ladybird/Meta/test_pdf.py

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#!/usr/bin/env python3
'''Runs `pdf --debugging-stats` on a bunch of PDF files in parallel.
Give it one or more folders containing PDF files, and the optional -n flag
to pick a random subset of n PDFs:
test_pdf.py -n 200 ~/Downloads/0000 ~/src/pdffiles
https://pdfa.org/new-large-scale-pdf-corpus-now-publicly-available/ has
8 TB of test PDFs, organized in a bunch of zip files with 1000 PDFs each.
One of those zip files in unzipped makes for a good input folder.
'''
import argparse
import collections
import glob
import multiprocessing
import os
import random
import re
import subprocess
Result = collections.namedtuple(
'Result', ['filename', 'returncode', 'stdout', 'stderr'])
def elide_aslr(s):
return re.sub(rb'\b0x[0-9a-f]+\b', b'0xc3ns0r3d', s)
def elide_parser_offset(s):
return re.sub(rb'\bParser error at offset [0-9]+:', b'Parser error:', s)
def test_pdf(filename):
pdf_path = os.path.join(os.path.dirname(__file__), '../Build/lagom/bin/pdf')
r = subprocess.run([pdf_path, '--debugging-stats', filename],
capture_output=True)
return Result(filename, r.returncode, r.stdout,
elide_parser_offset(elide_aslr(r.stderr)))
def main():
parser = argparse.ArgumentParser(
epilog=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
)
parser.add_argument('input', nargs='+', help='input directories')
parser.add_argument('-n', type=int, help='render at most n pdfs')
args = parser.parse_args()
files = []
for input_directory in args.input:
files += glob.glob(os.path.join(input_directory, '*.pdf'))
if args.n is not None:
random.seed(42)
files = random.sample(files, k=args.n)
results = multiprocessing.Pool().map(test_pdf, files)
num_files_without_issues = 0
failed_files = []
num_crashes = 0
stack_to_files = {}
for r in results:
print(r.filename)
print(r.stdout.decode('utf-8'))
if r.returncode == 0:
if b'no issues found' in r.stdout:
num_files_without_issues += 1
continue
if r.returncode == 1:
failed_files.append(r.filename)
else:
num_crashes += 1
stack_to_files.setdefault(r.stderr, []).append(r.filename)
print('Top 5 crashiest stacks')
keys = list(stack_to_files.keys())
keys.sort(key=lambda x: len(stack_to_files[x]), reverse=True)
for stack in reversed(keys[:5]):
files = stack_to_files[stack]
print(stack.decode('utf-8', 'backslashreplace'), end='')
print(f'In {len(files)} files:')
for file in files:
print(f' {file}')
print()
percent = 100 * num_files_without_issues / len(results)
print(f'{num_files_without_issues} files without issues ({percent:.1f}%)')
print()
percent = 100 * num_crashes / len(results)
print(f'{num_crashes} crashes ({percent:.1f}%)')
print(f'{len(keys)} distinct crash stacks')
percent = 100 * len(failed_files) / len(results)
print()
print(f'{len(failed_files)} failed to open ({percent:.1f}%)')
for f in failed_files:
print(f' {f}')
if __name__ == '__main__':
main()