260 lines
8.9 KiB
Python
260 lines
8.9 KiB
Python
#!/usr/bin/env python3
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"""Convert textutil Word HTML export to ct-word-doc seed for ContractTemplate."""
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import json
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import re
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from pathlib import Path
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from typing import Dict, List, Optional, Set
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from bs4 import BeautifulSoup, NavigableString, Tag
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SRC = Path("/tmp/v266-contract.html")
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OUT = Path(__file__).resolve().parent.parent / "src/prototypes/contract-template-management/v266-lease-document.js"
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# Semantic ct-word classes for key blocks (layout still driven by embedded CSS)
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SEMANTIC = {
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"p2": "ct-word-title",
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"p3": "ct-word-contract-no",
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"p5": "ct-word-party-line",
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"p6": "ct-word-party-line",
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"p7": "ct-word-party-line",
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"p8": "ct-word-party-line",
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}
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def parse_css_rules(css_text: str) -> Dict[str, str]:
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rules: Dict[str, str] = {}
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for block in re.findall(r"([^{]+)\{([^}]+)\}", css_text):
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selector = block[0].strip()
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props = block[1].strip()
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if "," in selector:
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continue
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selector = selector.lstrip(".")
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if re.match(r"^(p|span|td|table)\.", selector):
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rules[selector] = props
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return rules
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def is_red_style(style: str) -> bool:
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return bool(re.search(r"color\s*:\s*#ff0000", style, re.I))
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def build_red_classes(rules: Dict[str, str]) -> Set[str]:
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red = set()
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for cls, props in rules.items():
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if is_red_style(props):
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red.add(cls.split(".")[-1])
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return red
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def class_list(tag: Tag) -> List[str]:
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raw = tag.get("class") or []
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if isinstance(raw, str):
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return raw.split()
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return list(raw)
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def primary_class(tag: Tag) -> Optional[str]:
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classes = class_list(tag)
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for c in classes:
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if c in SEMANTIC or re.match(r"^[pst]\d+$", c) or re.match(r"^td\d+$", c):
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return c
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return classes[0] if classes else None
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def merge_style(tag: Tag, rules: Dict[str, str]) -> None:
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parts: List[str] = []
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for c in class_list(tag):
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key_p = f"p.{c}" if c.startswith("p") else None
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key_s = f"span.{c}" if c.startswith("s") else None
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key_td = f"td.{c}" if c.startswith("td") else None
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key_t = f"table.{c}" if c.startswith("t") else None
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for key in (key_p, key_s, key_td, key_t):
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if key and key in rules:
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parts.append(rules[key])
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if parts:
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existing = tag.get("style", "")
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merged = ";".join([existing] + parts) if existing else ";".join(parts)
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tag["style"] = merged
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def strip_apple_noise(soup: BeautifulSoup) -> None:
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for el in soup.find_all(class_="Apple-converted-space"):
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el.replace_with("\u00a0" * max(1, len(el.get_text())))
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for el in soup.find_all(class_="Apple-tab-span"):
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el.replace_with("\t")
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def wrap_risk_redlines(soup: BeautifulSoup, red_classes: Set[str]) -> None:
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risk_seq = 0
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def next_id() -> str:
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nonlocal risk_seq
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risk_seq += 1
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return f"risk-{risk_seq}"
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def is_red_tag(tag: Tag) -> bool:
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pc = primary_class(tag)
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return pc in red_classes if pc else False
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# Block-level red paragraphs: wrap inner content once
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for p in list(soup.find_all("p")):
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if not is_red_tag(p):
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continue
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if p.find_parent(class_=lambda x: x and "ct-risk-redline" in x):
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continue
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inner = list(p.contents)
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if not inner:
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continue
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wrapper = soup.new_tag(
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"span",
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attrs={
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"class": "ct-risk-redline",
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"data-risk-redline": "1",
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"data-risk-id": next_id(),
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},
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)
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for child in inner:
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wrapper.append(child.extract() if isinstance(child, Tag) else child)
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p.clear()
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p.append(wrapper)
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# Inline red spans inside non-red paragraphs
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for span in list(soup.find_all("span")):
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if not is_red_tag(span):
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continue
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if span.find_parent(class_=lambda x: x and "ct-risk-redline" in x):
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continue
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parent_p = span.find_parent("p")
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if parent_p and is_red_tag(parent_p):
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continue
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wrapper = soup.new_tag(
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"span",
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attrs={
