95 lines
3.1 KiB
Python
95 lines
3.1 KiB
Python
import subprocess
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import os
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import gzip
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import re
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from multiprocessing import Pool
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def extract_urls_from_file(file_path):
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urls = []
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try:
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with gzip.open(file_path, 'rt', encoding='latin-1') as file:
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# Process the file line by line
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for line in file:
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# Extract URLs using regular expression
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url_pattern = re.compile(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+')
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line_urls = re.findall(url_pattern, line)
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urls.extend(line_urls)
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except (gzip.BadGzipFile, EOFError) as e:
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print(f"Skipping file '{file_path}' due to an error while reading the compressed file: {e}")
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except Exception as e:
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print(f"An unexpected error occurred while processing '{file_path}': {e}")
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return urls
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def process_file(file_path):
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# Extract URLs from the gzipped file
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urls = extract_urls_from_file(file_path)
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# Create the output file path with '_urls.txt' extension
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output_file_path = os.path.splitext(file_path)[0] + '_urls.txt'
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# Write the URLs to the output file
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with open(output_file_path, 'w') as output_file:
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output_file.write('\n'.join(urls))
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print(f"URLs extracted from '{file_path}' and saved to '{output_file_path}'")
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# Remove the original gzipped file
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os.remove(file_path)
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def extract_urls_from_directory(directory_path):
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# Get the list of files in the directory and sort them
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file_list = sorted(os.listdir(directory_path))
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# Create a multiprocessing Pool with the number of processes
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# based on the available CPU cores
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pool = Pool(processes=7)
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# Map the file processing function to the list of files
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pool.map(process_file, [os.path.join(directory_path, filename) for filename in file_list if filename.endswith('.wat.gz')])
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# Close the pool to free up resources
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pool.close()
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pool.join()
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# Read the URLs from the file
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with open('urls_to_download.txt', 'r') as file:
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urls = file.readlines()
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# Remove any leading/trailing whitespace from the URLs
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urls = [url.strip() for url in urls]
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# Define the batch size
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batch_size = 48
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# Define the concurrency level (number of download processes running concurrently)
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concurrency_level = 4
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# Split the URLs into batches
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batches = [urls[i:i+batch_size] for i in range(0, len(urls), batch_size)]
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# Iterate over the batches and download URLs
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for batch in batches:
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# Create a multiprocessing Pool with the specified concurrency level
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pool = Pool(processes=concurrency_level)
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for url in batch:
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# Create the command to download the URL using axel with 3 connections
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command = f'axel -n 2 {url}'
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# Start the subprocess in the background
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pool.apply_async(subprocess.run, args=(command,), kwds={'shell': True})
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# Close the pool to indicate that no more tasks will be added
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pool.close()
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# Wait for all processes in the pool to finish
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pool.join()
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# Extract URLs from the downloaded files
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extract_urls_from_directory(os.getcwd())
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# Run the urlextractor_archiveteam.sh script
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subprocess.run(['bash', 'urlextractor_archiveteam.sh'])
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