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@yuuang/ffi-rs-darwin-x64
Advanced tools
A module written in Rust and N-APi provides interface (FFI) features for Node.js
ffi-rs is a high performance module written in Rust and N-API that provides FFI (Foreign Function Interface) features for Node.js. It allows developers to call functions written in other languages such as C++, C, and Rust directly from JavaScript without writing any C++ code.
This module aims to provide similar functionality to the node-ffi module, but with a completely rewritten underlying codebase. The node-ffi module has been unmaintained for several years and is no longer usable, which is why ffi-rs was developed.
$ node bench/bench.js
Running "ffi" suite...
Progress: 100%
ffi-napi:
2 028 ops/s, ±4.87% | slowest, 99.24% slower
ffi-rs:
318 467 ops/s, ±0.17% | fastest
Finished 2 cases!
Fastest: ffi-rs
Slowest: ffi-napi
$ npm i ffi-rs
Currently, ffi-rs only supports there types of parameters and return values. However, support for more types will be added in the future based on actual usage scenarios.
Note: You need to make sure that the compilation environment of the dynamic library is the same as the installation and runtime environment of the ffi-rs
call.
Here is an example of how to use ffi-rs:
For below c++ code, we compile this file into a dynamic library
Note: The return value type of a function must be of type c
#include <cstdio>
#include <cstring>
#include <iostream>
#include <string>
extern "C" int sum(int a, int b) { return a + b; }
extern "C" double doubleSum(double a, double b) { return a + b; }
extern "C" const char *concatenateStrings(const char *str1, const char *str2) {
std::string result = std::string(str1) + std::string(str2);
char *cstr = new char[result.length() + 1];
strcpy(cstr, result.c_str());
return cstr;
}
extern "C" void noRet() { printf("%s", "hello world"); }
extern "C" bool return_opposite(bool input) { return !input; }
$ g++ -dynamiclib -o libsum.so cpp/sum.cpp # macos
$ g++ -shared -o libsum.so cpp/sum.cpp # linux
$ g++ -shared -o sum.dll cpp/sum.cpp # win
Then can use ffi-rs
invoke the dynamic library file contains functions.
const { equal } = require('assert')
const { load, DataType, open, close, arrayConstructor } = require('ffi-rs')
const a = 1
const b = 100
const dynamicLib = platform === 'win32' ? './sum.dll' : "./libsum.so"
// first open dynamic library with key for close
// It only needs to be opened once.
open({
library: 'libsum', // key
path: dynamicLib // path
})
const r = load({
library: "libsum", // path to the dynamic library file
funcName: 'sum', // the name of the function to call
retType: DataType.I32, // the return value type
paramsType: [DataType.I32, DataType.I32], // the parameter types
paramsValue: [a, b] // the actual parameter values
})
equal(r, a + b)
// release library memory when you're not using it.
close('libsum')
number|string|boolean|double|void
are basic types
const c = "foo"
const d = c.repeat(200)
equal(c + d, load({
library: 'libsum',
funcName: 'concatenateStrings',
retType: DataType.String,
paramsType: [DataType.String, DataType.String],
paramsValue: [c, d]
}))
equal(undefined, load({
library: 'libsum',
funcName: 'noRet',
retType: DataType.Void,
paramsType: [],
paramsValue: []
}))
equal(1.1 + 2.2, load({
library: 'libsum',
funcName: 'doubleSum',
retType: DataType.Double,
paramsType: [DataType.Double, DataType.Double],
paramsValue: [1.1, 2.2]
}))
const bool_val = true
equal(!bool_val, load({
library: 'libsum',
funcName: 'return_opposite',
retType: DataType.Boolean,
paramsType: [DataType.Boolean],
paramsValue: [bool_val],
}))
Use arrayConstructor
to specify array type with legal length which is important.
If the length is incorrect, program maybe exit abnormally
extern "C" int *createArrayi32(const int *arr, int size) {
int *vec = (int *)malloc((size) * sizeof(int));
for (int i = 0; i < size; i++) {
vec[i] = arr[i];
}
return vec;
}
extern "C" double *createArrayDouble(const double *arr, int size) {
double *vec = (double *)malloc((size) * sizeof(double));
for (int i = 0; i < size; i++) {
vec[i] = arr[i];
}
return vec;
}
extern "C" char **createArrayString(char **arr, int size) {
char **vec = (char **)malloc((size) * sizeof(char *));
for (int i = 0; i < size; i++) {
vec[i] = arr[i];
}
return vec;
}
let bigArr = new Array(100).fill(100)
deepStrictEqual(bigArr, load({
library: 'libsum',
funcName: 'createArrayi32',
retType: arrayConstructor({ type: DataType.I32Array, length: bigArr.length }),
paramsType: [DataType.I32Array, DataType.I32],
paramsValue: [bigArr, bigArr.length],
}))
let bigDoubleArr = new Array(5).fill(1.1)
deepStrictEqual(bigDoubleArr, load({
library: 'libsum',
funcName: 'createArrayDouble',
retType: arrayConstructor({ type: DataType.DoubleArray, length: bigDoubleArr.length }),
paramsType: [DataType.DoubleArray, DataType.I32],
paramsValue: [bigDoubleArr, bigDoubleArr.length],
}))
let stringArr = [c, c.repeat(20)]
deepStrictEqual(stringArr, load({
library: 'libsum',
funcName: 'createArrayString',
retType: arrayConstructor({ type: DataType.StringArray, length: stringArr.length }),
paramsType: [DataType.StringArray, DataType.I32],
paramsValue: [stringArr, stringArr.length],
}))
For create a c struct or get a c struct as a return type, you need to define the types of the parameters strictly in the order in which the fields of the c structure are defined.
