# Find the Minimum Processing Rate to Meet a Deadline You have several independent workloads. During each hour, a worker chooses one workload and processes up to `rate` units from it. If that workload contains fewer than `rate` remaining units, the worker finishes it and the unused capacity in that hour cannot be applied to another workload. Find the smallest positive integer `rate` that finishes all workloads within `hours` hours. ## Function Signature ```python def min_processing_rate(workloads: list[int], hours: int) -> int: ``` ## Inputs - `workloads[i]` is the positive size of workload `i`. - `hours` is the maximum total number of hourly processing slots. - It is guaranteed that `hours >= len(workloads)`, so a feasible rate exists. ## Output Return the minimum positive integer processing rate that completes every workload within the deadline. ## Constraints - `1 <= len(workloads) <= 100_000` - `1 <= workloads[i] <= 10^9` - `len(workloads) <= hours <= 10^9` - The input array must not be mutated. ## Examples ```text workloads = [3, 6, 7, 11] hours = 8 output = 4 ``` ```text workloads = [30, 11, 23, 4, 20] hours = 5 output = 30 ```