261 lines
8.5 KiB
Python
261 lines
8.5 KiB
Python
"""
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Generate bilingual.dj for 佛教徒的人生态度.
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Source: Chinese from DOCX manuscript.
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Target: English from PDF typeset.
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Strategy: find each DOCX English paragraph in PDF body, extract
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the PDF text region for that paragraph using position boundaries.
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"""
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import re, subprocess, os
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DOCX = "/home/user/documents/mpi/translate-files/佛教徒的人生态度/定稿 佛教徒的人生态度 善鑫慧炬照禅道靖妙一观轩慈德20260527.docx"
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PDF = "/home/user/documents/mpi/translate-files/佛教徒的人生态度/0607-二排-果澄-佛教徒的人生态度-一校-多人-0607.pdf"
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OUT_DIR = "/home/user/documents/mpi/translate-files/佛教徒的人生态度"
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def has_cjk(s):
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return any('\u4e00' <= c <= '\u9fff' for c in s)
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def pandoc(path):
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r = subprocess.run(['pandoc', path, '-f', 'docx', '-t', 'plain', '--wrap=none'],
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capture_output=True, text=True)
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return r.stdout
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def extract_docx_pairs(text):
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"""Return [(cn_para, en_para), ...] from body onwards."""
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lines = text.split('\n')
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body_start = None
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for i, l in enumerate(lines):
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if '生活在这个世间' in l:
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body_start = i
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break
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pairs = []
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i = body_start
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while i < len(lines):
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cn = lines[i].strip()
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if not cn or not has_cjk(cn):
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i += 1
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continue
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en = ''
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if i + 2 < len(lines) and lines[i+1].strip() == '':
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ec = lines[i+2].strip()
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if ec and not has_cjk(ec):
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en = ec
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i += 3
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else:
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i += 1
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else:
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i += 1
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continue
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pairs.append((cn, en))
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return pairs
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def extract_pdf_body(text):
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"""Return cleaned PDF body string."""
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lines = text.split('\n')
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body_start = None
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for i, l in enumerate(lines):
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if 'iving in this world' in l.strip():
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body_start = i
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break
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slug_re = re.compile(r'佛教徒的人生态度.*indd \d+')
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hdr_re = re.compile(r'^(The Life Attitudes of Buddhists|The Mindful Peace Academy Collection)$')
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pn_re = re.compile(r'^\d{1,3}$')
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tl = []
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for i in range(body_start, len(lines)):
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s = lines[i].strip()
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if not s or s == '\x0c':
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continue
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if slug_re.search(s) or hdr_re.match(s) or pn_re.match(s):
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continue
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tl.append(s)
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# Join hyphenation breaks — handle consecutive breaks
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joined = []
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i = 0
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while i < len(tl):
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line = tl[i].rstrip()
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if line.endswith('-') and i + 1 < len(tl):
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n = tl[i+1].lstrip()
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if n and n[0].islower():
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merged = line[:-1] + n
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# Check if MORE consecutive breaks follow
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j = i + 2
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while j < len(tl) and merged.rstrip().endswith('-'):
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nn = tl[j].lstrip()
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if nn and nn[0].islower():
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merged = merged.rstrip()[:-1] + nn
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j += 1
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else:
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break
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joined.append(merged)
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i = j
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continue
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joined.append(line)
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i += 1
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body = ' '.join(joined)
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body = re.sub(r'\s+', ' ', body).strip()
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body = body.replace('L iving', 'Living')
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return body
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def norm(s):
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s = re.sub(r'\s+', ' ', s).strip().lower()
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s = s.replace('\u201c', '"').replace('\u201d', '"')
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s = s.replace('\u2018', "'").replace('\u2019', "'")
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return s
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def find_positions(pairs, pdf_body):
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"""For each DOCX English para, find start position in PDF body.
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Returns list of (start_pos or None, matched_text or None).
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"""
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positions = []
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last_pos = 0
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for cn, en in pairs:
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needle = norm(en)
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haystack = norm(pdf_body[last_pos:])
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# Try full match
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idx = haystack.find(needle)
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if idx < 0:
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# Try first 80 chars
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key = needle[:80]
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idx = haystack.find(key)
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if idx < 0:
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# Try first 40 chars
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key = needle[:40]
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idx = haystack.find(key)
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if idx < 0:
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# Try first 25 chars
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key = needle[:25]
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idx = haystack.find(key)
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if idx >= 0:
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pos = last_pos + idx
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positions.append(pos)
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last_pos = pos + max(len(needle), 30)
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else:
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positions.append(None)
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return positions
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def extract_segments(pdf_body, positions):
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"""For each position, extract the PDF text region.
