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Merge branch 'main' of https://github.com/allenai/pdelfin into main
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commit
cb800d6e2c
@ -60,6 +60,9 @@ class PdfFilter:
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word_counts = Counter(clean_text.split())
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word_counts = Counter(clean_text.split())
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total_words = len(clean_text.split())
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total_words = len(clean_text.split())
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if total_words == 0:
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return False
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seo_score = sum(word_counts[word] for word in seo_words if word in word_counts)
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seo_score = sum(word_counts[word] for word in seo_words if word in word_counts)
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return (seo_score / total_words) > self.download_spam_threshold
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return (seo_score / total_words) > self.download_spam_threshold
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@ -107,3 +110,89 @@ class PdfFilter:
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return True # Filter out
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return True # Filter out
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return False # Keep the PDF
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return False # Keep the PDF
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if __name__ == "__main__":
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import tempfile
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import boto3
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from pdelfin.s3_utils import parse_s3_path
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from concurrent.futures import ProcessPoolExecutor, as_completed
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from tqdm import tqdm
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# Quiet logs from pypdf
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logging.getLogger("pypdf").setLevel(logging.ERROR)
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def process_pdf(s3_path):
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"""
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Process a single PDF file to determine if it should be kept or removed.
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"""
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s3_bucket, s3_key = parse_s3_path(s3_path)
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pdf_s3 = boto3.client("s3")
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with tempfile.NamedTemporaryFile(suffix=".pdf", delete=True) as tmp_file:
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pdf_s3.download_fileobj(s3_bucket, s3_key, tmp_file)
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tmp_file.flush()
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# Perform filtering logic
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if filter.filter_out_pdf(tmp_file.name):
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return s3_path, "remove"
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else:
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return s3_path, "keep"
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# Load the list of S3 paths with a progress bar
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with open("/home/ubuntu/s2pdf_paths_1M.txt", "r") as f:
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s3_work_paths = list(filter(None, (line.strip() for line in tqdm(f, desc="Loading paths"))))
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# Initialize the PDF filter
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filter = PdfFilter(
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languages_to_keep={Language.ENGLISH, None}, # none means could not detect language, that's okay keep it, might be an OCR
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apply_download_spam_check=True,
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apply_form_check=True,
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)
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# Output files
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keep_path = "/home/ubuntu/s2pdf_paths_filter_keep.txt"
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remove_path = "/home/ubuntu/s2pdf_paths_filter_remove.txt"
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# Max number of concurrent futures
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max_concurrent_futures = 1000
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# Process the PDFs in parallel with limited concurrent futures
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with open(keep_path, "w") as fkeep, open(remove_path, "w") as fremove:
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with ProcessPoolExecutor(max_workers=max_concurrent_futures) as executor:
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futures = {}
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with tqdm(total=len(s3_work_paths), desc="Processing PDFs") as pbar:
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for s3_path in s3_work_paths:
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# Submit a new future if we haven't reached the max_concurrent_futures
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future = executor.submit(process_pdf, s3_path)
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futures[future] = s3_path
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# Monitor completed futures
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try:
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while len(futures) >= max_concurrent_futures:
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for completed_future in as_completed(futures, timeout=0.1):
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s3_path = futures.pop(completed_future)
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try:
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s3_path, result = completed_future.result()
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if result == "keep":
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fkeep.write(s3_path + "\n")
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elif result == "remove":
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fremove.write(s3_path + "\n")
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except Exception as e:
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print(f"Error processing {s3_path}: {e}")
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pbar.update(1)
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except TimeoutError:
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pass
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# Process remaining futures after all tasks have been submitted
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for completed_future in as_completed(futures):
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s3_path = futures.pop(completed_future)
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try:
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s3_path, result = completed_future.result()
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if result == "keep":
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fkeep.write(s3_path + "\n")
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elif result == "remove":
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fremove.write(s3_path + "\n")
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except Exception as e:
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print(f"Error processing {s3_path}: {e}")
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pbar.update(1)
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