for C libraries
to use this pattern of requiring the caller to allocate memory to be passed to the callee and
filled in. Allocation of memory from Julia like this is generally accomplished by creating an
uninitialized array and passing a pointer to its data to the C function. This is why we don't
use the Cstring type here: as the array is uninitialized, it could contain NUL bytes. Converting
to a Cstring as part of the ccall checks for contained NUL bytes and could therefore
throw a conversion error.

# Creating C-Compatible Julia Function Pointers

It is possible to pass Julia functions to native C functions that accept function pointer arguments.
For example, to match C prototypes of the form:

typedef returntype (*functiontype)(argumenttype, ...)

The macro @cfunction generates the C-compatible function pointer for a call to a
Julia function. Arguments to @cfunction are as follows:

  1. A Julia Function
  2. Return type
  3. A literal tuple of input types

Like ccall, all of these arguments will be evaluated at compile-time, when the containing method is defined.

Currently, only the platform-default C calling convention is supported. This means that
@cfunction-generated pointers cannot be used in calls where WINAPI expects stdcall
function on 32-bit windows, but can be used on WIN64 (where stdcall is unified with the
C calling convention).

A classic example is the standard C library qsort function, declared as:

void qsort(void *base, size_t nmemb, size_t size,
           int (*compare)(const void*, const void*));

The base argument is a pointer to an array of length nmemb, with elements of size bytes
each. compare is a callback function which takes pointers to two elements a and b and returns
an integer less/greater than zero if a should appear before/after b (or zero if any order
is permitted). Now, suppose that we have a 1d array A of values in Julia that we want to sort
using the qsort function (rather than Julia's built-in sort function). Before we worry about
calling qsort and passing arguments, we need to write a comparison function that works for some
arbitrary objects (which define <):

julia> function mycompare(a, b)::Cint
           return (a < b) ? -1 : ((a > b) ? +1 : 0)
       end
mycompare (generic function with 1 method)

Notice that we have to be careful about the return type: qsort expects a function returning
a C int, so we annotate the return type of the function to be sure it returns a Cint.

In order to pass this function to C, we obtain its address using the macro @cfunction:

julia> mycompare_c = @cfunction(mycompare, Cint, (Ref{Cdouble}, Ref{Cdouble}));

@cfunction requires three arguments: the Julia function (mycompare), the return type
(Cint), and a literal tuple of the input argument types, in this case to sort an array of Cdouble
(Float64) elements.

The final call to qsort looks like this:

julia> A = [1.3, -2.7, 4.4, 3.1]
4-element Array{Float64,1}:
  1.3
 -2.7
  4.4
  3.1

julia> ccall(:qsort, Cvoid, (Ptr{Cdouble}, Csize_t, Csize_t, Ptr{Cvoid}),
             A, length(A), sizeof(eltype(A)), mycompare_c)

julia> A
4-element Array{Float64,1}:
 -2.7
  1.3
  3.1
  4.4

As can be seen, A is changed to the sorted array [-2.7, 1.3, 3.1, 4.4]. Note that Julia
knows how to convert an array into a Ptr{Cdouble}, how to compute the size of a type in bytes
(identical to C's sizeof operator), and so on. For fun, try inserting a println("mycompare($a, $b)")
line into mycompare, which will allow you to see the comparisons that qsort is performing
(and to verify that it is really calling the Julia function that you passed to it).

# Mapping C Types to Julia

It is critical to exactly match the declared C type with its declaration in Julia. Inconsistencies
can cause code that works correctly on one system to fail or produce indeterminate results on
a different system.

Note that no C header files are used anywhere in the process of calling C functions: you are responsible
for making sure that your Julia types and call signatures accurately reflect those in the C header
file. (The Clang package can be used to auto-generate
Julia code from a C header file.)

# Auto-conversion:

Julia automatically inserts calls to the Base.cconvert function to convert each argument
to the specified type. For example, the following call:

ccall((:foo, "libfoo"), Cvoid, (Int32, Float64), x, y)


will behave as if the following were written:


ccall((:foo, "libfoo"), Cvoid, (Int32, Float64),
      Base.unsafe_convert(Int32, Base.cconvert(Int32, x)),
      Base.unsafe_convert(Float64, Base.cconvert(Float64, y)))

Base.cconvert normally just calls convert, but can be defined to return an
arbitrary new object more appropriate for passing to C.
This should be used to perform all allocations of memory that will be accessed by the C code.
For example, this is used to convert an Array of objects (e.g. strings) to an array of pointers.

Base.unsafe_convert handles conversion to Ptr types. It is considered unsafe because
converting an object to a native pointer can hide the object from the garbage collector, causing
it to be freed prematurely.

