对于Linux C应用程序:

这是我根据上面的答案重新编写的代码，它遵循我的C代码实践并返回任意大小的随机缓冲区(具有适当的返回代码等)。确保在程序开始时调用urandom_open()一次。

int gUrandomFd = -1;

int urandom_open(void)
{
    if (gUrandomFd == -1) {
        gUrandomFd = open("/dev/urandom", O_RDONLY);
    }

    if (gUrandomFd == -1) {
        fprintf(stderr, "Error opening /dev/urandom: errno [%d], strerrer [%s]\n",
                  errno, strerror(errno));
        return -1;
    } else {
        return 0;
    }
}


void urandom_close(void)
{
    close(gUrandomFd);
    gUrandomFd = -1;
}


//
// This link essentially validates the merits of /dev/urandom:
// http://sockpuppet.org/blog/2014/02/25/safely-generate-random-numbers/
//
int getRandomBuffer(uint8_t *buf, int size)
{
    int ret = 0; // Return value

    if (gUrandomFd == -1) {
        fprintf(stderr, "Urandom (/dev/urandom) file not open\n");
        return -1;
    }

    ret = read(gUrandomFd, buf, size);

    if (ret != size) {
        fprintf(stderr, "Only read [%d] bytes, expected [%d]\n",
                 ret, size);
        return -1;
    } else {
        return 0;
    }
}

你可以生成随机字符，然后将它们视为int:

#include <stdlib.h>
#include <stdio.h>

typedef double rand_type; // change double to int

rand_type my_rand() {
    char buff[sizeof(rand_type)];
    for (size_t i = 0 ; i < sizeof(rand_type) ; ++i)
        buff[i] = (char) rand();
    return *(rand_type *) buff;
}

int main() {
    int i ; // srand as you want
    for (i = 0 ; i < 10 ; ++i)
        printf("%g\n", my_rand()); // change %g to %d
    return 0 ;
}

我们来看看这个。首先，我们使用srand()函数来为随机化器播种。基本上，计算机可以根据输入给srand()的数字生成随机数。如果你给出相同的种子值，那么每次都会生成相同的随机数。

因此，我们必须用一个总是在变化的值来给随机化器播种。我们通过time()函数将当前时间的值提供给它来实现这一点。

现在，当我们调用rand()时，每次都会产生一个新的随机数。

    #include <stdio.h>

    int random_number(int min_num, int max_num);

    int main(void)
    {
        printf("Min : 1 Max : 40 %d\n", random_number(1,40));
        printf("Min : 100 Max : 1000 %d\n",random_number(100,1000));
        return 0;
    }

    int random_number(int min_num, int max_num)
    {
        int result = 0, low_num = 0, hi_num = 0;

        if (min_num < max_num)
        {
            low_num = min_num;
            hi_num = max_num + 1; // include max_num in output
        } else {
            low_num = max_num + 1; // include max_num in output
            hi_num = min_num;
        }

        srand(time(NULL));
        result = (rand() % (hi_num - low_num)) + low_num;
        return result;
    }

下面是我的方法(围绕rand()的包装器):

我还扩展到允许min为INT_MIN而max为INT_MAX的情况，这通常不可能单独使用rand()，因为它返回从0到RAND_MAX的值，包括(1/2范围)。

像这样使用它:

const int MIN = 1;
const int MAX = 1024;
// Get a pseudo-random number between MIN and MAX, **inclusive**.
// Seeding of the pseudo-random number generator automatically occurs
// the very first time you call it.
int random_num = utils_rand(MIN, MAX);

定义和氧描述:

#include <assert.h>
#include <stdbool.h>
#include <stdlib.h>

/// \brief      Use linear interpolation to rescale, or "map" value `val` from range
///             `in_min` to `in_max`, inclusive, to range `out_min` to `out_max`, inclusive.
/// \details    Similar to Arduino's ingenious `map()` function:
///             https://www.arduino.cc/reference/en/language/functions/math/map/
///
/// TODO(gabriel): turn this into a gcc statement expression instead to prevent the potential for
/// the "double evaluation" bug. See `MIN()` and `MAX()` above.
#define UTILS_MAP(val, in_min, in_max, out_min, out_max) \
    (((val) - (in_min)) * ((out_max) - (out_min)) / ((in_max) - (in_min)) + (out_min))

/// \brief      Obtain a pseudo-random integer value between `min` and `max`, **inclusive**.
/// \details    1. If `(max - min + 1) > RAND_MAX`, then the range of values returned will be
///             **scaled** to the range `max - min + 1`, and centered over the center of the
///             range at `(min + max)/2`. Scaling the numbers means that in the case of scaling,
///             not all numbers can even be reached. However, you will still be assured to have
///             a random distribution of numbers across the full range.
///             2. Also, the first time per program run that you call this function, it will
///             automatically seed the pseudo-random number generator with your system's
///             current time in seconds.
/// \param[in]  min         The minimum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \param[in]  max         The maximum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \return     A pseudo-random integer value between `min` and `max`, **inclusive**.
int utils_rand(int min, int max)
{
    static bool first_run = true;
    if (first_run)
    {
        // seed the pseudo-random number generator with the seconds time the very first run
        time_t time_now_sec = time(NULL);
        srand(time_now_sec);
        first_run = false;
    }

    int range = max - min + 1;
    int random_num = rand();  // random num from 0 to RAND_MAX, inclusive

    if (range > RAND_MAX)
    {
        static_assert(
            sizeof(long int) > sizeof(int),
            "This must be true or else the below mapping/scaling may have undefined overflow "
            "and not work properly. In such a case, try casting to `long long int` instead of "
            "just `long int`, and update this static_assert accordingly.");

        random_num = UTILS_MAP((long int)random_num, (long int)0, (long int)RAND_MAX, (long int)min,
                               (long int)max);
        return random_num;
    }

    // This is presumably a faster approach than the map/scaling function above, so do this faster
    // approach below whenever you don't **have** to do the more-complicated approach above.
    random_num %= range;
    random_num += min;

    return random_num;
}

参见:

[我在写下上面的答案后发现了这个问答，但它显然非常相关，他们对非缩放范围的情况做了同样的事情]我如何从rand()中获得特定的数字范围? [我需要进一步研究和阅读这个答案-似乎有一些好的观点，保持良好的随机性不使用模量]我如何从rand()得到一个特定的数字范围? http://c-faq.com/lib/randrange.html

在现代的x86_64 cpu上，您可以通过_rdrand64_step()使用硬件随机数生成器。

示例代码:

#include <immintrin.h>

uint64_t randVal;
if(!_rdrand64_step(&randVal)) {
  // Report an error here: random number generation has failed!
}
// If no error occured, randVal contains a random 64-bit number

看看ISAAC(间接，移动，积累，添加和计数)。它是均匀分布的，平均循环长度为2^8295。