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Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

5 matches
Algorithms & data structures medium

Binary Search for Ship Capacity in Python

Use binary search to find the minimum ship capacity that can transport all packages within a given number of days.

binary search greedy capacity
Python
def ship_within_days(weights, days):
    def can_ship(capacity):
        current = 0
        needed_days = 1
        for weight in weights:
            if current + weight > capacity:
                needed_days += 1
                current = 0
            current += weight
        return needed_days <= days

    low …
13 0 Open
Algorithms & data structures medium

How to Find Minimum Swaps to Sort an Array in Python

Calculate the minimum number of adjacent-free swaps needed to sort a permutation array using cycle detection in Python.

sorting cycles greedy
Python
def min_swaps_to_sort(arr):
    n = len(arr)
    arr_pos = sorted((val, idx) for idx, val in enumerate(arr))
    visited = [False] * n
    swaps = 0

    for i in range(n):
        if visited[i] or arr_pos[i][1] == i:
            continue

        cycle_size = 0
        j = i
        while not visited[j]:
            …
13 0 Open
Algorithms & data structures medium

Split Array Largest Sum in Python (Minimize Largest Subarray Sum)

Binary search + greedy check to split an array into k subarrays while minimizing the largest subarray sum.

binary-search greedy array
Python
def can_split(nums, k, max_sum):
    subarrays = 1
    current_sum = 0
    for num in nums:
        if current_sum + num <= max_sum:
            current_sum += num
        else:
            subarrays += 1
            current_sum = num
            if subarrays > k:
                return False
    return True

def spli…
15 0 Open
A/B testing & experimentation medium

Epsilon Greedy Bandit Mock in Python

A simple epsilon-greedy multi-armed bandit simulation that balances exploration and exploitation to estimate true means of several Bernoulli-like reward distributions.

bandit epsilon-greedy exploration
Python
import random


class Bandit:
    def __init__(self, true_mean):
        self.true_mean = true_mean
        self.estimated_mean = 0.0
        self.n_pulls = 0

    def pull(self):
        return random.gauss(self.true_mean, 1.0)

    def update(self, reward):
        self.n_pulls += 1
        self.estimated_mean += (r…
12 0 Open
A/B testing & experimentation medium

How to simulate a contextual bandit in Python

Simulate a contextual multi-armed bandit with random features and epsilon-greedy action selection in Python.

bandit-algorithms simulation epsilon-greedy
Python
import random


class ContextualBandit:
    def __init__(self, n_actions=3, n_features=4):
        self.n_actions = n_actions
        self.n_features = n_features
        self.theta = [random.random() for _ in range(n_actions * n_features)]

    def mock_context(self):
        return [random.uniform(-1, 1) for _ in ra…
13 0 Open

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