172. Using ThreadPoolExecutor for Parallelism

Snippet 1: Basic Example with ThreadPoolExecutor

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from concurrent.futures import ThreadPoolExecutor

def print_number(number):
    print(f"Number: {number}")

with ThreadPoolExecutor(max_workers=3) as executor:
    executor.map(print_number, range(5))

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Snippet 2: Parallel File Reading

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from concurrent.futures import ThreadPoolExecutor

def read_file(filename):
    with open(filename, 'r') as f:
        return f.read()

filenames = ["file1.txt", "file2.txt", "file3.txt"]
with ThreadPoolExecutor() as executor:
    results = list(executor.map(read_file, filenames))

for i, content in enumerate(results):
    print(f"Content of {filenames[i]}:\n{content}")

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Snippet 3: Fetching Web Pages Concurrently

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from concurrent.futures import ThreadPoolExecutor
import requests

def fetch_url(url):
    response = requests.get(url)
    return url, response.status_code

urls = ["https://www.python.org", "https://www.github.com", "https://www.google.com"]
with ThreadPoolExecutor() as executor:
    results = list(executor.map(fetch_url, urls))

for url, status in results:
    print(f"{url} returned status {status}")

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Snippet 4: Calculating Squares Concurrently

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from concurrent.futures import ThreadPoolExecutor

def calculate_square(n):
    return n * n

numbers = range(1, 6)
with ThreadPoolExecutor(max_workers=3) as executor:
    results = executor.map(calculate_square, numbers)

print("Squares:", list(results))

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Snippet 5: Running Functions with submit

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from concurrent.futures import ThreadPoolExecutor

def greet(name):
    return f"Hello, {name}!"

with ThreadPoolExecutor() as executor:
    future = executor.submit(greet, "Alice")
    print(future.result())

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Snippet 6: Parallel Sorting of Multiple Lists

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from concurrent.futures import ThreadPoolExecutor

def sort_list(lst):
    return sorted(lst)

lists = [[3, 1, 2], [9, 7, 5], [4, 6, 8]]
with ThreadPoolExecutor() as executor:
    sorted_lists = list(executor.map(sort_list, lists))

print("Sorted lists:", sorted_lists)

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Snippet 7: Performing Delayed Tasks

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from concurrent.futures import ThreadPoolExecutor
import time

def delayed_task(seconds):
    time.sleep(seconds)
    return f"Task completed after {seconds} seconds"

delays = [1, 2, 3]
with ThreadPoolExecutor() as executor:
    results = list(executor.map(delayed_task, delays))

print("\n".join(results))

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Snippet 8: Factorial Calculation in Parallel

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from concurrent.futures import ThreadPoolExecutor
import math

def factorial(n):
    return math.factorial(n)

numbers = [5, 7, 10]
with ThreadPoolExecutor() as executor:
    results = list(executor.map(factorial, numbers))

print("Factorials:", results)

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Snippet 9: Writing to Multiple Files

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from concurrent.futures import ThreadPoolExecutor

def write_to_file(filename, content):
    with open(filename, 'w') as f:
        f.write(content)
    return f"{filename} written successfully"

tasks = [("file1.txt", "Hello, File 1"), ("file2.txt", "Hello, File 2"), ("file3.txt", "Hello, File 3")]
with ThreadPoolExecutor() as executor:
    results = executor.map(lambda x: write_to_file(*x), tasks)

print("\n".join(results))

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Snippet 10: Handling Exceptions in ThreadPoolExecutor

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from concurrent.futures import ThreadPoolExecutor

def risky_division(x, y):
    return x / y

tasks = [(10, 2), (5, 0), (20, 4)]
with ThreadPoolExecutor() as executor:
    futures = [executor.submit(risky_division, *task) for task in tasks]

for future in futures:
    try:
        print(f"Result: {future.result()}")
    except ZeroDivisionError as e:
        print(f"Error: {e}")

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