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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 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…Merge k sorted lists in Python using a heap
Merge k individually sorted lists into one sorted list in Python using a min-heap.
import heapq
def merge_k_sorted_lists(lists):
heap = []
# Push the first element of each list onto the heap
for i, lst in enumerate(lists):
if lst:
heapq.heappush(heap, (lst[0], i, 0))
result = []
while heap:
val, list_idx, elem_idx = heapq.heappop(heap)
re…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]
…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.
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…How to Send Values into a Python Generator Coroutine
Use the .send() method to pass values into a running generator coroutine and capture them.
def coroutine():
received = []
while True:
value = yield
received.append(value)
print(f"Coroutine received: {value}")
if value == "stop":
break
return received
if __name__ == "__main__":
gen = coroutine()
next(gen) # Prime the generator
gen.send("he…How to Throw an Exception into a Python Generator
This code demonstrates how to use the .throw() method on a generator to inject an exception at its current yield point and let it recover gracefully.
def demo_throw_into_generator():
"""Demonstrate throwing an exception into a running generator."""
def counter():
"""Generator that counts until interrupted."""
try:
i = 0
while True:
yield i
i += 1
except ValueError as e:
…How to stream parse JSON arrays in Python
This code demonstrates two generators: one that streams a JSON array as individual chunks, and another that incrementally parses those chunks into Python objects using json.JSONDecoder.
import json
def json_array_stream(items):
"""Generator that yields JSON-encoded values one at a time."""
yield "["
for i, item in enumerate(items):
if i > 0:
yield ","
yield json.dumps(item)
yield "]"
def parse_json_stream(stream):
"""Consumes a stream of JSON fragme…Merge Sorted Iterators with a Heap Generator in Python
Merge multiple sorted iterators into a single sorted stream using a heap and generator, yielding values lazily in order.
import heapq
def merge_sorted_iterators(*iterators):
heap = []
for idx, iterator in enumerate(iterators):
try:
value = next(iterator)
heapq.heappush(heap, (value, idx, iterator))
except StopIteration:
continue
while heap:
value, idx, iterator = …How to parallel map embeddings with a thread pool in Python
Run embedding computations in parallel using ThreadPoolExecutor, collect results into a dict keyed by the original item.
import threading
from concurrent.futures import ThreadPoolExecutor
import time
def compute_embedding(item: int) -> tuple[int, int]:
time.sleep(0.05) # Simulate embedding work
return item, item * 10
def parallel_map_embed(items, max_workers=3):
results = {}
with ThreadPoolExecutor(max_workers=max_w…Parse ReAct Logs into Thought Action Observation Steps in Python
Parse a ReAct agent's textual log into structured steps with thought, action, and observation using regex and named tuples.
import re
from collections import namedtuple
ReActStep = namedtuple("ReActStep", ["thought", "action", "observation"])
def parse_react_log(log: str) -> list[ReActStep]:
"""Parse a ReAct log into structured thought/action/observation steps."""
pattern = re.compile(
r"Thought:\s*(?P<thought>.+?)\s*"
…Build a Complete Website Sitemap Generator Without External Services
Crawl a website recursively using only Python's standard library to generate a structured sitemap of internal links.
import json
from urllib.parse import urlparse, urljoin
from collections import deque
import urllib.request
import urllib.error
import re
from html.parser import HTMLParser
class SitemapParser(HTMLParser):
def __init__(self, base_url):
super().__init__()
self.base_url = base_url
self.links …Build a Python Tool to Find All API Endpoints on a Website
A Python script that crawls a website, searches for common API endpoint patterns in HTML and JavaScript, and returns all discovered public API URLs.
import re
import requests
from urllib.parse import urljoin, urlparse
from collections import deque
def find_api_endpoints(base_url, max_pages=10):
visited = set()
queue = deque([base_url])
api_endpoints = set()
api_patterns = [
r'/api/[a-zA-Z0-9_/-]+',
r'/v[0-9]+/[a-zA-Z0-9_/-]+',…Build a Python Utility That Verifies Backup Integrity Automatically
Automatically compute and verify SHA-256 checksums of backup files using a JSON manifest to detect missing or corrupted data.
import hashlib
import os
import json
def compute_checksum(filepath, algorithm='sha256'):
"""Compute checksum for the given file."""