# Type Correspondences:

First, a review of some relevant Julia type terminology:

Syntax / KeywordExampleDescription
mutable structBitSet"Leaf Type" :: A group of related data that includes a type-tag, is managed by the Julia GC, and is defined by object-identity. The type parameters of a leaf type must be fully defined (no TypeVars are allowed) in order for the instance to be constructed.
abstract typeAny, AbstractArray{T, N}, Complex{T}"Super Type" :: A super-type (not a leaf-type) that cannot be instantiated, but can be used to describe a group of types.
T{A}Vector{Int}"Type Parameter" :: A specialization of a type (typically used for dispatch or storage optimization).
|"TypeVar" :: The T in the type parameter declaration is referred to as a TypeVar (short for type variable).
primitive typeInt, Float64"Primitive Type" :: A type with no fields, but a size. It is stored and defined by-value.
structPair{Int, Int}"Struct" :: A type with all fields defined to be constant. It is defined by-value, and may be stored with a type-tag.
| ComplexF64 (isbits)"Is-Bits" :: A primitive type, or a struct type where all fields are other isbits types. It is defined by-value, and is stored without a type-tag.
struct ...; endnothing"Singleton" :: a Leaf Type or Struct with no fields.
(...) or tuple(...)(1, 2, 3)"Tuple" :: an immutable data-structure similar to an anonymous struct type, or a constant array. Represented as either an array or a struct.

# [Bits Types](@id man-bits-types)

There are several special types to be aware of, as no other type can be defined to behave the
same:

  • Float32

    Exactly corresponds to the float type in C (or REAL*4 in Fortran).

  • Float64

    Exactly corresponds to the double type in C (or REAL*8 in Fortran).

  • ComplexF32

    Exactly corresponds to the complex float type in C (or COMPLEX*8 in Fortran).

  • ComplexF64

    Exactly corresponds to the complex double type in C (or COMPLEX*16 in Fortran).

  • Signed

    Exactly corresponds to the signed type annotation in C (or any INTEGER type in Fortran).
    Any Julia type that is not a subtype of Signed is assumed to be unsigned.

  • Ref{T}

    Behaves like a Ptr{T} that can manage its memory via the Julia GC.

  • Array{T,N}

    When an array is passed to C as a Ptr{T} argument, it is not reinterpret-cast: Julia requires
    that the element type of the array matches T, and the address of the first element is passed.

    Therefore, if an Array contains data in the wrong format, it will have to be explicitly converted
    using a call such as trunc(Int32, a).

    To pass an array A as a pointer of a different type without converting the data beforehand
    (for example, to pass a Float64 array to a function that operates on uninterpreted bytes), you
    can declare the argument as Ptr{Cvoid}.

    If an array of eltype Ptr{T} is passed as a Ptr{Ptr{T}} argument, Base.cconvert
    will attempt to first make a null-terminated copy of the array with each element replaced by its
    Base.cconvert version. This allows, for example, passing an argv pointer array of type
    Vector{String} to an argument of type Ptr{Ptr{Cchar}}.

On all systems we currently support, basic C/C++ value types may be translated to Julia types
as follows. Every C type also has a corresponding Julia type with the same name, prefixed by C.
This can help for writing portable code (and remembering that an int in C is not the same as
an Int in Julia).

System Independent:

C nameFortran nameStandard Julia AliasJulia Base Type
unsigned charCHARACTERCucharUInt8
bool (only in C++)| CucharUInt8
shortINTEGER*2, LOGICAL*2CshortInt16
unsigned short| CushortUInt16
int, BOOL (C, typical)INTEGER*4, LOGICAL*4CintInt32
unsigned int| CuintUInt32
long longINTEGER*8, LOGICAL*8ClonglongInt64
unsigned long long| CulonglongUInt64
intmax_t| Cintmax_tInt64
uintmax_t| Cuintmax_tUInt64
floatREAL*4iCfloatFloat32
doubleREAL*8CdoubleFloat64
complex floatCOMPLEX*8ComplexF32Complex{Float32}
complex doubleCOMPLEX*16ComplexF64Complex{Float64}
ptrdiff_t| Cptrdiff_tInt
ssize_t| Cssize_tInt
size_t| Csize_tUInt
void|Cvoid
void and [[noreturn]] or _Noreturn|Union{}
void*|Ptr{Cvoid}
T* (where T represents an appropriately defined type)|Ref{T}
char* (or char[], e.g. a string)CHARACTER*N| Cstring if NUL-terminated, or Ptr{UInt8} if not
char** (or *char[])|Ptr{Ptr{UInt8}}
jl_value_t* (any Julia Type)|Any
jl_value_t** (a reference to a Julia Type)|Ref{Any}
va_arg|Not supported
... (variadic function specification)|T... (where T is one of the above types, variadic functions of different argument types are not supported)

The Cstring type is essentially a synonym for Ptr{UInt8}, except the conversion to Cstring
throws an error if the Julia string contains any embedded NUL characters (which would cause the
string to be silently truncated if the C routine treats NUL as the terminator). If you are passing
a char* to a C routine that does not assume NUL termination (e.g. because you pass an explicit
string length), or if you know for certain that your Julia string does not contain NUL and want
to skip the check, you can use Ptr{UInt8} as the argument type. Cstring can also be used as
the ccall return type, but in that case it obviously does not introduce any extra
checks and is only meant to improve readability of the call.

