I got, here you have used functional programming term to introduce the use of map(), filter() and reduce() in your code but you should not use it here for this scenario as functional programming refers to the implementation of your problem by using functions (modular design).
In your case, you cannot use filter(), reduce() to get the expected result as these functions does not provide you a flexible way to control the program's control.
You can try something like this but I don't want you to use that, you may get None if the condition is not satisfied in case of map(). Using filter() / reduce() does not make sense.
Here, I have tried to make it working as you expect.
>>> def f(tup):
... items = []
... if tup[0] == 'two':
... for s in tup[1].items():
... if s[0] == "two-two":
... for a in s[1].items():
... print(a[1])
... items.append(a[1])
... return items
... else:
... return None
...
>>> test
{'one': 1, 'two': {'two-two': {'two-two-two': 222, 'three-three-three': 333}},
'three': 3}
>>>
>>> out = list(map(f, test.items()))
222
333
>>> out
[None, [222, 333], None]
>>>
>>> out[1]
[222, 333]
>>>
map(), filter() are bascially used to work on iterables like list, tuple, dictionary, set etc. and produce another iterables by performaing opeartions on items. filter() allows us to filter data (picking even numbers from a list).
reduce() is bascially used to work on iterables and reducing them to a single value (e.g. getting sum of list of numbers).
Initializations
>>> l = [9, 4, 3, 2, 1]
>>> d = {'first': 'Rishikesh', 'last': 'Agrawani'}
>>> t = (3, 4, 5)
>>>
Using map()
>>> # Using map()
...
>>> map_obj = map(lambda n: n ** 2, l)
>>> map_obj
<map object at 0x0000016DAF88B6D8>
>>>
>>> squares = list(map_obj) # list(map(lambda n: n ** 2, l))
>>> squares
[81, 16, 9, 4, 1]
>>>
>>> details = {k + '-name': v for k, v in d.items()}
>>> details
{'first-name': 'Rishikesh', 'last-name': 'Agrawani'}
>>>
>>> details = dict(map(lambda tup: (tup[0] + '_name', tup[1]), d.items()))
>>> details
{'first_name': 'Rishikesh', 'last_name': 'Agrawani'}
>>>
Using filter()
>>> # Using filter() - let's filter even numbers from list
...
>>> filter_obj = filter(lambda n: n % 2 == 0, l)
>>> filter_obj
<filter object at 0x0000016DAF88B908>
>>>
>>> evens = list(filter_obj)
>>> evens
[4, 2]
>>>
Using reduce()
>>> # Using reduce() - finding sum of al numbers in a list
... # i.e. reducing list of values to a single value
...
>>> from functools import reduce
>>>
>>> total = reduce(lambda n1, n2: n1 + n2, l)
>>> total
19
>>>