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* Enable ruff ARG001 rule * Fix dynamic_programming/combination_sum_iv.py * Fix machine_learning/frequent_pattern_growth.py * Fix other/davis_putnam_logemann_loveland.py * Fix other/password.py * Fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix physics/n_body_simulation.py * Fix project_euler/problem_145/sol1.py * Fix project_euler/problem_174/sol1.py * Fix scheduling/highest_response_ratio_next.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix * Fix * Fix scheduling/job_sequencing_with_deadline.py * Fix scheduling/job_sequencing_with_deadline.py * Fix * Fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
def job_sequencing_with_deadlines(jobs: list) -> list:
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"""
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Function to find the maximum profit by doing jobs in a given time frame
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Args:
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jobs [list]: A list of tuples of (job_id, deadline, profit)
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Returns:
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max_profit [int]: Maximum profit that can be earned by doing jobs
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in a given time frame
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Examples:
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>>> job_sequencing_with_deadlines(
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... [(1, 4, 20), (2, 1, 10), (3, 1, 40), (4, 1, 30)])
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[2, 60]
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>>> job_sequencing_with_deadlines(
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... [(1, 2, 100), (2, 1, 19), (3, 2, 27), (4, 1, 25), (5, 1, 15)])
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[2, 127]
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"""
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# Sort the jobs in descending order of profit
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jobs = sorted(jobs, key=lambda value: value[2], reverse=True)
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# Create a list of size equal to the maximum deadline
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# and initialize it with -1
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max_deadline = max(jobs, key=lambda value: value[1])[1]
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time_slots = [-1] * max_deadline
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# Finding the maximum profit and the count of jobs
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count = 0
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max_profit = 0
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for job in jobs:
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# Find a free time slot for this job
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# (Note that we start from the last possible slot)
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for i in range(job[1] - 1, -1, -1):
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if time_slots[i] == -1:
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time_slots[i] = job[0]
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count += 1
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max_profit += job[2]
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break
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return [count, max_profit]
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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