translate, done with 众生都是既然众生 and 佛教徒的人生态度

scripts/proofread-pdf.py

@@ -0,0 +1,169 @@
+"""Compare manuscript (DOCX English body) against typeset (PDF English body).
+Usage: python3 scripts/proofread-pdf.py <docx_path> <pdf_path>
+Output: sentences from DOCX not found in PDF, and word-level changes within matched sentences.
+"""
+import re, sys, subprocess
+
+
+def extract_docx_en(path):
+    with open(path) as f:
+        lines = f.readlines()
+
+    body_start = None
+    for i, line in enumerate(lines):
+        if '生活在这个世间' in line:
+            body_start = i
+            break
+    if body_start is None:
+        sys.exit("Could not find body start in DOCX")
+
+    docx_en = []
+    skip_next = 0
+    for i in range(body_start, len(lines)):
+        if skip_next > 0:
+            skip_next -= 1
+            continue
+        line = lines[i].strip()
+        if not line:
+            continue
+        has_cjk = any('\u4e00' <= c <= '\u9fff' for c in line)
+        if has_cjk:
+            if i + 1 < len(lines) and lines[i+1].strip() == '':
+                if i + 2 < len(lines):
+                    en_line = lines[i+2].strip()
+                    if en_line and not any('\u4e00' <= c <= '\u9fff' for c in en_line):
+                        docx_en.append(en_line)
+                        skip_next = 2
+        else:
+            docx_en.append(line)
+
+    # Split into sentences, filter out headings
+    text = ' '.join(docx_en)
+    sentences = re.split(r'(?<=[.!?"”])\s+', text)
+    return [(s.strip(), len(s.strip())) for s in sentences if len(s.strip()) >= 20]
+
+
+def extract_pdf_en(path):
+    with open(path) as f:
+        lines = f.readlines()
+
+    body_start = None
+    for i, line in enumerate(lines):
+        if 'iving in this world' in line:
+            body_start = i
+            break
+    if body_start is None:
+        sys.exit("Could not find body start in PDF")
+
+    slug_re = re.compile(r'佛教徒的人生态度.*indd \d+')
+    header_re = re.compile(r'^(The Life Attitudes of Buddhists|The Mindful Peace Academy Collection)$')
+    page_num_re = re.compile(r'^\d{1,3}$')
+
+    text_lines = []
+    for i in range(body_start, len(lines)):
+        s = lines[i].strip()
+        if not s or s == '\x0c':
+            continue
+        if slug_re.search(s) or header_re.match(s) or page_num_re.match(s):
+            continue
+        text_lines.append(s)
+
+    # Join hyphenated breaks
+    joined = []
+    i = 0
+    while i < len(text_lines):
+        line = text_lines[i]
+        if line.rstrip().endswith('-') and i + 1 < len(text_lines):
+            n = text_lines[i+1].lstrip()
+            if n and n[0].islower():
+                joined.append(line.rstrip()[:-1] + n)
+                i += 2
+                continue
+        joined.append(line)
+        i += 1
+
+    body = ' '.join(joined)
+    body = re.sub(r'\s+', ' ', body).strip()
+    body = body.replace('L iving', 'Living')
+    return body
+
+
+def normalize_for_search(s):
+    """Normalize text for fuzzy matching."""
+    s = re.sub(r'\s+', ' ', s).strip().lower()
+    # Normalize quotes
+    s = s.replace('\u201c', '"').replace('\u201d', '"')
+    s = s.replace('\u2018', "'").replace('\u2019', "'")
+    return s
+
+
+def find_sentence_in_pdf(sentence, pdf_body):
+    """Try to locate sentence in PDF body. Returns (found, matched_text)."""
+    s_norm = normalize_for_search(sentence)
+    # Try full sentence
+    if s_norm in pdf_body.lower():
+        return True, sentence
+    # Try first 60 chars
+    key = s_norm[:60]
+    if key in pdf_body.lower():
+        return True, sentence
+    # Try first 30 chars
+    key = s_norm[:30]
+    if key in pdf_body.lower():
+        return True, sentence
+    return False, None
+
+
+def find_word_diff(docx_sentence, pdf_sentence):
+    """Find word-level differences between two matched sentences."""
+    if not pdf_sentence:
+        return []
+    dw = re.findall(r'\S+', docx_sentence)
+    pw = re.findall(r'\S+', pdf_sentence)
+    diffs = []
+    for dwi, pwi in zip(dw, pw):
+        if dwi.lower() != pwi.lower():
+            diffs.append((dwi, pwi))
+    if len(dw) != len(pw):
+        diffs.append((f"[{len(dw)} words]", f"[{len(pw)} words]"))
+    return diffs
+
+
+if __name__ == '__main__':
+    if len(sys.argv) != 3:
+        sys.exit("Usage: proofread-pdf.py <docx_path> <pdf_path>")
+
+    docx_path, pdf_path = sys.argv[1], sys.argv[2]
+    docx_txt = '/tmp/proofread_docx.txt'
+    pdf_txt = '/tmp/proofread_pdf.txt'
+
+    subprocess.run(['pandoc', docx_path, '-f', 'docx', '-t', 'plain', '--wrap=none', '-o', docx_txt], check=True)
+    subprocess.run(['pdftotext', '-layout', pdf_path, pdf_txt], check=True)
+
+    docx_sentences = extract_docx_en(docx_txt)
+    pdf_body = extract_pdf_en(pdf_txt)
+    pdf_normalized = normalize_for_search(pdf_body)
+
+    missing = []
+    found_count = 0
+    for sentence, length in docx_sentences:
+        s_norm = normalize_for_search(sentence)
+        if s_norm in pdf_normalized:
+            found_count += 1
+        elif s_norm[:60] in pdf_normalized:
+            found_count += 1
+        elif s_norm[:30] in pdf_normalized:
+            found_count += 1
+        else:
+            missing.append(sentence)
+
+    print(f"DOCX body sentences: {len(docx_sentences)}")
+    print(f"Matched in PDF: {found_count}")
+    print(f"Missing: {len(missing)}")
+    print()
+
+    if missing:
+        print("=== Sentences from DOCX NOT found in PDF ===")
+        for i, s in enumerate(missing):
+            print(f"\n--- Missing #{i+1} ---")
+            print(s[:200])