### Problem Context

The [Fibonacci](http://en.wikipedia.org/wiki/Fibonacci_number) sequence is traditionally used to explain tree recursion.  

```python
def fibonacci(n):
    if n in [0, 1]:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)
```

This algorithm serves welll its educative purpose but it's [tremendously inefficient](http://mitpress.mit.edu/sicp/full-text/book/book-Z-H-11.html#%_sec_1.2.2), not only because of recursion, but because we invoke the fibonacci function twice, and the right branch of recursion (i.e. `fibonacci(n-2)`) recalculates all the Fibonacci numbers already calculated by the left branch (i.e. `fibonacci(n-1)`).

This algorithm is so inefficient that the time to calculate any Fibonacci number over 50 is simply too much. You may go for a cup of coffee or go take a nap while you wait for the answer. But if you try it here in Code Wars you will most likely get a code timeout before any answers.

For this particular Kata we want to **implement the memoization solution**. This will be cool because it will let us *keep using the tree recursion* algorithm while still keeping it sufficiently optimized to get an answer very rapidly.

The trick of the memoized version is that we will keep a cache data structure (most likely an associative array) where we will store the Fibonacci numbers as we calculate them. When a Fibonacci number is calculated, we first look it up in the cache, if it's not there, we calculate it and put it in the cache, otherwise we returned the cached number.

Refactor the function into a recursive Fibonacci function that using  a memoized data structure avoids the deficiencies of tree recursion Can you make it so the memoization cache is private to this function?

```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 = "from functools import wraps\n\n# very rudimentary implementation of a cache decorator\n# python 3's functools.lru_cache or its backport should be favored\ndef cache(f):\n    _cache = {}\n    @wraps(f)\n    def wrapped(n):\n        if n in _cache:\n            return _cache[n]\n        else:\n            result = f(n)\n            _cache[n] = result\n            return result\n    return wrapped\n    \n@cache\ndef fibonacci(n):\n    if n in [0, 1]:\n        return n\n    return fibonacci(n - 1) + fibonacci(n - 2)"
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'fibonacci'
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: 31124