Solution #da62d7c8-7478-45d4-9a99-7694263e3c37

1def solve(input):
2    jobs = input.get("jobs", []) if isinstance(input, dict) else []
3    if not jobs:
4        return 0
5
6    # Time-compressed DP over all unique boundaries.
7    # This avoids subtle binary-search/indexing mistakes from interval-index DP.
8    times = sorted({t for s, e, _ in jobs for t in (s, e)})
9    m = len(times)
10    idx = {t: i for i, t in enumerate(times)}
11
12    ends_at = [[] for _ in range(m)]
13    for s, e, w in jobs:
14        ends_at[idx[e]].append((idx[s], w))
15
16    dp = [0] * m
17    best = 0
18    for i in range(m):
19        if i:
20            best = dp[i - 1]
21        for s_idx, w in ends_at[i]:
22            cand = (dp[s_idx] if s_idx >= 0 else 0) + w
23            if cand > best:
24                best = cand
25        dp[i] = best
26
27    return dp[-1] if dp else 0

1def solve(input):
2    if not isinstance(input, dict):
3        return 0
4    raw = input.get("jobs")
5    if not raw:
6        return 0
7
8    jobs = []
9    for j in raw:
10        if isinstance(j, (list, tuple)) and len(j) == 3:
11            jobs.append((j[1], j[0], j[2]))  # sort by end, store as (end, start, weight)
12    if not jobs:
13        return 0
14
15    jobs.sort()
16    ends = []
17    bests = []
18
19    for e, s, w in jobs:
20        lo = 0
21        hi = len(ends)
22        while lo < hi:
23            mid = (lo + hi) >> 1
24            if ends[mid] <= s:
25                lo = mid + 1
26            else:
27                hi = mid
28
29        candidate = w + (bests[lo - 1] if lo else 0)
30        current = bests[-1] if bests else 0
31
32        if candidate > current:
33            if ends and ends[-1] == e:
34                bests[-1] = candidate
35            else:
36                ends.append(e)
37                bests.append(candidate)
38
39    return bests[-1] if bests else 0