System-dependent:

C nameStandard Julia AliasJulia Base Type
charCcharInt8 (x86, x86_64), UInt8 (powerpc, arm)
longClongInt (UNIX), Int32 (Windows)
unsigned longCulongUInt (UNIX), UInt32 (Windows)
wchar_tCwchar_tInt32 (UNIX), UInt16 (Windows)

!!! note
When calling Fortran, all inputs must be passed by pointers to heap- or stack-allocated
values, so all type correspondences above should contain an additional Ptr{..} or
Ref{..} wrapper around their type specification.

!!! warning
For string arguments (char*) the Julia type should be Cstring (if NUL- terminated data is
expected) or either Ptr{Cchar} or Ptr{UInt8} otherwise (these two pointer types have the same
effect), as described above, not String. Similarly, for array arguments (T[] or T*), the
Julia type should again be Ptr{T}, not Vector{T}.

!!! warning
Julia's Char type is 32 bits, which is not the same as the wide character type (wchar_t or
wint_t) on all platforms.

!!! warning
A return type of Union{} means the function will not return i.e. C++11 [[noreturn]] or C11
_Noreturn (e.g. jl_throw or longjmp). Do not use this for functions that return no value
(void) but do return, use Cvoid instead.

!!! note
For wchar_t* arguments, the Julia type should be Cwstring (if the C routine expects a NUL-terminated
string) or Ptr{Cwchar_t} otherwise. Note also that UTF-8 string data in Julia is internally
NUL-terminated, so it can be passed to C functions expecting NUL-terminated data without making
a copy (but using the Cwstring type will cause an error to be thrown if the string itself contains
NUL characters).

!!! note
C functions that take an argument of the type char** can be called by using a Ptr{Ptr{UInt8}}
type within Julia. For example, C functions of the form:

```c
int main(int argc, char **argv);
```

can be called via the following Julia code:


argv = [ "a.out", "arg1", "arg2" ]
ccall(:main, Int32, (Int32, Ptr{Ptr{UInt8}}), length(argv), argv)
```

!!! note
For Fortran functions taking variable length strings of type character(len=*) the string lengths
are provided as hidden arguments. Type and position of these arguments in the list are compiler
specific, where compiler vendors usually default to using Csize_t as type and append the hidden
arguments at the end of the argument list. While this behaviour is fixed for some compilers (GNU),
others optionally permit placing hidden arguments directly after the character argument (Intel,PGI).
For example, Fortran subroutines of the form

```fortran
subroutine test(str1, str2)
character(len=*) :: str1,str2
```

can be called via the following Julia code, where the lengths are appended


str1 = "foo"
str2 = "bar"
ccall(:test, Void, (Ptr{UInt8}, Ptr{UInt8}, Csize_t, Csize_t),
                    str1, str2, sizeof(str1), sizeof(str2))
```

!!! warning
Fortran compilers may also add other hidden arguments for pointers, assumed-shape (:)
and assumed-size (*) arrays. Such behaviour can be avoided by using ISO_C_BINDING and
including bind(c) in the definition of the subroutine, which is strongly recommended for
interoperable code. In this case there will be no hidden arguments, at the cost of some
language features (e.g. only character(len=1) will be permitted to pass strings).

!!! note
A C function declared to return Cvoid will return the value nothing in Julia.

# Struct Type correspondences

Composite types, aka struct in C or TYPE in Fortran90 (or STRUCTURE / RECORD in some variants
of F77), can be mirrored in Julia by creating a struct definition with the same
field layout.

When used recursively, isbits types are stored inline. All other types are stored as a pointer
to the data. When mirroring a struct used by-value inside another struct in C, it is imperative
that you do not attempt to manually copy the fields over, as this will not preserve the correct
field alignment. Instead, declare an isbits struct type and use that instead. Unnamed structs
are not possible in the translation to Julia.

Packed structs and union declarations are not supported by Julia.

You can get a near approximation of a union if you know, a priori, the field that will have
the greatest size (potentially including padding). When translating your fields to Julia, declare
the Julia field to be only of that type.

