假设你有一个32位整数，为什么不把a移到前16位的一半，把B移到另一半?

def vec_pack(vec):
    return vec[0] + vec[1] * 65536;


def vec_unpack(number):
    return [number % 65536, number // 65536];

除了尽可能节省空间和计算成本之外，一个非常酷的副作用是，您可以在填充的数字上进行向量计算。

a = vec_pack([2,4])
b = vec_pack([1,2])

print(vec_unpack(a+b)) # [3, 6] Vector addition
print(vec_unpack(a-b)) # [1, 2] Vector subtraction
print(vec_unpack(a*2)) # [4, 8] Scalar multiplication

给定正整数A和B，设D = A的位数，E= B的位数 结果可以是D, 0, E, 0, a和B的串联。

示例:A = 300, B = 12。D = 3, E=2 result = 302030012。 这利用了一个事实，即唯一以0开头的数字是0，

优点:易于编码，易于解码，人类可读，有效数字可以先比较，潜在的比较无需计算，简单的错误检查。

缺点:结果的大小是个问题。不过没关系，我们为什么要在电脑里存储无界整数呢。

下面是基于@nawfal给出的方法将@DoctorJ的代码扩展到无界整数。它可以编码和解码。它适用于普通数组和numpy数组。

#!/usr/bin/env python
from numbers import Integral    

def tuple_to_int(tup):
    """:Return: the unique non-negative integer encoding of a tuple of non-negative integers."""
    if len(tup) == 0:  # normally do if not tup, but doesn't work with np
        raise ValueError('Cannot encode empty tuple')
    if len(tup) == 1:
        x = tup[0]
        if not isinstance(x, Integral):
            raise ValueError('Can only encode integers')
        return x
    elif len(tup) == 2:
        # print("len=2")
        x, y = tuple_to_int(tup[0:1]), tuple_to_int(tup[1:2])  # Just to validate x and y

        X = 2 * x if x >= 0 else -2 * x - 1  # map x to positive integers
        Y = 2 * y if y >= 0 else -2 * y - 1  # map y to positive integers
        Z = (X * X + X + Y) if X >= Y else (X + Y * Y)  # encode

        # Map evens onto positives
        if (x >= 0 and y >= 0):
            return Z // 2
        elif (x < 0 and y >= 0 and X >= Y):
            return Z // 2
        elif (x < 0 and y < 0 and X < Y):
            return Z // 2
        # Map odds onto negative
        else:
            return (-Z - 1) // 2
    else:
        return tuple_to_int((tuple_to_int(tup[:2]),) + tuple(tup[2:]))  # ***speed up tuple(tup[2:])?***


def int_to_tuple(num, size=2):
    """:Return: the unique tuple of length `size` that encodes to `num`."""
    if not isinstance(num, Integral):
        raise ValueError('Can only encode integers (got {})'.format(num))
    if not isinstance(size, Integral) or size < 1:
        raise ValueError('Tuple is the wrong size ({})'.format(size))
    if size == 1:
        return (num,)
    elif size == 2:

        # Mapping onto positive integers
        Z = -2 * num - 1 if num < 0 else 2 * num

        # Reversing Pairing
        s = isqrt(Z)
        if Z - s * s < s:
            X, Y = Z - s * s, s
        else:
            X, Y = s, Z - s * s - s

        # Undoing mappint to positive integers
        x = (X + 1) // -2 if X % 2 else X // 2  # True if X not divisible by 2
        y = (Y + 1) // -2 if Y % 2 else Y // 2  # True if Y not divisible by 2

        return x, y

    else:
        x, y = int_to_tuple(num, 2)
        return int_to_tuple(x, size - 1) + (y,)


def isqrt(n):
    """":Return: the largest integer x for which x * x does not exceed n."""
    # Newton's method, via http://stackoverflow.com/a/15391420
    x = n
    y = (x + 1) // 2
    while y < x:
        x = y
        y = (x + n // x) // 2
    return x

你正在寻找一个双射NxN - >n映射。这些是用于例如燕尾。请看这个PDF文件，它介绍了所谓的配对函数。维基百科介绍了一个特定的配对函数，即康托配对函数:

备注:三个

As others have made clear, if you plan to implement a pairing function, you may soon find you need arbitrarily large integers (bignums). If you don't want to make a distinction between the pairs (a, b) and (b, a), then sort a and b before applying the pairing function. Actually I lied. You are looking for a bijective ZxZ -> N mapping. Cantor's function only works on non-negative numbers. This is not a problem however, because it's easy to define a bijection f : Z -> N, like so: f(n) = n * 2 if n >= 0 f(n) = -n * 2 - 1 if n < 0

看看这个:http://en.wikipedia.org/wiki/Pigeonhole_principle。如果A, B, C是同一类型，就不能做。如果A和B是16位整数，而C是32位整数，那么您可以简单地使用移位。

哈希算法的本质是它们不能为每个不同的输入提供唯一的哈希。

尽管Stephan202的答案是唯一真正通用的答案，但对于有限范围内的整数，您可以做得更好。例如，如果你的范围是0..1万，那么你可以这样做:

#define RANGE_MIN 0
#define RANGE_MAX 10000

unsigned int merge(unsigned int x, unsigned int y)
{
    return (x * (RANGE_MAX - RANGE_MIN + 1)) + y;
}

void split(unsigned int v, unsigned int &x, unsigned int &y)
{
    x = RANGE_MIN + (v / (RANGE_MAX - RANGE_MIN + 1));
    y = RANGE_MIN + (v % (RANGE_MAX - RANGE_MIN + 1));
}

结果可以适用于单个整数，其范围可达整数类型基数的平方根。这种打包方法比Stephan202更通用的方法效率稍高。它的解码也简单得多;对于初学者来说，不需要平方根:)