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"class": "ct-risk-redline",
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"data-risk-redline": "1",
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"data-risk-id": next_id(),
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},
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)
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span.wrap(wrapper)
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def apply_semantic_classes(root: Tag) -> None:
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for tag in root.find_all(True):
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pc = primary_class(tag)
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if pc and pc in SEMANTIC:
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classes = class_list(tag)
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extra = SEMANTIC[pc]
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if extra not in classes:
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tag["class"] = classes + [extra]
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def map_tables(root: Tag) -> None:
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for i, table in enumerate(root.find_all("table")):
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classes = class_list(table)
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if "ct-word-table" not in classes:
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table["class"] = classes + ["ct-doc-table", "ct-word-table"]
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if i == 0:
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for td in table.find_all("td"):
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tdc = primary_class(td)
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tr = td.find_parent("tr")
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row_idx = len(list(tr.find_previous_siblings("tr"))) if tr else 0
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if row_idx == 0:
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if tdc == "td1":
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td["class"] = class_list(td) + ["ct-word-party-left"]
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elif tdc == "td2":
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td["class"] = class_list(td) + ["ct-word-party-right"]
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else:
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td["class"] = class_list(td) + ["ct-word-td"]
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def apply_template_vars(html: str) -> str:
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regex_replacements = [
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(r"合同编号<span[^>]*>：</span>【LNZLHT\s*<span[^>]*>[\s\S]*?</span>\s*】",
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"合同编号：【LNZLHT {{contractCode}} 】"),
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(r"合同编号：【LNZLHT[^】]*】", "合同编号：【LNZLHT {{contractCode}} 】"),
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]
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literal_replacements = [
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("甲方（出租方）：羚牛氢能科技（广东）有限公司", "甲方（出租方）：{{lessorName}}"),
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("甲方(出租方): 羚牛氢能科技（广东）有限公司", "甲方(出租方): {{lessorName}}"),
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("甲方(出租方): 羚牛氢能科技（广东）有限公司", "甲方(出租方): {{lessorName}}"),
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("甲方：羚牛氢能科技（广东）有限公司", "甲方：{{lessorName}}"),
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("致：羚牛氢能科技（广东）有限公司", "致：{{lessorName}}"),
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("户 名：【羚牛氢能科技（广东）有限公司", "户 名：【{{lessorAccountName}}"),
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("开户行：【招商银行广州萝岗支行 】", "开户行：【{{lessorBankName}} 】"),
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("账 号：【120924165110201 】", "账 号：【{{lessorBankAccount}} 】"),
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("乙方</b><span class=\"s3\"><b>（承租方）：</b></span>",
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"乙方</b><span class=\"s3\"><b>（承租方）：{{customerName}}</b></span>"),
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("乙方(承租方):</b>", "乙方(承租方): {{customerName}}</b>"),
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("乙方（承租方）：</b>", "乙方（承租方）：{{customerName}}</b>"),
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]
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out = html
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for pattern, repl in regex_replacements:
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out = re.sub(pattern, repl, out)
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for old, new in literal_replacements:
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out = out.replace(old, new)
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return out
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def scope_css(css_text: str) -> str:
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scoped = []
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for block in re.findall(r"([^{]+)\{([^}]+)\}", css_text):
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selector = block[0].strip()
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props = block[1].strip()
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if selector.startswith("@") or "," in selector:
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continue
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scoped.append(f".ct-word-doc--v266 {selector}{{{props}}}")
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return "\n".join(scoped)
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def convert() -> str:
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raw = SRC.read_text(encoding="utf-8")
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css_match = re.search(r"<style[^>]*>([\s\S]*?)</style>", raw)
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body_match = re.search(r"<body>([\s\S]*?)</body>", raw)
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if not css_match or not body_match:
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raise SystemExit("Invalid source HTML")
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rules = parse_css_rules(css_match.group(1))
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red_classes = build_red_classes(rules)
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scoped = scope_css(css_match.group(1))
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soup = BeautifulSoup(body_match.group(1), "lxml")
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# lxml adds html/body wrapper
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root = soup.body or soup
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strip_apple_noise(soup)
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for tag in soup.find_all(True):
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merge_style(tag, rules)
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wrap_risk_redlines(soup, red_classes)
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apply_semantic_classes(soup)
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map_tables(soup)
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body_html = "".join(str(c) for c in (soup.body or soup).contents)
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body_html = apply_template_vars(body_html)
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body_html = re.sub(r"<p class=\"p1\"><br\s*/?></p>\s*", "", body_html, count=1)
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doc = (
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'<div class="ct-word-doc ct-word-doc--v266">'
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f"<style>{scoped}</style>"
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f"{body_html}"
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"</div>"
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)
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return doc
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def main() -> None:
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html = convert()
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escaped = json.dumps(html, ensure_ascii=False)
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OUT.write_text(
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"// AUTO-GENERATED V26.6 Word HTML — do not edit by hand\n"
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f"export var V266_LEASE_DOCUMENT_HTML = {escaped};\n",
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encoding="utf-8",
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)
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print(f"Wrote {OUT} ({OUT.stat().st_size} bytes)")
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print(f"Redline markers: {html.count('data-risk-redline')}")
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if __name__ == "__main__":
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main()
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