Arrays of parameters can be expressed with NTuple:

in C:

struct B {
    int A[3];
};
b_a_2 = B.A[2];

in Julia:

struct B
A::NTuple{3, Cint}
end
b_a_2 = B.A[3] # note the difference in indexing (1-based in Julia, 0-based in C)


Arrays of unknown size (C99-compliant variable length structs specified by `[]` or `[0]`) are not directly supported.
Often the best way to deal with these is to deal with the byte offsets directly.
For example, if a C library declared a proper string type and returned a pointer to it:

```c
struct String {
    int strlen;
    char data[];
};

In Julia, we can access the parts independently to make a copy of that string:

str = from_c::Ptr{Cvoid}
len = unsafe_load(Ptr{Cint}(str))
unsafe_string(str + Core.sizeof(Cint), len)


### Type Parameters

The type arguments to `ccall` and `@cfunction` are evaluated statically,
when the method containing the usage is defined.
They therefore must take the form of a literal tuple, not a variable,
and cannot reference local variables.

This may sound like a strange restriction,
but remember that since C is not a dynamic language like Julia,
its functions can only accept argument types with a statically-known, fixed signature.

However, while the type layout must be known statically to compute the intended C ABI,
the static parameters of the function are considered to be part of this static environment.
The static parameters of the function may be used as type parameters in the call signature,
as long as they don't affect the layout of the type.
For example, `f(x::T) where {T} = ccall(:valid, Ptr{T}, (Ptr{T},), x)`
is valid, since `Ptr` is always a word-size primitive type.
But, `g(x::T) where {T} = ccall(:notvalid, T, (T,), x)`
is not valid, since the type layout of `T` is not known statically.

### SIMD Values

Note: This feature is currently implemented on 64-bit x86 and AArch64 platforms only.

If a C/C++ routine has an argument or return value that is a native SIMD type, the corresponding
Julia type is a homogeneous tuple of `VecElement` that naturally maps to the SIMD type.  Specifically:

>   * The tuple must be the same size as the SIMD type. For example, a tuple representing an `__m128`
>     on x86 must have a size of 16 bytes.
>   * The element type of the tuple must be an instance of `VecElement{T}` where `T` is a primitive type that
>     is 1, 2, 4 or 8 bytes.

For instance, consider this C routine that uses AVX intrinsics:

```c
#include <immintrin.h>

__m256 dist( __m256 a, __m256 b ) {
    return _mm256_sqrt_ps(_mm256_add_ps(_mm256_mul_ps(a, a),
                                        _mm256_mul_ps(b, b)));
}

The following Julia code calls dist using ccall:

const m256 = NTuple{8, VecElement{Float32}}

a = m256(ntuple(i -> VecElement(sin(Float32(i))), 8))
b = m256(ntuple(i -> VecElement(cos(Float32(i))), 8))

function call_dist(a::m256, b::m256)
ccall((:dist, "libdist"), m256, (m256, m256), a, b)
end

println(call_dist(a,b))


The host machine must have the requisite SIMD registers.  For example, the code above will not
work on hosts without AVX support.

### Memory Ownership

**malloc/free**

Memory allocation and deallocation of such objects must be handled by calls to the appropriate
cleanup routines in the libraries being used, just like in any C program. Do not try to free an
object received from a C library with [`Libc.free`](@ref) in Julia, as this may result in the `free` function
being called via the wrong `libc` library and cause Julia to crash. The reverse (passing an object
allocated in Julia to be freed by an external library) is equally invalid.

### When to use T, Ptr{T} and Ref{T}

In Julia code wrapping calls to external C routines, ordinary (non-pointer) data should be declared
to be of type `T` inside the [`ccall`](@ref), as they are passed by value.  For C code accepting
pointers, [`Ref{T}`](@ref) should generally be used for the types of input arguments, allowing the use
of pointers to memory managed by either Julia or C through the implicit call to [`Base.cconvert`](@ref).
 In contrast, pointers returned by the C function called should be declared to be of output type
[`Ptr{T}`](@ref), reflecting that the memory pointed to is managed by C only. Pointers contained in C
structs should be represented as fields of type `Ptr{T}` within the corresponding Julia struct
types designed to mimic the internal structure of corresponding C structs.

In Julia code wrapping calls to external Fortran routines, all input arguments
should be declared as of type `Ref{T}`, as Fortran passes all variables by
pointers to memory locations. The return type should either be `Cvoid` for
Fortran subroutines, or a `T` for Fortran functions returning the type `T`.

