调用 C 和 Fortran 代码

在数值计算领域，尽管有很多用 C 语言或 Fortran 写的高质量且成熟的库都可以用 Julia 重写，但为了便捷利用现有的 C 或 Fortran 代码，Julia 提供简洁且高效的调用方式。Julia 的哲学是 "no boilerplate": Julia 可以直接调用 C/Fortran 的函数，不需要任何"胶水"代码，代码生成或其它编译过程 – 即使在交互式会话 (REPL/Jupyter notebook) 中使用也一样. 在 Julia 中，上述特性可以仅仅通过调用ccall实现，它的语法看起来就像是普通的函数调用。

被调用的代码必须是一个 shared library (.so, .dylib, .dll). 大多数 C 和 Fortran 库都已经是以 shared library 发布的，但在用 GCC 或 Clang 编译自己的代码时，需要添加 -shared 和 -fPIC 编译器选项。由于 Julia 的 JIT 生成的机器码跟原生 C 代码的调用是一样，所以在 Julia 里调用 C/Fortran 库的 overhead 与直接从 C 里调用是一样的。(在 C 和 Julia 中的非库函数调用都能被内联，因此可能会比调用标准库函数花销更少。当库与可执行文件都由 LLVM 生成时，可能会对整个程序执行甚至能跨越这一限制的优化，但是 Julia 现在还不支持这种优化。不过在未来，它可能会这么做，来获得更大的性能提升)

我们可以通过 (:function, "library") 或 ("function", "library") 这两种形式来索引库中的函数，其中 function 是函数名，library 是库名。对于不同的平台/操作系统，库的载入路径可能会不同，如果库在默认载入路径中，则可以直接将 library 设为库名，否则，需要将其设为一个完整的路径。

可以单独使用函数名来代替元组（只用:function 或 "function"）。 在这种情况下，函数名在当前进程中进行解析。这一调用形式可用于调用 C 库函数、Julia 运行时中的函数或链接到 Julia 的应用程序中的函数。

默认情况下，Fortran编译器会改变变量名generate mangled names（例如，将函数名转换为小写或大写，通常会添加下划线），要通过 ccall 调用 Fortran 函数，必须传递与 Fortran 编译器生成的相对应的标识符。 此外，在调用 Fortran 函数时，所有输入必须以指针形式传递，并已在堆或栈上分配内存。 这不仅适用于通常是堆分配的数组和其他可变对象，而且适用于整数和浮点数等标量值，这些值通常是栈分配的，并且在使用 C 或 Julia 调用约定时通常通过寄存器传递。

最终，你能使用ccall来实际生成一个对库函数的调用。ccall的参数如下：

• 一个 (:function, "library") 对，必须为字面值常量形式，

或

一个函数指针，（例如，dlsym）。

• 返回类型（参见下文，将声明的C类型对应到Julia）

  • 当包含的函数已经定义时，参数将会在编译时计算。

• 输入类型的元组。输入类型必须为字面值元组，而非元组 变量或表达式。

  • 当包含的函数已经定义时，参数将会在编译时计算。
• 紧接着的参数，如果有的话，将会以参数的实际值传递给函数。

举一个完整而简单的例子：从标准C库函数中调用 clock函数。

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

clock 不接收任何参数，并返回一个 Int32 。一个常见的问题是必须要用逗号尾随来写一个1-元组。例如，要调用 getenv 函数来获取指向环境变量值的指针，可以这样来调用：

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

请注意，参数类型元组必须是 (Cstring,)，而不是 (Cstring) 。 这是因为 (Cstring) 只是括号括起来的表达式 Cstring ，而不是包含 Cstring 的1-元组：

julia> (Cstring)
Cstring
julia> (Cstring,)
(Cstring,)

在实践中，特别是在提供可重用功能时，通常在Julia函数中封装 ccall 用于设置参数的，然后在任何指示错误的 C 或 Fortran 函数中检查错误，作为异常传递给 Julia 调用者。这一点尤其重要，因为C和Fortran的API在如何指示错误条件方面存在众所周知的不一致。 例如，C库函数getenv 包含在以下Julia函数中，该函数是env.jl实际定义的简化版本：

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

C函数 getenv 通过返回 NULL 指出了一个错误，但是其他标准C函数通过多种不同的方式来指出错误，包括返回-1, 0, 1和其它特殊值。这一层封装能抛出一个清晰地指出问题的异常，即是否调用者尝试获取一个不存在的环境变量：

julia> getenv("SHELL")
"/bin/bash"
julia> getenv("FOOBAR")
getenv: undefined variable: FOOBAR

