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How to Solve the Trapping Rain Water Problem in Python
Compute the total water trapped between elevation bars using a two-pointer O(n) algorithm.
def trap(height):
if not height:
return 0
left, right = 0, len(height) - 1
left_max, right_max = 0, 0
water = 0
while left < right:
if height[left] < height[right]:
if height[left] >= left_max:
left_max = height[left]
else:
…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…How to solve the stock span problem in Python
Calculate the stock span for each day's price using a monotonic stack in O(n) time.
def stock_span(prices):
span = [1] * len(prices)
stack = []
for i in range(len(prices)):
while stack and prices[stack[-1]] <= prices[i]:
stack.pop()
span[i] = i - stack[-1] if stack else i + 1
stack.append(i)
return span
if __name__ == "__main__":
pric…Product of All Elements Except Self in Python
Given a list of integers, return a list where each element is the product of all other elements except itself, using prefix and suffix products in O(n) time and O(1) extra space.
def product_except_self(nums):
n = len(nums)
result = [1] * n
left_product = 1
for i in range(n):
result[i] = left_product
left_product *= nums[i]
right_product = 1
for i in range(n - 1, -1, -1):
result[i] *= right_product
right_product *= nums[i]
…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…Set Matrix Zeroes in Python: Markers List Grid Demo
Given a matrix, this code finds all rows and columns that contain a zero and sets every element in those rows and columns to zero, using boolean marker arrays.
def set_zeroes(matrix):
rows, cols = len(matrix), len(matrix[0])
row_markers = [False] * rows
col_markers = [False] * cols
# First pass: record which rows and columns contain zeros
for i in range(rows):
for j in range(cols):
if matrix[i][j] == 0:
row_markers[i] …Validate Sudoku Board Rows Columns and Boxes in Python
Validate a 9x9 Sudoku board by checking that each row, column, and 3x3 box contains the numbers 1 through 9 exactly once.
def validate_sudoku(board):
def is_valid_group(group):
return sorted(group) == list(range(1, 10))
def get_columns():
return [[board[r][c] for r in range(9)] for c in range(9)]
def get_boxes():
boxes = []
for box_row in range(0, 9, 3):
for box_col in range(0, 9,…How to Topologically Sort a DAG in Python
Compute a valid execution order for tasks with dependencies using Kahn's algorithm in Python.
from collections import defaultdict, deque
def topological_order(dependencies):
graph = defaultdict(list)
in_degree = defaultdict(int)
tasks = set(dependencies.keys())
for task, depends_on in dependencies.items():
for d in depends_on:
graph[d].append(task)
in_degree[t…Merge K Sorted Lists in Python with heapq
Merge k sorted lists into one sorted list in O(N log k) time using a min-heap of current elements.
import heapq
def merge_k_sorted_lists(lists):
heap = []
for i, lst in enumerate(lists):
if lst: # only push non-empty lists
heapq.heappush(heap, (lst[0], i, 0))
result = []
while heap:
val, list_idx, elem_idx = heapq.heappop(heap)
result.append(val)
if elem…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]:
…Redis Leaky Bucket Rate Limiting Mock in Python
Simulates a Redis-backed leaky bucket rate limiter using a local class with continuous leaking and token capacity checks.
import time
from collections import deque
class LeakyBucket:
def __init__(self, capacity, leak_rate):
self.capacity = capacity
self.leak_rate = leak_rate
self.water = 0.0
self.timestamp = time.time()
self.history = deque()
def allow(self):
current = time.time(…GCRA generic cell rate algorithm in Python
Mock implementation of the Generic Cell Rate Algorithm (GCRA) for traffic shaping and rate limiting.
from collections import deque
import time
class GCRA:
def __init__(self, rate, burst):
self.tau = burst
self.T = rate
self.t = 0
self.LCT = 0
def add_cell(self, arrival_time):
if arrival_time <= self.t:
return False
arrived_early = (arrival_time - s…Token bucket rate limiter in Python (in-memory)
Implement a thread-safe in-memory token bucket rate limiter that throttles requests based on a steady refill rate.
import time
import threading
class TokenBucket:
def __init__(self, capacity, refill_rate, refill_interval=1.0):
self.capacity = capacity
self.tokens = capacity
self.refill_rate = refill_rate
self.refill_interval = refill_interval
self.last_refill = time.monotonic()
…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 contextual bandit in Python
Simulate a contextual multi-armed bandit with random features and epsilon-greedy action selection in 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…Thompson Sampling Mock Bandit in Python
Implement a Thompson sampling multi-armed bandit to explore and exploit reward probabilities across multiple options, updating Beta distributions over time.
import random
class ThompsonSamplingBandit:
def __init__(self, num_arms, alpha=1.0, beta=1.0):
self.num_arms = num_arms
self.alpha = [alpha] * num_arms
self.beta = [beta] * num_arms
def select_arm(self):
samples = [random.betavariate(a, b) for a, b in zip(self.alpha, self.beta…UCB1 Bandit Algorithm in Python
This code implements the UCB1 multi-armed bandit algorithm, balancing exploration and exploitation to identify the best arm while maximizing cumulative reward.
import math
import random
def ucb1(means, n_iterations=1000, exploration_weight=2.0):
"""Run UCB1 bandit algorithm on arms with given true means."""
n_arms = len(means)
counts = [0] * n_arms
rewards = [0.0] * n_arms
for t in range(1, n_iterations + 1):
# UCB1 selection
if t <…Simulate a GIN Index for JSONB in Python
Build a mock Generalized Inverted Index (GIN) that flattens JSON documents into key-value tokens for fast lookup queries, mimicking PostgreSQL JSONB indexing.
import json
import random
from collections import defaultdict
# Mock GIN (Generalized Inverted Index) for JSONB key-value pairs
class GINIndex:
def __init__(self):
self.posting_lists = defaultdict(list) # token -> list of doc_ids
def index(self, doc_id, json_obj):
"""Index a JSON documen…Browse by section
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