## Mapping C Functions to Julia

### `ccall` / `@cfunction` argument translation guide

For translating a C argument list to Julia:

  * `T`, where `T` is one of the primitive types: `char`, `int`, `long`, `short`, `float`, `double`,
    `complex`, `enum` or any of their `typedef` equivalents

      * `T`, where `T` is an equivalent Julia Bits Type (per the table above)
      * if `T` is an `enum`, the argument type should be equivalent to `Cint` or `Cuint`
      * argument value will be copied (passed by value)
  * `struct T` (including typedef to a struct)

      * `T`, where `T` is a Julia leaf type
      * argument value will be copied (passed by value)
  * `void*`

      * depends on how this parameter is used, first translate this to the intended pointer type, then
        determine the Julia equivalent using the remaining rules in this list
      * this argument may be declared as `Ptr{Cvoid}`, if it really is just an unknown pointer
  * `jl_value_t*`

      * `Any`
      * argument value must be a valid Julia object
  * `jl_value_t**`

      * `Ref{Any}`
      * argument value must be a valid Julia object (or `C_NULL`)
  * `T*`

      * `Ref{T}`, where `T` is the Julia type corresponding to `T`
      * argument value will be copied if it is an `isbits` type otherwise, the value must be a valid Julia
        object
  * `T (*)(...)` (e.g. a pointer to a function)

      * `Ptr{Cvoid}` (you may need to use [`@cfunction`](@ref) explicitly to create this pointer)
  * `...` (e.g. a vararg)

      * `T...`, where `T` is the Julia type
      * currently unsupported by `@cfunction`
  * `va_arg`

      * not supported by `ccall` or `@cfunction`

### `ccall` / `@cfunction` return type translation guide

For translating a C return type to Julia:

  * `void`

      * `Cvoid` (this will return the singleton instance `nothing::Cvoid`)
  * `T`, where `T` is one of the primitive types: `char`, `int`, `long`, `short`, `float`, `double`,
    `complex`, `enum` or any of their `typedef` equivalents

      * `T`, where `T` is an equivalent Julia Bits Type (per the table above)
      * if `T` is an `enum`, the argument type should be equivalent to `Cint` or `Cuint`
      * argument value will be copied (returned by-value)
  * `struct T` (including typedef to a struct)

      * `T`, where `T` is a Julia Leaf Type
      * argument value will be copied (returned by-value)
  * `void*`

      * depends on how this parameter is used, first translate this to the intended pointer type, then
        determine the Julia equivalent using the remaining rules in this list
      * this argument may be declared as `Ptr{Cvoid}`, if it really is just an unknown pointer
  * `jl_value_t*`

      * `Any`
      * argument value must be a valid Julia object
  * `jl_value_t**`

      * `Ptr{Any}` (`Ref{Any}` is invalid as a return type)
      * argument value must be a valid Julia object (or `C_NULL`)
  * `T*`

      * If the memory is already owned by Julia, or is an `isbits` type, and is known to be non-null:

          * `Ref{T}`, where `T` is the Julia type corresponding to `T`
          * a return type of `Ref{Any}` is invalid, it should either be `Any` (corresponding to `jl_value_t*`)
            or `Ptr{Any}` (corresponding to `jl_value_t**`)
          * C **MUST NOT** modify the memory returned via `Ref{T}` if `T` is an `isbits` type
      * If the memory is owned by C:

          * `Ptr{T}`, where `T` is the Julia type corresponding to `T`
  * `T (*)(...)` (e.g. a pointer to a function)

      * `Ptr{Cvoid}` (you may need to use [`@cfunction`](@ref) explicitly to create this pointer)

### Passing Pointers for Modifying Inputs

Because C doesn't support multiple return values, often C functions will take pointers to data
that the function will modify. To accomplish this within a [`ccall`](@ref), you need to first
encapsulate the value inside a [`Ref{T}`](@ref) of the appropriate type. When you pass this `Ref` object
as an argument, Julia will automatically pass a C pointer to the encapsulated data:


width = Ref{Cint}(0)
range = Ref{Cfloat}(0)
ccall(:foo, Cvoid, (Ref{Cint}, Ref{Cfloat}), width, range)

Upon return, the contents of width and range can be retrieved (if they were changed by foo)
by width[] and range[]; that is, they act like zero-dimensional arrays.

# Special Reference Syntax for ccall (deprecated):

The & syntax is deprecated, use the Ref{T} argument type instead.

A prefix & is used on an argument to ccall to indicate that a pointer to a scalar
argument should be passed instead of the scalar value itself (required for all Fortran function
arguments, as noted above). The following example computes a dot product using a BLAS function.

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64})
@assert length(DX) == length(DY)
n = length(DX)
incx = incy = 1
product = ccall((:ddot_, "libLAPACK"),
Float64,
(Ref{Int32}, Ptr{Float64}, Ref{Int32}, Ptr{Float64}, Ref{Int32}),
n, DX, incx, DY, incy)
return product
end


The meaning of prefix `&` is not quite the same as in C. In particular, any changes to the referenced
variables will not be visible in Julia unless the type is mutable (declared via `mutable struct`). However,
even for immutable structs it will not cause any harm for called functions to attempt such modifications
(that is, writing through the passed pointers). Moreover, `&` may be used with any expression,
such as `&0` or `&f(x)`.

When a scalar value is passed with `&` as an argument of type `Ptr{T}`, the value will first be
converted to type `T`.