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Region extends from positions[i] to positions[i+1] (or end),
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trimmed to avoid bleeding into the next paragraph.
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"""
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segments = []
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for i, pos in enumerate(positions):
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if pos is None:
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segments.append(None)
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continue
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start = pos
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end = len(pdf_body)
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for j in range(i + 1, len(positions)):
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if positions[j] is not None:
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end = positions[j]
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break
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raw = pdf_body[start:end].strip()
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# Trim: if raw contains what looks like the NEXT paragraph's heading,
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# cut at the last sentence boundary before it.
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# Headings match patterns like: "I Passive", "1) Expressions", "1. The Definitions"
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heading_pattern = re.compile(
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r'\s+(?=[IVX]+\.?\s+[A-Z]' # Roman numeral chapter
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r'|\d+\)\s+[A-Z]' # 1) Sub-heading
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r'|\(\d+\)\s+[A-Z]' # (1) Sub-heading
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r'|\d+\.\s+[A-Z][a-z]+.*?(?:Passive|Pessimism|Abstinence|Focus|Benefit|Transcending|Love|Adapting|Conclusion|Desire|Being|What|How|The|Buddhism|Set|Free|A Middle)' # Numbered heading
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r')'
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)
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m = heading_pattern.search(raw)
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if m:
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# Cut before this heading
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raw = raw[:m.start()].strip()
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segments.append(raw)
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return segments
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def generate(pairs, segments, out_path):
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lines = []
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# Title
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lines.append('# 佛教徒的人生态度')
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lines.append('# The Life Attitudes of Buddhists')
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lines.append('')
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lines.append('------2014年秋讲于第九届菩提静修营')
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lines.append('---Lecture Given at the 9th Bodhi Meditation Retreat, 2014')
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lines.append('')
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lines.append(' 济群法师 ')
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lines.append('Master Jiqun')
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lines.append('')
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# TOC from DOCX
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lines.append('- 一、消极还是积极')
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lines.append('- 二、悲观还是乐观')
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lines.append('- 三、禁欲还是纵欲')
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lines.append('- 四、重生还是重死')
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lines.append('- 五、自利还是利他')
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lines.append('- 六、出世还是入世')
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lines.append('- 七、无情还是多情')
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lines.append('- 八、随缘还是进取')
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lines.append('- 九、结束语')
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lines.append('')
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lines.append('- I. Passive or Proactive')
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lines.append('- II. Pessimism or Optimism')
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lines.append('- III. Abstinence or Indulgence')
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lines.append('- IV. Focus on Life or on Death')
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lines.append('- V. Benefit Oneself or Benefit Others')
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lines.append('- VI. Transcending the World or Engaging with the World')
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lines.append('- VII. To Love or Not to Love')
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lines.append('- VIII. Adapting to Conditions or Striving for Progress')
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lines.append('- IX. Conclusion')
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lines.append('')
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# Body
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for (cn, en), seg in zip(pairs, segments):
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target = seg if seg else en
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lines.append(cn)
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lines.append(target)
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lines.append('')
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with open(out_path, 'w') as f:
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f.write('\n'.join(lines))
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matched = sum(1 for s in segments if s is not None)
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print(f"Written: {out_path}")
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print(f" Paragraphs: {len(pairs)}, matched from PDF: {matched}, fallback to DOCX: {len(pairs) - matched}")
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if __name__ == '__main__':
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print("Extracting DOCX...")
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docx_text = pandoc(DOCX)
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pairs = extract_docx_pairs(docx_text)
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print(f" Pairs: {len(pairs)}")
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print("Extracting PDF...")
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r = subprocess.run(['pdftotext', '-layout', PDF, '/tmp/_bilingual_pdf.txt'], check=True)
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with open('/tmp/_bilingual_pdf.txt') as f:
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pdf_raw = f.read()
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pdf_body = extract_pdf_body(pdf_raw)
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print(f" PDF body: {len(pdf_body)} chars")
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print("Finding positions...")
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positions = find_positions(pairs, pdf_body)
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found = sum(1 for p in positions if p is not None)
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print(f" Found: {found}/{len(pairs)}")
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print("Extracting segments...")
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segments = extract_segments(pdf_body, positions)
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out = os.path.join(OUT_DIR, 'bilingual.dj')
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generate(pairs, segments, out)
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