Strings A and B are K-similar (for some non-negative integer K) if we can swap the positions of two letters in A exactly K times so that the resulting string equals B.
Given two anagrams A and B, return the smallest K for which A and B are K-similar.
Example 1:
Input: A = "ab", B = "ba"
Output: 1


Example 2:
Input: A = "abc", B = "bca"
Output: 2


Example 3:
Input: A = "abac", B = "baca"
Output: 2


Example 4:
Input: A = "aabc", B = "abca"
Output: 2



Note:

1 <= A.length == B.length <= 20
A and B contain only lowercase letters from the set {'a', 'b', 'c', 'd', 'e', 'f'}

```python

USER_FILENAME = "<user_code>"
import sys, json, builtins
import math, heapq, bisect, itertools, functools, collections, statistics, fractions, decimal, operator, array, random, re, string, os, pathlib
try:
    import resource as _res
except Exception:
    _res = None
from collections import Counter, defaultdict, deque, OrderedDict
from functools import lru_cache, reduce
from itertools import accumulate, permutations, combinations, product
from math import gcd, ceil, floor, sqrt
from decimal import Decimal
try:
    from typing import *
except Exception:
    pass
try:
    sys.setrecursionlimit(1_000_000)
except Exception:
    pass
try:
    import site as _site
    try:
        _sys_sites = _site.getsitepackages() if hasattr(_site, "getsitepackages") else []
        for _p in _sys_sites:
            if _p and _p not in sys.path:
                sys.path.append(_p)
    except Exception:
        pass
    try:
        _usp = _site.getusersitepackages()
        if isinstance(_usp, str):
            _usp = [_usp]
        for _p in _usp:
            if _p and _p not in sys.path:
                sys.path.append(_p)
    except Exception:
        pass
except Exception:
    pass

def _disabled_input(*args, **kwargs):
    raise RuntimeError("input() is disabled in callable mode")
builtins.input = _disabled_input

ns = {"__name__": "__judge__"}  # prevent if __name__ == "__main__" blocks
for _k, _v in list(globals().items()):
    if not _k.startswith("_"):
        ns[_k] = _v
_CODE = "'''\n'ab'\n'ba'\n1\n\n'abc' -> 'acb' -> 'bca'\n'bca'\n2\n\n'abac' -> 'baac' -> 'baca'\n'baca'\n2\n\n'aabc' -> 'acba' -> 'abca'\n'abca'\n2\n\n* See the problem as a graph problem.\n* Nodes are the strings.\n* Two nodes are conneted to each order if the one string is equal to the\n  other if we swap two chars.\n* The problem boils down to find the shortest path between A and B.\n* Since this is an unweigthed graph, the shortest path can be found by\n  traversing the graph in BFS.\n  \n  \n'abc' -> 'bac'\n      -> 'cba'\n      -> 'acb'\n      \n* This approach doesn't sound an efficient approach because for every node\n  we'd need to generated its adjcent nodes.\n  \n* This sounds like an optimization problem.\n\n'abcd'  --> 'bcd'\n'adbc'      'dbc'\n\n* If the first char from A and B are equal, recurse on the remaining string.\n* Else, swap A so it first char match and recurse. If the target char repeats,\n  try swapping all of them and consider the one that leads to the smallest K.\n  \n  \n('abac', 'baca') = 1 + ('aac', 'aca')\n('aac', 'aca') = ('ac', 'ca')\n('ac', 'ca') = 1 + ('a', 'a')\n('a', 'a') = 0\n\n'''\n\nclass Solution:\n    def kSimilarity(self, A: str, B: str) -> int:\n        return do_kSimilarity(list(A), list(B), {})\n                \n                \ndef do_kSimilarity(A, B, memo):\n    if (tuple(A), tuple(B)) in memo:\n        return memo[(tuple(A), tuple(B))]\n    if A == B:\n        return 0\n\n    if A[0] == B[0]:\n        return do_kSimilarity(A[1:], B[1:], memo)\n    else:\n        swaps = []\n        for i, char in enumerate(A):\n            if char == B[0]:\n                swaps.append(i)\n        \n        k = float('inf')\n        for swap in swaps:\n            A[0], A[swap] = A[swap], A[0]\n            k = min(k, 1 + do_kSimilarity(A[1:], B[1:], memo))\n            A[0], A[swap] = A[swap], A[0]\n        \n        memo[(tuple(A), tuple(B))] = k\n        return k"
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'kSimilarity'
if _fn_name:
    if "Solution" in ns:
        try:
            _obj = ns["Solution"]()
            if hasattr(_obj, _fn_name):
                _target = getattr(_obj, _fn_name)
        except Exception:
            _target = None
    if _target is None and _fn_name in ns and callable(ns[_fn_name]):
        _target = ns[_fn_name]
# Fallback: if there's exactly one user-defined function, use it
if _target is None:
    _cands = [v for k, v in ns.items() if callable(v) and getattr(v, "__module__", "") in ("__judge__", "__main__")]
    _user_funcs = [c for c in _cands if getattr(c, "__name__", "").startswith("_") is False]
    if len(_user_funcs) == 1:
        _target = _user_funcs[0]
if _target is None:
    raise RuntimeError(f"Could not resolve callable '{_fn_name}'")

_raw = sys.stdin.read().strip()
if _raw:
    _parsed = json.loads(_raw)
    if isinstance(_parsed, dict):
        _kwargs = _parsed.get("kwargs", {})
        _args = _parsed.get("args", [])
    else:
        _args, _kwargs = _parsed, {}
else:
    _args, _kwargs = [], {}
if not isinstance(_args, (list, tuple)):
    _args = [_args]
_res = _target(*_args, **_kwargs)
try:
    sys.stdout.write(repr(_res) + "\n")
except Exception:
    pass

```

Measured memory_bytes: 7402