Python – 混合嵌套元组中的元素频率

有时，在处理Python数据时，我们可能会遇到一个问题，即我们在单个元组中包含嵌套和非嵌套形式的数据，我们希望计算其中的元素频率。这类问题可能出现在 Web 开发和数据科学等领域。让我们讨论可以执行此任务的某些方式。

Input : test_tuple = (5, (6, (7, 8, 6)))
Output : {5: 1, 6: 2, 7: 1, 8: 1}

Input : test_tuple = (5, 6, 7, 8)
Output : {5: 1, 6: 1, 7: 1, 8: 1}

方法#1：使用递归+循环
这个问题的解决包括两个步骤。首先，我们使用递归对元组进行扁平化，然后使用循环以蛮力方式执行计数。

# Python3 code to demonstrate working of 
# Elements Frequency in Mixed Nested Tuple
# Using recursion + loop
  
# helper_fnc
def flatten(test_tuple):
    for tup in test_tuple:
        if isinstance(tup, tuple):
            yield from flatten(tup)
        else:
            yield tup
  
# initializing tuple
test_tuple = (5, 6, (5, 6), 7, (8, 9), 9)
  
# printing original tuple
print("The original tuple : " + str(test_tuple))
  
# Elements Frequency in Mixed Nested Tuple
# Using recursion + loop
res = {}
for ele in flatten(test_tuple):
    if ele not in res:
        res[ele] = 0
    res[ele] += 1
  
# printing result 
print("The elements frequency : " + str(res))

输出 ：

The original tuple : (5, 6, (5, 6), 7, (8, 9), 9)
The elements frequency : {5: 2, 6: 2, 7: 1, 8: 1, 9: 2}

方法#2：使用Counter() + resursion
这是可以解决此问题的另一种方式。在此，我们使用 Counter() 来执行计算元素的任务。

# Python3 code to demonstrate working of 
# Elements Frequency in Mixed Nested Tuple
# Using recursion + Counter()
from collections import Counter
  
# helper_fnc
def flatten(test_tuple):
    for tup in test_tuple:
        if isinstance(tup, tuple):
            yield from flatten(tup)
        else:
            yield tup
  
# initializing tuple
test_tuple = (5, 6, (5, 6), 7, (8, 9), 9)
  
# printing original tuple
print("The original tuple : " + str(test_tuple))
  
# Elements Frequency in Mixed Nested Tuple
# Using recursion + Counter()
res = dict(Counter(flatten(test_tuple)))
  
# printing result 
print("The elements frequency : " + str(res))

输出 ：

The original tuple : (5, 6, (5, 6), 7, (8, 9), 9)
The elements frequency : {5: 2, 6: 2, 7: 1, 8: 1, 9: 2}