Python Articles

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Check if one list is subset of other in Python

SaiKrishna Tavva
SaiKrishna Tavva
Updated on 25-Mar-2026 6K+ Views

Python provides various methods to check if one list is a subset of another. A subset means all elements of the smaller list exist in the larger list. We'll explore three effective approaches: all() function, issubset() method, and intersection() method. Using all() Function The all() function returns True if all elements in an iterable are true, otherwise False. We can combine it with a generator expression to check if every element of the sublist exists in the main list − # Define the main list and the sublist main_list = ['Mon', 'Tue', 5, 'Sat', 9] sub_list ...

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Compare Version Numbers in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 3K+ Views

Comparing version numbers is a common programming task. Python provides several ways to compare version strings like "1.0.1" and "1.2.3". When comparing versions, we return 1 if the first version is greater, -1 if it's smaller, and 0 if they're equal. Understanding Version Number Comparison Version numbers consist of numeric parts separated by dots. Each part represents a different level of revision ? Version "2.5" means the 5th second-level revision of the 2nd first-level revision Missing parts default to 0 (e.g., "1.2" is equivalent to "1.2.0.0...") Compare each part from left to right until finding a ...

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Longest Well-Performing Interval in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 315 Views

The Longest Well-Performing Interval problem requires finding the longest subarray where tiring days (hours > 8) outnumber non-tiring days. We solve this using a prefix sum approach with a hashmap to track cumulative balance efficiently. Understanding the Problem A tiring day occurs when hours worked > 8. A well-performing interval is a subarray where tiring days strictly outnumber non-tiring days. We transform each day into +1 (tiring) or -1 (non-tiring) and find the longest subarray with positive sum. Algorithm Approach We use a prefix sum technique with the following key insights: Convert hours to ...

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Corporate Flight Bookings in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 265 Views

The Corporate Flight Bookings problem involves calculating the total number of seats booked on each flight when given multiple booking ranges. Each booking specifies a range of flights and the number of seats to book across that range. Problem Understanding Given n flights labeled 1 to n, and a list of bookings where each booking [i, j, k] means k seats are booked from flight i to flight j (inclusive), we need to find the total seats booked on each flight. Example With bookings [[1, 2, 10], [2, 3, 20], [2, 5, 25]] and n = ...

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Car Pooling in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 933 Views

Car pooling is a common algorithmic problem where we need to determine if a vehicle can accommodate all passenger trips without exceeding its capacity. The vehicle travels only eastward, picking up and dropping off passengers at specific locations. Problem Understanding Given a list of trips where each trip contains [num_passengers, start_location, end_location] and a vehicle capacity, we need to check if all trips can be completed without exceeding the capacity limit. Algorithm Approach We use a difference array technique to track passenger changes at each location ? Create an array to track passenger count ...

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Largest Values From Labels in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 257 Views

The Largest Values From Labels problem involves selecting items from a collection to maximize the sum while respecting constraints on the total number of items and usage limits per label. Problem Statement Given a set of items where the i-th item has values[i] and labels[i], we need to find a subset S such that: |S| ≤ num_wanted For every label L, the number of items in S with label L is ≤ use_limit The goal is to find the largest possible sum of the subset S. ...

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Letter Tile Possibilities in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 675 Views

Given a set of letter tiles, we need to find the number of possible non-empty sequences we can make using these tiles. For example, with tiles "AAB", we can form 8 different sequences: "A", "B", "AA", "AB", "BA", "AAB", "ABA", "BAA". This problem uses backtracking with frequency counting to generate all possible permutations while avoiding duplicates. Algorithm Approach We use a depth-first search (DFS) approach with the following steps: Count the frequency of each letter in the input tiles For each recursive call, try using each available letter Backtrack by restoring the letter count after ...

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Flip Columns For Maximum Number of Equal Rows in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 334 Views

Given a binary matrix of 0s and 1s, we can flip any columns to maximize the number of rows with equal values. Flipping a column changes all 0s to 1s and all 1s to 0s in that column. The goal is to find the maximum number of rows that can have identical values after optimal column flips. Original Matrix: 0 0 0 0 ...

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Distant Barcodes in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 207 Views

In a warehouse with a row of barcodes, we need to rearrange them so that no two adjacent barcodes are the same. For example, if we have [1, 1, 1, 2, 2, 2], we want to output [2, 1, 2, 1, 2, 1]. The strategy is to place the most frequent barcode first at even positions (0, 2, 4...), then fill odd positions with remaining barcodes. Algorithm Steps Count frequency of each barcode Sort barcodes by frequency (ascending order) Place the most frequent barcode at even positions (0, 2, 4...) Place remaining barcodes at odd positions ...

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Previous Permutation With One Swap in Python

Arnab Chakraborty
Arnab Chakraborty
Updated on 25-Mar-2026 512 Views

Finding the previous permutation with one swap means finding the lexicographically largest permutation that is smaller than the given array by swapping exactly two elements. If no such permutation exists, we return the original array. For example, given [3, 2, 1], we can swap positions 1 and 2 to get [3, 1, 2], which is the largest permutation smaller than the original. Algorithm The algorithm follows these steps ? Find the rightmost position where A[left] > A[left + 1] If no such position exists, return the original array Find the largest element to the right ...

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