## Some Examples of C Wrappers

Here is a simple example of a C wrapper that returns a `Ptr` type:


mutable struct gsl_permutation
end

# The corresponding C signature is
#     gsl_permutation * gsl_permutation_alloc (size_t n);
function permutation_alloc(n::Integer)
    output_ptr = ccall(
        (:gsl_permutation_alloc, :libgsl), # name of C function and library
        Ptr{gsl_permutation},              # output type
        (Csize_t,),                        # tuple of input types
        n                                  # name of Julia variable to pass in
    )
    if output_ptr == C_NULL # Could not allocate memory
        throw(OutOfMemoryError())
    end
    return output_ptr
end

The GNU Scientific Library (here assumed to be accessible
through :libgsl) defines an opaque pointer, gsl_permutation *, as the return type of the C
function gsl_permutation_alloc. As user code never has to look inside the gsl_permutation
struct, the corresponding Julia wrapper simply needs a new type declaration, gsl_permutation,
that has no internal fields and whose sole purpose is to be placed in the type parameter of a
Ptr type. The return type of the ccall is declared as Ptr{gsl_permutation}, since
the memory allocated and pointed to by output_ptr is controlled by C (and not Julia).

The input n is passed by value, and so the function's input signature is
simply declared as (Csize_t,) without any Ref or Ptr necessary. (If the
wrapper was calling a Fortran function instead, the corresponding function input
signature should instead be (Ref{Csize_t},), since Fortran variables are
passed by pointers.) Furthermore, n can be any type that is convertible to a
Csize_t integer; the ccall implicitly calls Base.cconvert(Csize_t, n).

Here is a second example wrapping the corresponding destructor:

# The corresponding C signature is

# void gsl_permutation_free (gsl_permutation * p);

function permutation_free(p::Ref{gsl_permutation})
ccall(
(:gsl_permutation_free, :libgsl), # name of C function and library
Cvoid, # output type
(Ref{gsl_permutation},), # tuple of input types
p # name of Julia variable to pass in
)
end


Here, the input `p` is declared to be of type `Ref{gsl_permutation}`, meaning that the memory
that `p` points to may be managed by Julia or by C. A pointer to memory allocated by C should
be of type `Ptr{gsl_permutation}`, but it is convertible using [`Base.cconvert`](@ref) and therefore
can be used in the same (covariant) context of the input argument to a [`ccall`](@ref). A pointer
to memory allocated by Julia must be of type `Ref{gsl_permutation}`, to ensure that the memory
address pointed to is valid and that Julia's garbage collector manages the chunk of memory pointed
to correctly. Therefore, the `Ref{gsl_permutation}` declaration allows pointers managed by C or
Julia to be used.

If the C wrapper never expects the user to pass pointers to memory managed by Julia, then using
`p::Ptr{gsl_permutation}` for the method signature of the wrapper and similarly in the [`ccall`](@ref)
is also acceptable.

Here is a third example passing Julia arrays:


# The corresponding C signature is
#    int gsl_sf_bessel_Jn_array (int nmin, int nmax, double x,
#                                double result_array[])
function sf_bessel_Jn_array(nmin::Integer, nmax::Integer, x::Real)
    if nmax < nmin
        throw(DomainError())
    end
    result_array = Vector{Cdouble}(undef, nmax - nmin + 1)
    errorcode = ccall(
        (:gsl_sf_bessel_Jn_array, :libgsl), # name of C function and library
        Cint,                               # output type
        (Cint, Cint, Cdouble, Ref{Cdouble}),# tuple of input types
        nmin, nmax, x, result_array         # names of Julia variables to pass in
    )
    if errorcode != 0
        error("GSL error code $errorcode")
    end
    return result_array
end

The C function wrapped returns an integer error code; the results of the actual evaluation of
the Bessel J function populate the Julia array result_array. This variable can only be used
with corresponding input type declaration Ref{Cdouble}, since its memory is allocated and managed
by Julia, not C. The implicit call to Base.cconvert(Ref{Cdouble}, result_array) unpacks
the Julia pointer to a Julia array data structure into a form understandable by C.

Note that for this code to work correctly, result_array must be declared to be of type Ref{Cdouble}
and not Ptr{Cdouble}. The memory is managed by Julia and the Ref signature alerts Julia's
garbage collector to keep managing the memory for result_array while the ccall executes.
If Ptr{Cdouble} were used instead, the ccall may still work, but Julia's garbage
collector would not be aware that the memory declared for result_array is being used by the
external C function. As a result, the code may produce a memory leak if result_array never gets
freed by the garbage collector, or if the garbage collector prematurely frees result_array,
the C function may end up throwing an invalid memory access exception.

