Creating a nested dictionary from a flattened dictionary

output = {}

for k, v in source.items():
    # always start at the root.
    current = output

    # This is the part you're struggling with.
    pieces = k.split('_')

    # iterate from the beginning until the second to last place
    for piece in pieces[:-1]:
       if not piece in current:
          # if a dict doesn't exist at an index, then create one
          current[piece] = {}

       # as you walk into the structure, update your current location
       current = current[piece]

    # The reason you're using the second to last is because the last place
    # represents the place you're actually storing the item
    current[pieces[-1]] = v

Here’s one way using collections.defaultdict, borrowing heavily from this previous answer. There are 3 steps:

1. Create a nested defaultdict of defaultdict objects.
2. Iterate items in flat input dictionary.
3. Build defaultdict result according to the structure derived from splitting keys by _, using getFromDict to iterate the result dictionary.

This is a complete example:

from collections import defaultdict
from functools import reduce
from operator import getitem

def getFromDict(dataDict, mapList):
    """Iterate nested dictionary"""
    return reduce(getitem, mapList, dataDict)

# instantiate nested defaultdict of defaultdicts
tree = lambda: defaultdict(tree)
d = tree()

# iterate input dictionary
for k, v in flat.items():
    *keys, final_key = k.split('_')
    getFromDict(d, keys)[final_key] = v

{'X': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}},
 'Y': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}}}

As a final step, you can convert your defaultdict to a regular dict, though usually this step is not necessary.

def default_to_regular_dict(d):
    """Convert nested defaultdict to regular dict of dicts."""
    if isinstance(d, defaultdict):
        d = {k: default_to_regular_dict(v) for k, v in d.items()}
    return d

# convert back to regular dict
res = default_to_regular_dict(d)

The other answers are cleaner, but since you mentioned recursion we do have other options.

def nest(d):
    _ = {}
    for k in d:
        i = k.find('_')
        if i == -1:
            _[k] = d[k]
            continue
        s, t = k[:i], k[i+1:]
        if s in _:
            _[s][t] = d[k]
        else:
            _[s] = {t:d[k]}
    return {k:(nest(_[k]) if type(_[k])==type(d) else _[k]) for k in _}

You can use itertools.groupby:

import itertools, json
flat = {'Y_a_two': 20, 'Y_a_one': 10, 'X_b_two': 20, 'X_b_one': 10, 'X_a_one': 10, 'X_a_two': 20, 'Y_b_two': 20, 'Y_b_one': 10}
_flat = [[*a.split('_'), b] for a, b in flat.items()]
def create_dict(d): 
  _d = {a:list(b) for a, b in itertools.groupby(sorted(d, key=lambda x:x[0]), key=lambda x:x[0])}
  return {a:create_dict([i[1:] for i in b]) if len(b) > 1 else b[0][-1] for a, b in _d.items()}

print(json.dumps(create_dict(_flat), indent=3))

Output:

{
 "Y": {
    "b": {
      "two": 20,
      "one": 10
    },
    "a": {
      "two": 20,
      "one": 10
    }
 },
  "X": {
     "b": {
     "two": 20,
     "one": 10
   },
    "a": {
     "two": 20,
     "one": 10
   }
 }
}

Another non-recursive solution with no imports. Splitting the logic between inserting each key-value pair of the flat dict and mapping over key-value pairs of the flat dict.

def insert(dct, lst):
    """
    dct: a dict to be modified inplace.
    lst: list of elements representing a hierarchy of keys
    followed by a value.

    dct = {}
    lst = [1, 2, 3]

    resulting value of dct: {1: {2: 3}}
    """
    for x in lst[:-2]:
        dct[x] = dct = dct.get(x, dict())

    dct.update({lst[-2]: lst[-1]})


def unflat(dct):
    # empty dict to store the result
    result = dict()

    # create an iterator of lists representing hierarchical indices followed by the value
    lsts = ([*k.split("_"), v] for k, v in dct.items())

    # insert each list into the result
    for lst in lsts:
        insert(result, lst)

    return result


result = unflat(flat)
# {'X': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}},
# 'Y': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}}}

Here is a reasonably readable recursive result:

def unflatten_dict(a, result = None, sep = '_'):

    if result is None:
        result = dict()

    for k, v in a.items():
        k, *rest = k.split(sep, 1)
        if rest:
            unflatten_dict({rest[0]: v}, result.setdefault(k, {}), sep = sep)
        else:
            result[k] = v

    return result


flat = {'X_a_one': 10,
        'X_a_two': 20,
        'X_b_one': 10,
        'X_b_two': 20,
        'Y_a_one': 10,
        'Y_a_two': 20,
        'Y_b_one': 10,
        'Y_b_two': 20}

print(unflatten_dict(flat))
# {'X': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}}, 
#  'Y': {'a': {'one': 10, 'two': 20}, 'b': {'one': 10, 'two': 20}}}

This is based on a couple of the above answers, uses no imports and is only tested in python 3.

Install ndicts

pip install ndicts

Then in your script

from ndicts.ndicts import NestedDict

flat = {'X_a_one': 10,
        'X_a_two': 20, 
        'X_b_one': 10,
        'X_b_two': 20, 
        'Y_a_one': 10,
        'Y_a_two': 20,
        'Y_b_one': 10,
        'Y_b_two': 20}

nd = NestedDict()
for key, value in flat.items():
    n_key = tuple(key.split("_"))
    nd[n_key] = value

If you need the result as a dictionary:

>>> nd.to_dict()
{'X': {'a': {'one': 10, 'two': 20}, 
       'b': {'one': 10, 'two': 20}}, 
 'Y': {'a': {'one': 10, 'two': 20},
       'b': {'one': 10, 'two': 20}}}