typedef struct Person {
const char *name;
int age;
double doubleProps;
char **stringArray;
double *doubleArray;
int *i32Array;
} Person;
extern "C" const Person *getStruct(const Person *person) {
return person;
}
extern "C" Person *createPerson() {
Person *person = (Person *)malloc(sizeof(Person));
// Allocate and initialize doubleArray
person->doubleArray = (double *)malloc(sizeof(double) * 3);
person->doubleArray[0] = 1.0;
person->doubleArray[1] = 2.0;
person->doubleArray[2] = 3.0;
// Initialize age and doubleProps
person->age = 30;
person->doubleProps = 1.23;
// Allocate and initialize name
person->name = strdup("John Doe");
person->stringArray = (char **)malloc(sizeof(char *) * 2);
person->stringArray[0] = strdup("Hello");
person->stringArray[1] = strdup("World");
person->i32Array = (int *)malloc(sizeof(int) * 3);
person->i32Array[0] = 1;
person->i32Array[1] = 2;
person->i32Array[2] = 3;
person->testnum = 123;
person->boolTrue = true;
person->boolFalse = false;
return person;
}
const person = {
doubleArray: [1.1, 2.2, 3.3],
age: 23,
doubleProps: 1.1,
name: 'tom',
stringArray: ["foo", "bar"],
i32Array: [1, 2, 3, 4],
testnum: 32,
boolTrue: true,
boolFalse: false
}
const personObj = load({
library: 'libsum',
funcName: 'getStruct',
retType: {
doubleArray: arrayConstructor({ type: DataType.DoubleArray, length: person.doubleArray.length }),
age: DataType.I32,
doubleProps: DataType.Double,
name: DataType.String,
stringArray: arrayConstructor({ type: DataType.StringArray, length: person.stringArray.length }),
i32Array: arrayConstructor({ type: DataType.I32Array, length: person.i32Array.length }),
testnum: DataType.I32,
boolTrue: DataType.Boolean,
boolFalse: DataType.Boolean,
},
paramsType: [{
age: DataType.I32,
doubleProps: DataType.Double,
name: DataType.String,
stringArray: DataType.StringArray,
doubleArray: DataType.DoubleArray,
i32Array: DataType.I32Array,
testnum: DataType.I32,
boolTrue: DataType.Boolean,
boolFalse: DataType.Boolean,
}],
paramsValue: [person]
})
deepStrictEqual(person, personObj)
const p = load({
library: 'libsum',
funcName: 'createPerson',
retType: {
doubleArray: arrayConstructor({ type: DataType.DoubleArray, length: 3 }),
age: DataType.I32,
doubleProps: DataType.Double,
name: DataType.String,
stringArray: arrayConstructor({ type: DataType.StringArray, length: 2 }),
i32Array: arrayConstructor({ type: DataType.I32Array, length: 3 }),
testnum: DataType.I32,
boolTrue: DataType.Boolean,
boolFalse: DataType.Boolean,
},
paramsType: [],
paramsValue: []
})
console.log('createPerson', p)
deepStrictEqual(p, {
doubleArray: [1, 2, 3],
age: 30,
doubleProps: 1.23,
name: 'John Doe',
stringArray: ['Hello', 'World'],
i32Array: [1, 2, 3],
testnum: 123,
boolTrue: true,
boolFalse: false
})
ffi-rs
supports passing js function to c, like this
typedef void (*FunctionPointer)(int a, bool b, char *c, char **d, int *e,
Person *p);
extern "C" void callFunction(FunctionPointer func) {
printf("callFunction\n");
int a = 100;
bool b = false;
char *c = (char *)malloc(14 * sizeof(char));
strcpy(c, "Hello, World!");
// double a = 100.11;
char **stringArray = (char **)malloc(sizeof(char *) * 2);
stringArray[0] = strdup("Hello");
stringArray[1] = strdup("world");
int *i32Array = (int *)malloc(sizeof(int) * 3);
i32Array[0] = 101;
i32Array[1] = 202;
i32Array[2] = 303;
Person *p = createPerson();
func(a, b, c, stringArray, i32Array, p);
}
Corresponds to the code above,you can use ffi-rs
like
const func = (a, b, c, d, e, f) => {
console.log('func params', a, b, c, d, e, f)
equal(a, 100)
equal(b, false)
equal(c, 'Hello, World!')
deepStrictEqual(d, ['Hello', 'world'])
deepStrictEqual(e, [101, 202, 303])
deepStrictEqual(f, newP)
}
load({
library: 'libsum',
funcName: 'callFunction',
retType: DataType.Void,
paramsType: [funcConstructor({
paramsType: [DataType.I32, DataType.Boolean, DataType.String,
arrayConstructor({ type: DataType.StringArray, length: 2 }),
arrayConstructor({ type: DataType.I32Array, length: 3 }),
{
doubleArray: arrayConstructor({ type: DataType.DoubleArray, length: 3 }),
age: DataType.I32,
doubleProps: DataType.Double,
name: DataType.String,
stringArray: arrayConstructor({ type: DataType.StringArray, length: 2 }),
i32Array: arrayConstructor({ type: DataType.I32Array, length: 3 }),
testnum: DataType.I32,
boolTrue: DataType.Boolean,
boolFalse: DataType.Boolean,
}
],
retType: DataType.Void
})],
paramsValue: [func],
})
The function parameters supports type are all in the example above, we will support more types in the future
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The npm package @yuuang/ffi-rs-darwin-x64 receives a total of 9,966 weekly downloads. As such, @yuuang/ffi-rs-darwin-x64 popularity was classified as popular.
We found that @yuuang/ffi-rs-darwin-x64 demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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