（1）产生 1000 个伪随机数，并依次存储在一个数据文件中； （2）对此 1000 个伪随机数序列分别用冒泡排序、快速排序、希尔排序、 堆排序、归并排序方法进行排序，并比较它们的运行时间。

好的，可以使用Python内置的time模块来计算各种排序算法的运行时间，并将排序后的结果分别存储在不同的文件中。具体实现如下所示：

import random
import time

# 产生1000个随机数，并保存到文件中
with open('data.txt', 'w') as f:
    nums = [random.randint(1, 1000) for _ in range(1000)]
    f.write('\n'.join(map(str, nums)))

# 冒泡排序
def bubble_sort(nums):
    n = len(nums)
    for i in range(n):
        for j in range(0, n - i - 1):
            if nums[j] > nums[j + 1]:
                nums[j], nums[j + 1] = nums[j + 1], nums[j]

# 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)

# 希尔排序
def shell_sort(nums):
    n = len(nums)
    gap = n // 2
    while gap > 0:
        for i in range(gap, n):
            temp = nums[i]
            j = i
            while j >= gap and nums[j - gap] > temp:
                nums[j] = nums[j - gap]
                j -= gap
            nums[j] = temp
        gap //= 2

# 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)

# 归并排序
def merge_sort(nums):
    def merge(left, right):
        result = []
        i, j = 0, 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

    if len(nums) <= 1:
        return nums
    mid = len(nums) // 2
    left = nums[:mid]
    right = nums[mid:]
    left = merge_sort(left)
    right = merge_sort(right)
    return merge(left, right)

# 读取数据文件中的随机数
with open('data.txt', 'r') as f:
    nums = [int(x) for x in f.read().splitlines()]

# 冒泡排序
start_time = time.time()
bubble_sort(nums.copy())
end_time = time.time()
with open('bubble_sort.txt', 'w') as f:
    f.write('\n'.join(map(str, nums)))
print('Bubble sort time:', end_time - start_time)

# 快速排序
start_time = time.time()
sorted_nums = quick_sort(nums.copy())
end_time = time.time()
with open('quick_sort.txt', 'w') as f:
    f.write('\n'.join(map(str, sorted_nums)))
print('Quick sort time:', end_time - start_time)

# 希尔排序
start_time = time.time()
shell_sort(nums.copy())
end_time = time.time()
with open('shell_sort.txt', 'w') as f:
    f.write('\n'.join(map(str, nums)))
print('Shell sort time:', end_time - start_time)

# 堆排序
start_time = time.time()
heap_sort(nums.copy())
end_time = time.time()
with open('heap_sort.txt', 'w') as f:
    f.write('\n'.join(map(str, nums)))
print('Heap sort time:', end_time - start_time)

# 归并排序
start_time = time.time()
sorted_nums = merge_sort(nums.copy())
end_time = time.time()
with open('merge_sort.txt', 'w') as f:
    f.write('\n'.join(map(str, sorted_nums)))
print('Merge sort time:', end_time - start_time)

在这个示例代码中，我们首先使用文件操作将1000个随机数保存到文件中，然后分别读取数据文件中的随机数，并使用各种排序算法进行排序。在排序过程中，我们使用Python内置的time模块来计算每种排序算法的运行时间，并将排序后的结果保存到不同的文件中。最后，我们打印每种排序算法的运行时间。