用python怎么写产生3000个随机整数，用归治法进行归并排序和快速排序

用Python来产生3000个随机整数，可以使用 random 模块的 randint() 函数，如：numbers = [random.randint(1, 3000) for _ in range(3000)]。归并排序可以使用 merge_sort() 函数，而快速排序可以使用 quick_sort() 函数。

相关问题

用Python写随机产生3000个整数，分别用蛮力法和归治法和减治法进行排序

你可以使用 Python 的 `random` 模块来随机生成 3000 个整数。例如：

import random

numbers = [random.randint(1, 10000) for _ in range(3000)]

对于排序，你可以使用蛮力法、归并排序和快速排序。

蛮力法：

def brute_force_sort(numbers):
    for i in range(len(numbers)):
        for j in range(i+1, len(numbers)):
            if numbers[i] > numbers[j]:
                numbers[i], numbers[j] = numbers[j], numbers[i]
    return numbers

归并排序：

def merge_sort(numbers):
    if len(numbers) <= 1:
        return numbers

    mid = len(numbers) // 2
    left = numbers[:mid]
    right = numbers[mid:]

    left = merge_sort(left)
    right = merge_sort(right)

    return merge(left, right)

def merge(left, right):
    result = []
    i = j = 0

    while i < len(left) and j < len(right):
        if left[i] < right[j]:
            result.append(left[i])
            i += 1
        else:
            result.append(right[j])
            j += 1

    result += left[i:]
    result += right[j:]

    return result

快速排序：

def quick_sort(numbers):
    if len(numbers) <= 1:
        return numbers

    pivot = numbers[0]
    left = [x for x in numbers[1:] if x <= pivot]
    right = [x for x in numbers[1:] if x > pivot]

    return quick_sort(left) + [pivot] + quick_sort(right)

用python编写程序产生30000个随机整数，用蛮力法进行选择排序和冒泡排序，用归治法进行归并排序和快速排序，用减治法进行插入排序和堆排序；输出递增结果；统计每一种排序运行所花费的时间。

好的，我理解了你的要求。以下是 Python 代码实现：

import random
import time

# 产生30000个随机整数
nums = [random.randint(1, 100000) for _ in range(30000)]

# 蛮力法 - 选择排序
def selection_sort(nums):
    n = len(nums)
    for i in range(n):
        min_idx = i
        for j in range(i+1, n):
            if nums[j] < nums[min_idx]:
                min_idx = j
        nums[i], nums[min_idx] = nums[min_idx], nums[i]

# 蛮力法 - 冒泡排序
def bubble_sort(nums):
    n = len(nums)
    for i in range(n):
        for j in range(n-i-1):
            if nums[j] > nums[j+1]:
                nums[j], nums[j+1] = nums[j+1], nums[j]

# 归治法 - 归并排序
def merge_sort(nums):
    if len(nums) <= 1:
        return nums
    mid = len(nums) // 2
    left = merge_sort(nums[:mid])
    right = merge_sort(nums[mid:])
    return merge(left, right)

def merge(left, right):
    res = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] < right[j]:
            res.append(left[i])
            i += 1
        else:
            res.append(right[j])
            j += 1
    res += left[i:]
    res += right[j:]
    return res

# 归治法 - 快速排序
def quick_sort(nums):
    if len(nums) <= 1:
        return nums
    pivot = nums[0]
    left = [x for x in nums[1:] if x < pivot]
    right = [x for x in nums[1:] if x >= pivot]
    return quick_sort(left) + [pivot] + quick_sort(right)

# 减治法 - 插入排序
def insertion_sort(nums):
    n = len(nums)
    for i in range(1, n):
        j = i
        while j > 0 and nums[j] < nums[j-1]:
            nums[j], nums[j-1] = nums[j-1], nums[j]
            j -= 1

# 减治法 - 堆排序
def heap_sort(nums):
    def heapify(nums, n, i):
        largest = i
        l = 2 * i + 1
        r = 2 * i + 2
        if l < n and nums[l] > nums[largest]:
            largest = l
        if r < n and nums[r] > nums[largest]:
            largest = r
        if largest != i:
            nums[i], nums[largest] = nums[largest], nums[i]
            heapify(nums, n, largest)

    n = len(nums)
    for i in range(n//2-1, -1, -1):
        heapify(nums, n, i)
    for i in range(n-1, 0, -1):
        nums[0], nums[i] = nums[i], nums[0]
        heapify(nums, i, 0)

# 统计每种排序运行所花费的时间
start = time.time()
selection_sort(nums)
end = time.time()
print("选择排序所花费的时间：", end-start, "秒")

start = time.time()
bubble_sort(nums)
end = time.time()
print("冒泡排序所花费的时间：", end-start, "秒")

start = time.time()
merge_sort(nums)
end = time.time()
print("归并排序所花费的时间：", end-start, "秒")

start = time.time()
quick_sort(nums)
end = time.time()
print("快速排序所花费的时间：", end-start, "秒")

start = time.time()
insertion_sort(nums)
end = time.time()
print("插入排序所花费的时间：", end-start, "秒")

start = time.time()
heap_sort(nums)
end = time.time()
print("堆排序所花费的时间：", end-start, "秒")

# 输出递增结果
print(nums)

希望能够帮到你！