You want to schedule a list of jobs in d days. Jobs are dependent (i.e To work on the i-th job, you have to finish all the jobs j where 0 <= j < i).
You have to finish at least one task every day. The difficulty of a job schedule is the sum of difficulties of each day of the d days. The difficulty of a day is the maximum difficulty of a job done in that day.
Given an array of integers jobDifficulty and an integer d. The difficulty of the i-th job is jobDifficulty[i].
Return the minimum difficulty of a job schedule. If you cannot find a schedule for the jobs return -1.
 
Example 1:

Input: jobDifficulty = [6,5,4,3,2,1], d = 2
Output: 7
Explanation: First day you can finish the first 5 jobs, total difficulty = 6.
Second day you can finish the last job, total difficulty = 1.
The difficulty of the schedule = 6 + 1 = 7 

Example 2:
Input: jobDifficulty = [9,9,9], d = 4
Output: -1
Explanation: If you finish a job per day you will still have a free day. you cannot find a schedule for the given jobs.

Example 3:
Input: jobDifficulty = [1,1,1], d = 3
Output: 3
Explanation: The schedule is one job per day. total difficulty will be 3.

Example 4:
Input: jobDifficulty = [7,1,7,1,7,1], d = 3
Output: 15

Example 5:
Input: jobDifficulty = [11,111,22,222,33,333,44,444], d = 6
Output: 843

 
Constraints:

1 <= jobDifficulty.length <= 300
0 <= jobDifficulty[i] <= 1000
1 <= d <= 10

```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 = 'class Solution:\n    def minDifficulty( self, jobDifficulty: List[ int ], d: int ) -> int:\n        num_jobs = len( jobDifficulty )\n        if num_jobs < d:\n            return -1\n        \n        # The dp cache only keeps the best value up to that point for that number of days\n        # This can be further optimized to only need two arrays since we only look at the previous row\n        dp = [ [ -1 for _ in range( num_jobs ) ] for _ in range( d ) ]\n        \n        # First day everything is just the max up to that point\n        max_so_far = -math.inf\n        for job in range( num_jobs ):\n            max_so_far = max( max_so_far, jobDifficulty[ job ] )\n            dp[ 0 ][ job ] = max_so_far\n        \n        # Now do the rest\n        for day in range( 1, d ):\n            # In order to determine best difficulty, keep monotonic decreasing stack of difficulties\n            # This will retain useful information up to each value and remove the need to loop backwards\n            stack = []\n            for job in range( day, num_jobs ): # Must be at least as many days as jobs\n                # This value on its own plus the best of the previous\n                dp[ day ][ job ] = dp[ day - 1 ][ job - 1 ] + jobDifficulty[ job ]\n                # Keep stack in decreasing order\n                while stack and jobDifficulty[ stack[ -1 ] ] <= jobDifficulty[ job ]:\n                    index = stack.pop() \n                    dp[ day ][ job ] = min( dp[ day ][ job ], dp[ day ][ index ] - jobDifficulty[ index ] + jobDifficulty[ job ] )\n                if stack:\n                    dp[ day ][ job ] = min( dp[ day ][ job ], dp[ day ][ stack[ -1 ] ])\n                \n                stack.append( job )\n\n        return dp[ -1 ][ -1 ]\n        \n'
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'minDifficulty'
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: 6802