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Implement the Strategy Pattern with Interchangeable Algorithm Classes in Python
Uses abstract base classes to define a SortStrategy interface, then swaps between BubbleSort and QuickSort at runtime.
from abc import ABC, abstractmethod
from typing import List
class SortStrategy(ABC):
@abstractmethod
def sort(self, data: List[int]) -> List[int]:
pass
class BubbleSort(SortStrategy):
def sort(self, data: List[int]) -> List[int]:
result = data[:]
n = len(result)
for i in…Find All Triplets with Sum Zero in Python
This code finds all unique triplets in an array that sum to zero using a sorted array and two-pointer technique.
def find_triplets(nums):
nums.sort()
n = len(nums)
triplets = []
for i in range(n - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
left, right = i + 1, n - 1
while left < right:
total = nums[i] + nums[left] + nums[right]
if total == 0:
…How to Find Four Sum Quadruplets in Python (Sorted Demo)
Find all unique quadruplets in a sorted array that sum to a target, with duplicate skipping.
def four_sum(nums, target):
nums.sort()
result = []
n = len(nums)
for i in range(n - 3):
if i > 0 and nums[i] == nums[i - 1]:
continue
for j in range(i + 1, n - 2):
if j > i + 1 and nums[j] == nums[j - 1]:
continue
left, right = j + 1…How to Find Intersection of Two Sorted Interval Lists in Python
A two-pointer algorithm that finds all overlapping intervals between two sorted lists of intervals.
def interval_intersection(list1, list2):
i = j = 0
result = []
while i < len(list1) and j < len(list2):
# Find the overlap between current intervals
lo = max(list1[i][0], list2[j][0])
hi = min(list1[i][1], list2[j][1])
# If there's an overlap, add it to result
…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.
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]:
…How to Sort Colors (Dutch National Flag) in Python
In-place sorting of a list of 0s, 1s, and 2s using the Dutch National Flag algorithm with O(n) time and O(1) space.
def sort_colors(nums):
low, mid, high = 0, 0, len(nums) - 1
while mid <= high:
if nums[mid] == 0:
nums[low], nums[mid] = nums[mid], nums[low]
low += 1
mid += 1
elif nums[mid] == 1:
mid += 1
else: # nums[mid] == 2
nums[mid], n…Quickselect in Python: Find the kth Smallest Element
Python implementation of the Quickselect algorithm to find the kth smallest element in an unsorted list with average O(n) time complexity.
def quickselect(arr, k):
"""
Returns the k-th smallest element (0-indexed) using Quickselect.
Average: O(n), Worst: O(n^2)
"""
if len(arr) == 1:
return arr[0]
pivot = arr[-1]
left = [x for x in arr[:-1] if x <= pivot]
right = [x for x in arr[:-1] if x > pivot]
if k < len(l…Implement an Out-of-Order Sort Buffer with a Heap in Python
Buffers out-of-order indices from a stream and emits them in sorted order using a min-heap with a sliding window.
import heapq
from collections import deque
class OutOfOrderSorter:
def __init__(self, buffer_size):
self.buffer_size = buffer_size
self.buffer = deque(maxlen=buffer_size)
self.heap = []
self.next_expected_index = 0
self.result = []
def push(self, item):
heapq.…How to Profile CPU Hot Path in Python with cProfile and sort_stats cumtime
Profile a Python function's CPU usage by running cProfile, sorting stats by cumulative time, and printing a readable report to stdout.
import cProfile
import pstats
import io
def slow_function():
total = 0
for i in range(100_000):
total += i * i
return total
def fast_function():
return sum(i for i in range(100))
def main():
slow_function()
fast_function()
if __name__ == "__main__":
profiler = cProfile.Profi…How to Compare Execution Speed Between Python Functions
Measure and compare the average execution time of multiple Python functions using a reusable benchmark helper with time.perf_counter.
import time
import random
def method_a(values):
"""Sort using built-in sorted."""
return sorted(values)
def method_b(values):
"""Sort using list's sort method."""
values_copy = values[:]
values_copy.sort()
return values_copy
def method_c(values):
"""Sort manually using bubble sort (slow,…How to Implement the Strategy Pattern in Python
This Python code demonstrates the Strategy design pattern using interchangeable sorting algorithms (bubble sort and quick sort) that can be swapped at runtime.
class SortingStrategy:
def sort(self, data):
raise NotImplementedError
class BubbleSort(SortingStrategy):
def sort(self, data):
result = data.copy()
n = len(result)
for i in range(n):
for j in range(0, n - i - 1):
if result[j] > result[j + 1]:
…How to Build a DAG Execution Stage Calculator in Python
Computes the execution stages of a directed acyclic graph (DAG) by grouping nodes that become ready simultaneously using topological sorting with Kahn's algorithm.
from collections import defaultdict, deque
def get_stages(edges):
"""Return list of stages, where each stage is a list of nodes
that become ready at the same time in a DAG."""
graph = defaultdict(list)
in_degree = defaultdict(int)
nodes = set()
for src, dst in edges:
graph[src].appen…Training Pipeline Orchestration Mock DAG in Python
Build a mock DAG orchestrator that runs ML pipeline stages in dependency order using topological sorting (Kahn's algorithm).
from collections import deque
from dataclasses import dataclass, field
@dataclass
class DAGNode:
name: str
task: callable
dependencies: list[str] = field(default_factory=list)
class MockDAG:
def __init__(self, nodes: list[DAGNode]):
self.nodes = {n.name: n for n in nodes}
self.execu…How to Simulate a Stable Sort Cursor in Python
Build a MongoDB-style cursor mock that stably sorts records by a key while preserving original order for ties, with next() and rewind() methods.
```python
import random
class CursorStableSortMock:
"""Simulates stable sorting with a cursor-like pointer for MongoDB-style queries."""
def __init__(self, data, sort_key, reverse=False):
self.data = list(data)
self.sort_key = sort_key
self.reverse = reverse
self._index = …Browse by section
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