这有一个稍微复杂一点的例子，它能发现本机的主机名：

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

这个例子首先分配一个由bytes组成的数组，然后调用C库函数gethostname用主机名填充数组，获取指向主机名缓冲区的指针，假设它是一个以NUL终止的C字符串，并将指针转换为指向Julia字符串的指针。 这种使用这种需要调用者分配内存以传递给被调用者来填充的模式对于C库函数很常见。 Julia中类似的内存分配通常是通过创建一个未初始化的数组并将指向其数据的指针传递给C函数来完成的。 这就是我们不在这里使用Cstring类型的原因：由于数组未初始化，它可能包含NUL字节。转换到Cstring作为 ccall 的一部分会检查包含的NUL字节，因此可能会抛出转换错误。

创建和C兼容的Julia函数指针

可以将Julia函数传递给接受函数指针参数的原生C函数。例如，要匹配满足下面的C原型：

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

宏 @cfunction"">@cfunction 生成可兼容C的函数指针，来调用Julia函数。 @cfunction"">@cfunction 的参数如下：

• 一个Julia函数
• 返回类型
• 一个与输入类型相同的字面量元组
  与 ccall 一样，所有的参数将会在编译期执行，也就是包含的函数被定义时执行。

目前仅支持平台默认的C调用转换。这意味着@cfunction产生的指针不能在WINAPI需要stdcall的32位Windows上使用，但是能在（stdcall独立于C调用转换的）WIN64上使用。

一个典型的例子就是标准C库函数qsort，定义为：

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

base 是一个指向长度为nmemb，每个元素大小为size的数组的指针。compare 是一个回调函数，它接受指向两个元素a和b的指针并根据a应该排在b的前面或者后面返回一个大于或小于0的整数（如果在顺序无关紧要时返回0）。现在，假设在Julia中有一整个1维数组A的值我们希望用qsort（或者Julia的内置sort函数）函数进行排序。在我们关心调用qsort及其参数传递之前，我们需要写一个为每对值之间进行比较的函数（定义<）。

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

注意，我们需要小心返回值的类型：qsort期待一个返回C语言int类型的函数，所以我们需要标出这个函数的返回值类型来确保它返回Cint。

为了传递这个函数给C，我们可以用宏 @cfunction 取得它的地址：

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

@cfunction"">@cfunction 需要三个参数: Julia函数 (mycompare), 返回值类型(Cint), 和一个输入参数类型的值元组, 此处是要排序的Cdouble(Float64) 元素的数组.

qsort的最终调用看起来是这样的：

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:

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:

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:

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:

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 Csizet 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

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:

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:

#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 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, as they are passed by value. For C code accepting pointers, Ref{T} 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. In contrast, pointers returned by the C function called should be declared to be of output type Ptr{T}, 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"">@cfunction 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

    @cfunction return type translation guide" class="reference-link">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"">@cfunction 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, you need to first encapsulate the value inside a Ref{T} 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 and therefore can be used in the same (covariant) context of the input argument to a ccall. 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 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}(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"">@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"">@cfunction 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 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 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 gethostnameccall as above, but with the correct signature for Windows:

hn = Vector{UInt8}(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, 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 function. The arguments to cglobal are a symbol specification identical to that used by ccall, 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 and unsafe_store!.

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 and setindex! (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). (Julia values v can be converted to jl_value_t* pointers, as Ptr{Cvoid}, by calling pointer_from_objref(v).)

The reverse operation (writing data to a Ptr{T}), can be performed using unsafe_store!(ptr, value, [index]). 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) 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 object and wait on it:

cond = Base.AsyncCondition()
wait(cond)

传递给C的回调应该只执行:uv_async_send的@ref">' ccall '，传递cond.handle参数，注意避免任何分配操作或与Julia运行时的其他交互。

注意，事件可能会合并，因此对uv_async_send 的多个调用可能会导致对该条件的单个唤醒通知。

关于Callbacks的更多内容

关于如何传递callback到C库的更多细节，请参考此博客.

C++

如需要直接易用的C++接口，即直接用Julia写封装代码，请参考 Cxx。如需封装C++库的工具，即用C++写封装/胶水代码，请参考CxxWrap。

原文: https://juliacn.github.io/JuliaZH.jl/latest/manual/calling-c-and-fortran-code/