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@ -16,7 +16,7 @@ repos:
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- id: auto-walrus
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.7.3
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rev: v0.7.4
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hooks:
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- id: ruff
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- id: ruff-format
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@ -526,6 +526,7 @@
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* [Test Min Spanning Tree Prim](graphs/tests/test_min_spanning_tree_prim.py)
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## Greedy Methods
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* [Activity Selection](greedy_methods/activity_selection.py)
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* [Best Time To Buy And Sell Stock](greedy_methods/best_time_to_buy_and_sell_stock.py)
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* [Fractional Cover Problem](greedy_methods/fractional_cover_problem.py)
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* [Fractional Knapsack](greedy_methods/fractional_knapsack.py)
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52
greedy_methods/activity_selection.py
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52
greedy_methods/activity_selection.py
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"""
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The Activity Selection Problem is a classic problem in which a set of activities,
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each with a start and end time, needs to be scheduled in such a way that
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the maximum number of non-overlapping activities is selected.
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This is a greedy algorithm where at each step,
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we choose the activity that finishes the earliest
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and does not conflict with previously selected activities.
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Wikipedia: https://en.wikipedia.org/wiki/Activity_selection_problem
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"""
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def activity_selection(activities: list[tuple[int, int]]) -> list[tuple[int, int]]:
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"""
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Solve the Activity Selection Problem using a greedy algorithm by selecting
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the maximum number of non-overlapping activities from a list of activities.
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Parameters:
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activities: A list of tuples where each tuple contains
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the start and end times of an activity.
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Returns:
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A list of selected activities that are non-overlapping.
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Example:
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>>> activity_selection([(1, 3), (2, 5), (3, 9), (6, 8)])
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[(1, 3), (6, 8)]
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>>> activity_selection([(0, 6), (1, 4), (3, 5), (5, 7), (5, 9), (8, 9)])
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[(1, 4), (5, 7), (8, 9)]
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>>> activity_selection([(1, 2), (2, 4), (3, 5), (0, 6)])
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[(1, 2), (2, 4)]
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>>> activity_selection([(5, 9), (1, 2), (3, 4), (0, 6)])
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[(1, 2), (3, 4), (5, 9)]
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"""
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# Step 1: Sort the activities by their end time
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sorted_activities = sorted(activities, key=lambda activity: activity[1])
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# Step 2: Select the first activity (the one that finishes the earliest)
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# as the initial activity
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selected_activities = [sorted_activities[0]]
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# Step 3: Iterate through the sorted activities and select the ones
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# that do not overlap with the last selected activity
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for i in range(1, len(sorted_activities)):
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if sorted_activities[i][0] >= selected_activities[-1][1]:
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selected_activities.append(sorted_activities[i])
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return selected_activities
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@ -1,4 +1,4 @@
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#!/usr/bin/env python3
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#!python
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import os
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try:
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