# Garbage Collection Safety

When passing data to a ccall, it is best to avoid using the pointer function.
Instead define a convert method and pass the variables directly to the ccall. ccall
automatically arranges that all of its arguments will be preserved from garbage collection until
the call returns. If a C API will store a reference to memory allocated by Julia, after the ccall
returns, you must arrange that the object remains visible to the garbage collector. The suggested
way to handle this is to make a global variable of type Array{Ref,1} to hold these values, until
the C library notifies you that it is finished with them.

Whenever you have created a pointer to Julia data, you must ensure the original data exists until
you are done with using the pointer. Many methods in Julia such as unsafe_load and
String make copies of data instead of taking ownership of the buffer, so that it is
safe to free (or alter) the original data without affecting Julia. A notable exception is unsafe_wrap
which, for performance reasons, shares (or can be told to take ownership of) the underlying buffer.

The garbage collector does not guarantee any order of finalization. That is, if a contained
a reference to b and both a and b are due for garbage collection, there is no guarantee
that b would be finalized after a. If proper finalization of a depends on b being valid,
it must be handled in other ways.

# Non-constant Function Specifications

A (name, library) function specification must be a constant expression. However, it is possible
to use computed values as function names by staging through eval as follows:

@eval ccall(($(string("a", "b")), "lib"), ...

This expression constructs a name using string, then substitutes this name into a new ccall
expression, which is then evaluated. Keep in mind that eval only operates at the top level,
so within this expression local variables will not be available (unless their values are substituted
with $). For this reason, eval is typically only used to form top-level definitions, for example
when wrapping libraries that contain many similar functions.
A similar example can be constructed for @cfunction.

However, doing this will also be very slow and leak memory, so you should usually avoid this and instead keep reading.
The next section discusses how to use indirect calls to efficiently accomplish a similar effect.

# Indirect Calls

The first argument to ccall can also be an expression evaluated at run time. In this
case, the expression must evaluate to a Ptr, which will be used as the address of the native
function to call. This behavior occurs when the first ccall argument contains references
to non-constants, such as local variables, function arguments, or non-constant globals.

For example, you might look up the function via dlsym,
then cache it in a shared reference for that session. For example:

macro dlsym(func, lib)
z = Ref{Ptr{Cvoid}}(C_NULL)
quote
let zlocal = $z[]
if zlocal == C_NULL
zlocal = dlsym($(esc(lib))::Ptr{Cvoid}, $(esc(func)))::Ptr{Cvoid}
$z[] = $zlocal
end
zlocal
end
end
end

mylibvar = Libdl.dlopen("mylib")
ccall(@dlsym("myfunc", mylibvar), Cvoid, ())


## Closure cfunctions

The first argument to [`@cfunction`](@ref) can be marked with a `$`, in which case
the return value will instead be a `struct CFunction` which closes over the argument.
You must ensure that this return object is kept alive until all uses of it are done.
The contents and code at the cfunction pointer will be erased via a [`finalizer`](@ref)
when this reference is dropped and atexit. This is not usually needed, since this
functionality is not present in C, but can be useful for dealing with ill-designed APIs
which don't provide a separate closure environment parameter.


function qsort(a::Vector{T}, cmp) where T
    isbits(T) || throw(ArgumentError("this method can only qsort isbits arrays"))
    callback = @cfunction $cmp Cint (Ref{T}, Ref{T})
    # Here, `callback` isa Base.CFunction, which will be converted to Ptr{Cvoid}
    # (and protected against finalization) by the ccall
    ccall(:qsort, Cvoid, (Ptr{T}, Csize_t, Csize_t, Ptr{Cvoid}),
        a, length(a), Base.elsize(a), callback)
    # We could instead use:
    #    GC.@preserve callback begin
    #        use(Base.unsafe_convert(Ptr{Cvoid}, callback))
    #    end
    # if we needed to use it outside of a `ccall`
    return a
end

# Closing a Library

It is sometimes useful to close (unload) a library so that it can be reloaded.
For instance, when developing C code for use with Julia, one may need to compile,
call the C code from Julia, then close the library, make an edit, recompile,
and load in the new changes. One can either restart Julia or use the
Libdl functions to manage the library explicitly, such as:

lib = Libdl.dlopen("./my_lib.so") # Open the library explicitly.
sym = Libdl.dlsym(lib, :my_fcn) # Get a symbol for the function to call.
ccall(sym, ...) # Use the pointer sym instead of the (symbol, library) tuple (remaining arguments are the same).
Libdl.dlclose(lib) # Close the library explicitly.


Note that when using `ccall` with the tuple input
(e.g., `ccall((:my_fcn, "./my_lib.so"), ...)`), the library is opened implicitly
and it may not be explicitly closed.

