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, so ffi-rs was developed to fill that void.
- High performance ✨
- Better type hints 🧐
- Simpler data description and API interface 💗
- Support more different data types between
Node.js
andC
😊 - Support modifying data in place 🥸
- Provide many ways to handle pointer type directly 🐮
- Support running ffi task in a new thread 🤩️
- Support output errno info 🤔️
- No need to use ref to handle pointer 🤫
$ 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
See CHANGELOG.md
$ npm i ffi-rs
Currently, ffi-rs only supports these types of parameters and return values. However, support for more types may be added in the future based on actual usage scenarios.
- string
- wideString
- u8
- i32
- i64
- bigInt
- u64
- void (like js undefined)
- float (can only be used as paramsType instead of retType)
- double
- boolean
- pointer
- u8Array (buffer)
- i32Array
- stringArray
- doubleArray
- floatArray (can only be used as paramsType instead of retType)
- object (Nested object is also supported in the latest version)
- function
If you want to call a C++ function whose argument type is a class, you can use the pointer
type. See tutorial
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.
- darwin-x64
- darwin-arm64
- linux-x64-gnu
- linux-x64-musl
- win32-x64-msvc
- win32-ia32-msvc
- win32-arm64-msvc
- linux-arm64-gnu
- linux-arm64-musl
- linux-arm-gnueabihf
View test.ts for the latest usage
Here is an example of how to use ffi-rs:
For the following 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 # Windows
Then you can use ffi-rs
to invoke the dynamic library file that contains functions.
It's suggested to develop with TypeScript to get type hints
const { equal } = require('assert')
const { load, DataType, open, close, arrayConstructor, define } = 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
// freeResultMemory: true, // whether or not need to free the result of return value memory automatically, default is false
})
equal(r, a + b)
// Release library memory when you're not using it.
close('libsum')
// Use define function to define a function signature
const res = define({
sum: {
library: "libsum",
retType: DataType.I32,
paramsType: [DataType.I32, DataType.I32],
},
atoi: {
library: "libnative",
retType: DataType.I32,
paramsType: [DataType.String],
}
})
equal(res.sum([1, 2]), 3)
equal(res.atoi(["1000"]), 1000)
You can also pass an empty path string in the open
function like ffi-napi to get the main program handle. Refer to dlopen
open({
library: "libnative",
path: "",
});
// In Darwin/Linux, you can call the atoi function which is included in the basic C library
equal(
load({
library: "libnative",
funcName: "atoi",
retType: DataType.I32,
paramsType: [DataType.String],
paramsValue: ["1000"],
}),
1000,
);
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],
}))
In the latest version, ffi-rs
supports modifying data in place.
The sample code is as follows
extern int modifyData(char* buffer) {
// modify buffer data in place
}
const arr = Buffer.alloc(200) // create buffer
const res = load({
library: "libsum",
funcName: "modifyData",
retType: DataType.I32,
paramsType: [
DataType.U8Array
],
paramsValue: [arr]
})
console.log(arr) // buffer data can be updated
When using array
as retType
, you should use arrayConstructor
to specify the array type with a legal length which is important.
If the length is incorrect, the program may 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],
}))
In ffi-rs
, we use DataType.External for wrapping the pointer
which enables it to be passed between Node.js
and C
.
Pointer
is complicated and underlying, ffi-rs
provides four functions to handle this pointer including createPointer
, restorePointer
, unwrapPointer
, wrapPointer
, freePointer
, isNullPointer
for different scenes.
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" char *getStringFromPtr(void *ptr) { return (char *)ptr; };
// get pointer
const ptr = load({
library: "libsum",
funcName: "concatenateStrings",
retType: DataType.External,
paramsType: [DataType.String, DataType.String],
paramsValue: [c, d],
})
// send pointer
const string = load({
library: "libsum",
funcName: "getStringFromPtr",
retType: DataType.String,
paramsType: [DataType.External],
paramsValue: [ptr],
})
createPointer
function is used for creating a pointer pointing to a specified type. In order to avoid mistakes, developers have to understand what type this pointer is.
For numeric types like i32|u8|i64|f64
, createPointer will create a pointer like *mut i32
pointing to these numbers.
For types that are originally pointer types like char *
representing string
type in C
, createPointer will create a dual pointer like *mut *mut c_char
pointing to *mut c_char
. Developers can use unwrapPointer
to get the internal pointer *mut c_char
.
