We have n jobs, where every job is scheduled to be done from startTime[i] to endTime[i], obtaining a profit of profit[i].
You're given the startTime , endTime and profit arrays, you need to output the maximum profit you can take such that there are no 2 jobs in the subset with overlapping time range.
If you choose a job that ends at time X you will be able to start another job that starts at time X.
 
Example 1:

Input: startTime = [1,2,3,3], endTime = [3,4,5,6], profit = [50,10,40,70]
Output: 120
Explanation: The subset chosen is the first and fourth job. 
Time range [1-3]+[3-6] , we get profit of 120 = 50 + 70.

Example 2:
 

Input: startTime = [1,2,3,4,6], endTime = [3,5,10,6,9], profit = [20,20,100,70,60]
Output: 150
Explanation: The subset chosen is the first, fourth and fifth job. 
Profit obtained 150 = 20 + 70 + 60.

Example 3:

Input: startTime = [1,1,1], endTime = [2,3,4], profit = [5,6,4]
Output: 6

 
Constraints:

1 <= startTime.length == endTime.length == profit.length <= 5 * 10^4
1 <= startTime[i] < endTime[i] <= 10^9
1 <= profit[i] <= 10^4

```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 = "import collections\nimport functools\nimport heapq\nimport itertools\nimport sys\nfrom functools import lru_cache\nfrom typing import List\n\n'''\nn份工作薪水不同，开始时间和结束时间不同，找到最大的收益，时间不能冲突。\n\n背包问题，工作可以做或者不做，做时选择下一个不冲突的工作继续。\n'''\n\nclass Solution:\n    def jobScheduling(self, startTime: List[int], endTime: List[int], profit: List[int]) -> int:\n        def dfs_func():\n            n = len(profit)\n            dp = {}\n            jobs = [(startTime[i], endTime[i], profit[i]) for i in range(n)]\n            jobs.sort()\n\n            def find_next_confict(jobs_i):\n                for jobs_j in range(jobs_i + 1, n):\n                    if jobs[jobs_i][1] <= jobs[jobs_j][0]:\n                        return jobs_j\n                return n\n\n            # 二分加速\n            def find_next_confict_left(jobs_i):\n                dst = jobs[jobs_i][1]\n                left = jobs_i\n                right = n\n                while left < right:\n                    mid = int((left + right) / 2)\n                    mid_value = jobs[mid][0]\n                    if dst < mid_value:\n                        right = mid\n                    elif dst > mid_value:\n                        left = mid + 1\n                    else:\n                        right = mid\n                return left\n\n            def dfs(jobs_i):\n                if jobs_i >= n:\n                    return 0\n                if jobs_i in dp:\n                    return dp[jobs_i]\n                s, e, p = jobs[jobs_i]\n                jobs_j = find_next_confict_left(jobs_i)\n                choose = p\n                if jobs_j < n:\n                    choose += dfs(jobs_j)\n                not_choose = dfs(jobs_i + 1)\n                dp[jobs_i] = max(choose, not_choose)\n                return dp[jobs_i]\n\n            return dfs(0)\n\n        def dp_func():\n            # dp[end] = max(dp[end-1],dp[last_not_conflict] + profit))\n            # end有多个，用坐标代替\n            # sort(end)\n            # dp[i] = max(dp[i-1],dp[last_not_conflict] + profit))\n\n            # 二分加速\n\n            n = len(profit)\n            jobs = [(endTime[i], startTime[i], profit[i]) for i in range(n)]\n            jobs.sort()\n            dp = [0 for _ in range(n + 1)]\n\n            # 右边界\n            def find_pre_not_confict(jobs_i):\n                dst = jobs[jobs_i][1]\n                left = 0\n                right = jobs_i\n                while left < right:\n                    mid = int((left + right) / 2)\n                    mid_value = jobs[mid][0]\n                    if dst < mid_value:\n                        right = mid\n                    elif dst > mid_value:\n                        left = mid + 1\n                    else:\n                        left = mid + 1\n                return left - 1\n\n            def find_pre_not_confict1(jobs_i):\n                for i in range(jobs_i, -1, -1):\n                    if jobs[jobs_i][1] >= jobs[i][0]:\n                        return i\n                return -1\n\n            for i in range(1, n + 1):\n                last_not_conflict = find_pre_not_confict(i-1)\n                choose = jobs[i - 1][2]\n                # 再判断一次，防止0\n                if last_not_conflict != -1:\n                    choose += dp[last_not_conflict + 1]\n                dp[i] = max(dp[i - 1], choose)\n            return dp[n]\n        return dp_func()"
_co = compile(_CODE, USER_FILENAME, "exec")
exec(_co, ns, ns)

_target = None
_fn_name = 'jobScheduling'
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: 7500