Advanced Python Assignment Examples and Expert Guidance for Students

 Python has quickly become one of the most versatile and widely used programming languages across the world. From web development and data science to artificial intelligence and automation, its simplicity and power make it a favorite among students and professionals alike. However, as coursework becomes more advanced, students often find themselves struggling with complex concepts and tight deadlines. That’s where our expert team at ProgrammingHomeworkHelp.com steps in to provide reliable and professional support.

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Advanced Python Assignment Example 1: Implementing a Custom Decorator for Performance Measurement

Problem:
Create a Python decorator named measure_time that calculates and prints the execution time of any function it decorates. Use this decorator to measure the performance of a function that sorts a list of one million random numbers.

Solution by Our Expert:

import time
import random

# Decorator function
def measure_time(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(f"Execution Time: {end - start:.4f} seconds")
        return result
    return wrapper

@measure_time
def sort_large_list():
    data = [random.randint(1, 1000000) for _ in range(1000000)]
    data.sort()
    return data

# Execute the function
sorted_data = sort_large_list()

Explanation:
This example demonstrates how decorators can be used to analyze performance — a critical skill in software optimization and real-world application development. Our expert structured the code to emphasize clean design, modularity, and reusability — qualities that are essential in advanced programming projects.

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Advanced Python Assignment Example 2: Building a Simple Multithreaded Web Scraper

Problem:
Develop a multithreaded Python application that scrapes titles from multiple web pages simultaneously. Use the threading module to improve performance.

Solution by Our Expert:

import threading
import requests
from bs4 import BeautifulSoup

# Function to fetch titles from web pages
def fetch_title(url):
    try:
        response = requests.get(url)
        soup = BeautifulSoup(response.text, 'html.parser')
        print(f"Title from {url}: {soup.title.string}")
    except Exception as e:
        print(f"Error fetching {url}: {e}")

# List of target URLs
urls = [
    "https://www.python.org",
    "https://docs.python.org/3/",
    "https://pypi.org/"
]

# Creating and starting threads
threads = []
for url in urls:
    thread = threading.Thread(target=fetch_title, args=(url,))
    threads.append(thread)
    thread.start()

# Joining all threads
for thread in threads:
    thread.join()

Explanation:
This example showcases an efficient way to perform web scraping using threads — a common task in real-world projects such as data collection and analysis. Our experts emphasize proper exception handling and efficient use of system resources.

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