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],
}),
);
For the code above, we can use createPointer
function to wrap a pointer data and send it as paramsValue
const ptrArr: unknown[] = createPointer({
paramsType: [DataType.DoubleArray],
paramsValue: [[1.1,2.2]]
})
load({
library: "libsum",
funcName: "createArrayDouble",
retType: arrayConstructor({
type: DataType.DoubleArray,
length: bigDoubleArr.length,
}),
paramsType: [DataType.External, DataType.I32],
paramsValue: [unwrapPointer(ptrArr)[0], bigDoubleArr.length],
})
The two pieces of code above are equivalent
Similarly, you can use restorePointer
to restore data from a pointer
which is wrapped by createPointer
or as a return value of a foreign function
const pointerArr = createPointer({
paramsType: [DataType.DoubleArray],
paramsValue: [[1.1, 2.2]]
})
const restoreData = restorePointer({
retType: [arrayConstructor({
type: DataType.DoubleArray,
length: 2
})],
paramsValue: pointerArr
})
deepStrictEqual(restoreData, [[1.1, 2.2]])
freePointer
is used to free memory which is not freed automatically.
By default, ffi-rs
will free data memory for ffi call args and return result to prevent memory leaks. Except in the following cases:
- set
freeResultMemory: false
when callingload
method
If you set freeResultMemory to false, ffi-rs
will not release the return result memory which was allocated in the C environment
- Use
DataType.External
as paramsType or retType
If developers use DataType.External
as paramsType or retType, please use freePointer
to release the memory of the pointer. ref test.ts
wrapPointer
is used to create multiple pointers.
For example, developers can use wrapPointer
to create a pointer pointing to other existing pointers.
const { wrapPointer } = require('ffi-rs')
// ptr type is *mut c_char
const ptr = load({
library: "libsum",
funcName: "concatenateStrings",
retType: DataType.External,
paramsType: [DataType.String, DataType.String],
paramsValue: [c, d],
})
// wrapPtr type is *mut *mut c_char
const wrapPtr = wrapPointer([ptr])[0]
unwrapPointer
is opposite to wrapPointer
which is used to get the internal pointer for multiple pointers
const { unwrapPointer, createPointer } = require('ffi-rs')
// ptr type is *mut *mut c_char
let ptr = createPointer({
paramsType: [DataType.String],
paramsValue: ["foo"]
})
// unwrapPtr type is *mut c_char
const unwrapPtr = unwrapPointer([ptr])[0]
To 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.
ffi-rs
provides a C struct named Person
with many types of fields in sum.cpp
The example call method about how to call a foreign function to create a Person
struct or use Person
struct as a return value is here
There are two types of arrays in C language like int* array
and int array[100]
that have some different usages.
The first type int* array
is a pointer type storing the first address of the array.
The second type int array[100]
is a fixed-length array and each element in the array has a continuous address.
If you use an array as a function parameter, this usually passes an array pointer regardless of which type you define. But if the array type is defined in a struct, the two types of array definitions will cause different sizes and alignments of the struct.
So, ffi-rs
needs to distinguish between the two types.
By default, ffi-rs
uses pointer arrays to calculate struct. If you confirm there should be a static array, you can define it in this way:
typedef struct Person {
//...
uint8_t staticBytes[16];
//...