hash_func = hashlib.new(algorithm)
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
hash_func.update(chunk)
return hash_f…Convert HTML Tables to Excel Reports in Python
Convert HTML tables into formatted Excel reports using BeautifulSoup and Pandas with auto-adjusted column widths.
import pandas as pd
from bs4 import BeautifulSoup
from pathlib import Path
def html_table_to_excel(html_file: str, excel_file: str) -> None:
"""Convert HTML table to formatted Excel report."""
with open(html_file, 'r', encoding='utf-8') as f:
html_content = f.read()
soup = BeautifulSoup(html_…Detect Circular Imports Across Python Projects Automatically
This script walks through all .py files in a directory, builds an import graph, and uses depth-first search to find cycles—printing each circular dependency chain.
import ast
import sys
from pathlib import Path
from collections import defaultdict, deque
def find_imports(filepath):
"""Return set of module names imported by a Python file."""
imports = set()
try:
with open(filepath) as f:
tree = ast.parse(f.read())
except (SyntaxError, UnicodeDe…Find Broken Image References Across a Website in Python
Crawl internal pages of a website, collect all image source URLs, then check each with HEAD requests to report any that return HTTP 4xx or connection errors.
import requests
from urllib.parse import urljoin, urlparse
from bs4 import BeautifulSoup
from concurrent.futures import ThreadPoolExecutor, as_completed
def find_all_links(base_url, max_pages=50):
visited, to_visit = set(), {base_url}
while to_visit and len(visited) < max_pages:
url = to_visit.pop()
…Find the Largest Files Consuming Disk Space with a Beautiful Terminal Report in Python
Scan a directory recursively and print a formatted terminal report of the largest files, with human-readable sizes.
import os
import sys
from pathlib import Path
def get_largest_files(directory: str, count: int = 10) -> list:
"""
Scan the given directory and return the largest files.
Args:
directory: Path to the directory to scan
count: Number of largest files to return
Returns:
…How to Compare Two GitHub Repositories and Highlight Differences in Python
Fetch metadata from two GitHub repositories using the GitHub API and compare key attributes like stars, forks, license, and language, printing any differences.
import requests
import json
from pathlib import Path
def fetch_repo_data(owner, repo_name):
"""Fetch repository metadata from GitHub API."""
url = f"https://api.github.com/repos/{owner}/{repo_name}"
response = requests.get(url)
response.raise_for_status()
return response.json()
def compare_repos(…How to Create a Link Graph Visualization for Any Website in Python
A Python script that crawls a website's internal links, builds a directed graph of parent-child URL relationships, and prints the graph to the console.
import requests
from bs4 import BeautifulSoup
from collections import defaultdict
from urllib.parse import urljoin, urlparse
import sys
def get_links(url, max_links=20):
try:
response = requests.get(url, timeout=5)
soup = BeautifulSoup(response.text, 'html.parser')
base_url = f"{urlparse(u…How to Detect Applications Consuming Excessive Memory in Python
Use psutil to list the top memory-using processes by RSS and print their names, PIDs, and memory usage in MB.
import psutil
def find_top_memory_processes(limit=5):
"""Return top `limit` processes by memory usage (RSS)."""
processes = []
for proc in psutil.process_iter(['pid', 'name', 'memory_info']):
try:
info = proc.info
mem = info['memory_info'].rss if info['memory_info'] else 0…How to Detect Network Interface Changes in Python
Monitor active network interfaces and print a message when an interface is added or removed using psutil and socket.
import socket
import psutil
import time
def get_network_interfaces():
"""Return a set of currently active interface names."""
active_ifaces = set()
for iface, addrs in psutil.net_if_addrs().items():
for addr in addrs:
if addr.family == socket.AF_INET: # IPv4 address present
…How to Generate a Dependency Graph for Python Projects
This script walks through a Python project directory, parses each .py file's imports, and prints a dependency graph showing which modules depend on which other modules.
import os
import ast
from pathlib import Path
from collections import defaultdict
def get_imports(filepath):
with open(filepath) as f:
try:
tree = ast.parse(f.read())
except SyntaxError:
return []
imports = []
for node in ast.walk(tree):
if isinstance(node, …Browse by section
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