## Calling Convention

The second argument to [`ccall`](@ref) can optionally be a calling convention specifier (immediately
preceding return type). Without any specifier, the platform-default C calling convention is used.
Other supported conventions are: `stdcall`, `cdecl`, `fastcall`, and `thiscall` (no-op on 64-bit Windows). For example (from
`base/libc.jl`) we see the same `gethostname`[`ccall`](@ref) as above, but with the correct
signature for Windows:


hn = Vector{UInt8}(undef, 256)
err = ccall(:gethostname, stdcall, Int32, (Ptr{UInt8}, UInt32), hn, length(hn))

For more information, please see the LLVM Language Reference.

There is one additional special calling convention [llvmcall](@ref Base.llvmcall),
which allows inserting calls to LLVM intrinsics directly.
This can be especially useful when targeting unusual platforms such as GPGPUs.
For example, for CUDA, we need to be able to read the thread index:

ccall("llvm.nvvm.read.ptx.sreg.tid.x", llvmcall, Int32, ())


As with any `ccall`, it is essential to get the argument signature exactly correct.
Also, note that there is no compatibility layer that ensures the intrinsic makes
sense and works on the current target,
unlike the equivalent Julia functions exposed by `Core.Intrinsics`.

## Accessing Global Variables

Global variables exported by native libraries can be accessed by name using the [`cglobal`](@ref)
function. The arguments to [`cglobal`](@ref) are a symbol specification identical to that used
by [`ccall`](@ref), and a type describing the value stored in the variable:

julia> cglobal((:errno, :libc), Int32)
Ptr{Int32} @0x00007f418d0816b8


The result is a pointer giving the address of the value. The value can be manipulated through
this pointer using [`unsafe_load`](@ref) and [`unsafe_store!`](@ref).

## Accessing Data through a Pointer

The following methods are described as "unsafe" because a bad pointer or type declaration can
cause Julia to terminate abruptly.

Given a `Ptr{T}`, the contents of type `T` can generally be copied from the referenced memory
into a Julia object using `unsafe_load(ptr, [index])`. The index argument is optional (default
is 1), and follows the Julia-convention of 1-based indexing. This function is intentionally similar
to the behavior of [`getindex`](@ref) and [`setindex!`](@ref) (e.g. `[]` access syntax).

The return value will be a new object initialized to contain a copy of the contents of the referenced
memory. The referenced memory can safely be freed or released.

If `T` is `Any`, then the memory is assumed to contain a reference to a Julia object (a `jl_value_t*`),
the result will be a reference to this object, and the object will not be copied. You must be
careful in this case to ensure that the object was always visible to the garbage collector (pointers
do not count, but the new reference does) to ensure the memory is not prematurely freed. Note
that if the object was not originally allocated by Julia, the new object will never be finalized
by Julia's garbage collector.  If the `Ptr` itself is actually a `jl_value_t*`, it can be converted
back to a Julia object reference by [`unsafe_pointer_to_objref(ptr)`](@ref). (Julia values `v`
can be converted to `jl_value_t*` pointers, as `Ptr{Cvoid}`, by calling [`pointer_from_objref(v)`](@ref).)

The reverse operation (writing data to a `Ptr{T}`), can be performed using [`unsafe_store!(ptr, value, [index])`](@ref).
Currently, this is only supported for primitive types or other pointer-free (`isbits`) immutable struct types.

Any operation that throws an error is probably currently unimplemented and should be posted as
a bug so that it can be resolved.

If the pointer of interest is a plain-data array (primitive type or immutable struct), the function [`unsafe_wrap(Array, ptr,dims, own = false)`](@ref)
may be more useful. The final parameter should be true if Julia should "take ownership" of the
underlying buffer and call `free(ptr)` when the returned `Array` object is finalized.  If the
`own` parameter is omitted or false, the caller must ensure the buffer remains in existence until
all access is complete.

Arithmetic on the `Ptr` type in Julia (e.g. using `+`) does not behave the same as C's pointer
arithmetic. Adding an integer to a `Ptr` in Julia always moves the pointer by some number of
*bytes*, not elements. This way, the address values obtained from pointer arithmetic do not depend
on the element types of pointers.

## Thread-safety

Some C libraries execute their callbacks from a different thread, and since Julia isn't thread-safe
you'll need to take some extra precautions. In particular, you'll need to set up a two-layered
system: the C callback should only *schedule* (via Julia's event loop) the execution of your "real"
callback. To do this, create an [`AsyncCondition`](@ref Base.AsyncCondition) object and [`wait`](@ref) on it:


cond = Base.AsyncCondition()
wait(cond)

The callback you pass to C should only execute a ccall to :uv_async_send, passing
cond.handle as the argument, taking care to avoid any allocations or other interactions with the
Julia runtime.

Note that events may be coalesced, so multiple calls to uv_async_send may result in a single wakeup
notification to the condition.

# More About Callbacks

For more details on how to pass callbacks to C libraries, see this blog post.

# C++

For direct C++ interfacing, see the Cxx package. For tools to create C++
bindings, see the CxxWrap package.