} Person;
// use arrayConstructor and set ffiTypeTag field to DataType.StackArray
staticBytes: arrayConstructor({
type: DataType.U8Array,
length: parent.staticBytes.length,
ffiTypeTag: DataType.StackArray
}),
ffi-rs
supports passing JS function pointers to C functions, like this:
typedef const void (*FunctionPointer)(int a, bool b, char *c, double d,
char **e, int *f, Person *g);
extern "C" void callFunction(FunctionPointer func) {
printf("callFunction\n");
for (int i = 0; i < 2; i++) {
int a = 100;
bool b = false;
double d = 100.11;
char *c = (char *)malloc(14 * sizeof(char));
strcpy(c, "Hello, World!");
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, d, stringArray, i32Array, p);
}
}
Corresponding to the code above, you can use ffi-rs
like this:
const testFunction = () => {
const func = (a, b, c, d, e, f, g) => {
equal(a, 100);
equal(b, false);
equal(c, "Hello, World!");
equal(d, "100.11");
deepStrictEqual(e, ["Hello", "world"]);
deepStrictEqual(f, [101, 202, 303]);
deepStrictEqual(g, person);
logGreen("test function succeed");
// free function memory when it is not in use
freePointer({
paramsType: [funcConstructor({
paramsType: [
DataType.I32,
DataType.Boolean,
DataType.String,
DataType.Double,
arrayConstructor({ type: DataType.StringArray, length: 2 }),
arrayConstructor({ type: DataType.I32Array, length: 3 }),
personType,
],
retType: DataType.Void,
})],
paramsValue: funcExternal
})
if (!process.env.MEMORY) {
close("libsum");
}
};
// suggest using createPointer to create a function pointer for manual memory management
const funcExternal = createPointer({
paramsType: [funcConstructor({
paramsType: [
DataType.I32,
DataType.Boolean,
DataType.String,
DataType.Double,
arrayConstructor({ type: DataType.StringArray, length: 2 }),
arrayConstructor({ type: DataType.I32Array, length: 3 }),
personType,
],
retType: DataType.Void,
})],
paramsValue: [func]
})
load({
library: "libsum",
funcName: "callFunction",
retType: DataType.Void,
paramsType: [
DataType.External,
],
paramsValue: unwrapPointer(funcExternal),
});
}
The function parameters support all types in the example above.
Attention: since the vast majority of scenarios developers pass JS functions to C as callbacks, ffi-rs
will create threadsafe_function from JS functions which means the JS function will be called asynchronously, and the Node.js process will not exit automatically.
We'll provide more examples from real-world scenarios. If you have any ideas, please submit an issue.
In C++ scenarios, we can use DataType.External
to get a class type pointer.
In the code below, we use C types to wrap C++ types such as converting char *
to std::string
and returning a class pointer:
MyClass *createMyClass(std::string name, int age) {
return new MyClass(name, age);
}
extern "C" MyClass *createMyClassFromC(const char *name, int age) {
return createMyClass(std::string(name), age);
}
extern "C" void printMyClass(MyClass *instance) { instance->print(); }
And then, it can be called by the following code:
const classPointer = load({
library: "libsum",
funcName: "createMyClassFromC",
retType: DataType.External,
paramsType: [
DataType.String,
DataType.I32
],
paramsValue: ["classString", 26],
});
load({
library: "libsum",
funcName: "printMyClass",
retType: DataType.External,
paramsType: [
DataType.External,
],
paramsValue: [classPointer],
})
freePointer({
paramsType: [DataType.External],
paramsValue: [classPointer],
pointerType: PointerType.CPointer
})
By default, ffi-rs
will not output errno info. Developers can get it by passing errno: true
when calling the open method like:
load({
library: 'libnative',
funcName: 'setsockopt',
retType: DataType.I32,
paramsType: [DataType.I32, DataType.I32, DataType.I32, DataType.External, DataType.I32],
paramsValue: [socket._handle.fd, level, option, pointer[0], 4],
errno: true // set errno as true
})
// The above code will return an object including three fields: errnoCode, errnoMessage, and the foreign function return value
// { errnoCode: 22, errnoMessage: 'Invalid argument (os error 22)', value: -1 }
It's important to free the memory allocations during a single ffi call to prevent memory leaks.
What kinds of data memory are allocated in this?
- Call parameters in the Rust environment which are allocated in the heap like
String
- Return value which in the C environment which are allocated in the heap like
char*
By default, ffi-rs
will free call parameters memory which are allocated in Rust.
But it will not free the return value from the C side since some C dynamic libraries will manage their memory automatically (when ffi-rs >= 1.0.79)
There are two ways to prevent ffi-rs
from releasing memory:
- Set
freeResultMemory: false
when callingload
method, the default value is false
If you set freeResultMemory to false, ffi-rs
will not release the return result memory which was allocated in the C environment
- Use
DataType.External
as paramsType or retType
If developers use DataType.External
as paramsType or retType, please use freePointer
to release the memory of the pointer when this memory is no longer in use. ref test.ts
ffi-rs
supports running ffi tasks in a new thread without blocking the main thread, which is useful for CPU-intensive tasks.
To use this feature, you can pass the runInNewThread
option to the load method:
const testRunInNewThread = async () => {
// will return a promise but the task will run in a new thread
load({
library: "libsum",
funcName: "sum",
retType: DataType.I32,
paramsType: [DataType.I32, DataType.I32],
paramsValue: [1, 2],
runInNewThread: true,
}).then(res => {
equal(res, 3)
})
}