CommonCrawl_URL_Processor/multithread_script

import subprocess
import os
import gzip
import re
from multiprocessing import Pool

def extract_urls_from_file(file_path):
    urls = []
    try:
        with gzip.open(file_path, 'rt', encoding='latin-1') as file:
            # Process the file line by line
            for line in file:
                # Extract URLs using regular expression
                url_pattern = re.compile(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+')
                line_urls = re.findall(url_pattern, line)
                urls.extend(line_urls)
    except (gzip.BadGzipFile, EOFError) as e:
        print(f"Skipping file '{file_path}' due to an error while reading the compressed file: {e}")
    except Exception as e:
        print(f"An unexpected error occurred while processing '{file_path}': {e}")
    
    return urls

def process_file(file_path):
    # Extract URLs from the gzipped file
    urls = extract_urls_from_file(file_path)

    # Create the output file path with '_urls.txt' extension
    output_file_path = os.path.splitext(file_path)[0] + '_urls.txt'

    # Write the URLs to the output file
    with open(output_file_path, 'w') as output_file:
        output_file.write('\n'.join(urls))

    print(f"URLs extracted from '{file_path}' and saved to '{output_file_path}'")

    # Remove the original gzipped file
    os.remove(file_path)

def extract_urls_from_directory(directory_path):
    # Get the list of files in the directory and sort them
    file_list = sorted(os.listdir(directory_path))

    # Create a multiprocessing Pool with the number of processes
    # based on the available CPU cores
    pool = Pool(processes=12)

    # Map the file processing function to the list of files
    pool.map(process_file, [os.path.join(directory_path, filename) for filename in file_list if filename.endswith('.wat.gz')])

    # Close the pool to free up resources
    pool.close()
    pool.join()

# Read the URLs from the file
with open('urls_to_download.txt', 'r') as file:
    urls = file.readlines()

# Remove any leading/trailing whitespace from the URLs
urls = [url.strip() for url in urls]

# Define the batch size
batch_size = 100

# Define the concurrency level (number of download processes running concurrently)
concurrency_level = 10

# Split the URLs into batches
batches = [urls[i:i+batch_size] for i in range(0, len(urls), batch_size)]

# Iterate over the batches and download URLs
for batch in batches:
    # Create a multiprocessing Pool with the specified concurrency level
    pool = Pool(processes=concurrency_level)

    for url in batch:
        # Create the command to download the URL using axel with 3 connections
        command = f'axel -n 3 {url}'

        # Start the subprocess in the background
        pool.apply_async(subprocess.run, args=(command,), kwds={'shell': True})

    # Close the pool to indicate that no more tasks will be added
    pool.close()

    # Wait for all processes in the pool to finish
    pool.join()

    # Extract URLs from the downloaded files
    extract_urls_from_directory(os.getcwd())

    # Run the urlextractor_archiveteam.sh script
    subprocess.run(['bash', 'urlextractor_archiveteam.sh'])