restore and rebuild all stock query scripts

Recover 7 existing scripts from remote repo and rebuild 5 missing ones:
- twse-margin-trading.py (融資融券)
- twse-day-trading.py (當沖交易)
- twse-foreign-holdings.py (外資持股)
- yahoo-dividend-browserless.py (股利資訊)
- yahoo-broker-trading-browserless.py (主力券商進出)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

scripts/yahoo-etf-holdings.py

@@ -0,0 +1,164 @@
+#!/usr/bin/env python3
+"""抓 Yahoo 台股 ETF 持股分析頁的前十大持股 / 行業比重 / 資產分佈。"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import re
+import sys
+import urllib.request
+from html import unescape
+
+USER_AGENT = "Mozilla/5.0 (OpenClaw; yahoo-etf-holdings)"
+BASE_URL = "https://tw.stock.yahoo.com/quote/{symbol}.TW/holding"
+
+
+def fetch(url: str) -> str:
+    req = urllib.request.Request(url, headers={"User-Agent": USER_AGENT})
+    with urllib.request.urlopen(req, timeout=30) as response:
+        return response.read().decode("utf-8", "ignore")
+
+
+def strip_tags(text: str) -> str:
+    return unescape(re.sub(r"<[^>]+>", "", text)).strip()
+
+
+def extract_date(block: str) -> str:
+    m = re.search(r'<time[^>]*datatime="([0-9]{4}/[0-9]{2}/[0-9]{2})"', block)
+    return m.group(1) if m else ""
+
+
+def extract_block(html: str, start_marker: str, end_marker: str | None = None) -> str:
+    start = html.find(start_marker)
+    if start == -1:
+        return ""
+    sub = html[start:]
+    if end_marker:
+        end = sub.find(end_marker)
+        if end != -1:
+            sub = sub[:end]
+    return sub
+
+
+def parse_rank_list(block: str, value_class: str, limit: int | None = None) -> list[dict[str, str]]:
+    pattern = re.compile(
+        rf'">(\d+)\.</div>([^<]+)</div><div class="{re.escape(value_class)}">([0-9]+\.[0-9]+%)</div>',
+        re.S,
+    )
+    items = []
+    for rank, name, pct in pattern.findall(block):
+        items.append({"排名": rank, "名稱": strip_tags(name), "占比": pct})
+        if limit and len(items) >= limit:
+            break
+    return items
+
+
+def parse_industries(block: str) -> list[dict[str, str]]:
+    pattern = re.compile(
+        r'<div class="D\(f\) Ai\(c\)">(?:<div[^>]*></div>)?([^<]+)</div><div class="Fx\(n\) Fw\(b\) Pstart\(12px\)">([0-9]+\.[0-9]+%)</div>',
+        re.S,
+    )
+    items = []
+    for idx, (name, pct) in enumerate(pattern.findall(block), start=1):
+        items.append({"排名": str(idx), "名稱": strip_tags(name), "占比": pct})
+    return items
+
+
+def parse_holding_page(symbol: str) -> dict:
+    url = BASE_URL.format(symbol=symbol)
+    html = fetch(url)
+
+    asset_block = extract_block(html, '資產分佈</h2>', '前十大持股</h2>')
+    top_block = extract_block(html, '前十大持股</h2>', '網友也在看')
+    industry_block = extract_block(html, '行業比重</h2>', '持股明細</h2>')
+
+    assets = parse_rank_list(asset_block, 'Fx(n) Pstart(16px)')
+    top10 = parse_rank_list(top_block, 'Fx(n) Pstart(16px)', limit=10)
+    industries = parse_industries(industry_block)
+
+    return {
+        "symbol": symbol,
+        "url": url,
+        "asset_date": extract_date(asset_block),
+        "assets": assets,
+        "top10_date": extract_date(top_block),
+        "top10": top10,
+        "industry_date": extract_date(industry_block),
+        "industries": industries,
+    }
+
+
+def print_section(title: str, date: str, items: list[dict[str, str]]) -> None:
+    print(f"{title}｜資料時間：{date or '無資料'}")
+    for item in items:
+        print(f"{item['排名']}. {item['名稱']}：{item['占比']}")
+    print()
+
+
+def write_json(data: dict, out: str | None) -> None:
+    text = json.dumps(data, ensure_ascii=False, indent=2)
+    if out:
+        with open(out, 'w', encoding='utf-8') as f:
+            f.write(text)
+    else:
+        print(text)
+
+
+def write_csv(data: dict, out: str | None, section: str) -> None:
+    mapping = {
+        'top': ('top10', 'top10_date'),
+        'industry': ('industries', 'industry_date'),
+        'asset': ('assets', 'asset_date'),
+    }
+    rows = []
+    if section == 'all':
+        for sec in ['top', 'industry', 'asset']:
+            key, date_key = mapping[sec]
+            rows.extend({"section": sec, "data_date": data[date_key], **item} for item in data[key])
+    else:
+        key, date_key = mapping[section]
+        rows.extend({"section": section, "data_date": data[date_key], **item} for item in data[key])
+
+    fieldnames = ['section', 'data_date', '排名', '名稱', '占比']
+    if out:
+        f = open(out, 'w', encoding='utf-8-sig', newline='')
+    else:
+        f = sys.stdout
+    try:
+        writer = csv.DictWriter(f, fieldnames=fieldnames)
+        writer.writeheader()
+        writer.writerows(rows)
+    finally:
+        if out:
+            f.close()
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description='抓 Yahoo ETF 持股分析頁資料')
+    parser.add_argument('symbol', help='ETF 代號，例如 00922、0050')
+    parser.add_argument('--format', choices=['text', 'json', 'csv'], default='text')
+    parser.add_argument('--section', choices=['all', 'top', 'industry', 'asset'], default='all')
+    parser.add_argument('--out', help='輸出檔案路徑')
+    args = parser.parse_args()
+
+    data = parse_holding_page(args.symbol)
+
+    if args.format == 'json':
+        write_json(data, args.out)
+        return
+    if args.format == 'csv':
+        write_csv(data, args.out, args.section)
+        return
+
+    if args.section in ('all', 'top'):
+        print_section(f"{args.symbol} 前十大持股", data['top10_date'], data['top10'])
+    if args.section in ('all', 'industry'):
+        print_section(f"{args.symbol} 行業比重", data['industry_date'], data['industries'])
+    if args.section in ('all', 'asset'):
+        print_section(f"{args.symbol} 資產分佈", data['asset_date'], data['assets'])
+
+
+if __name__ == '__main__':
+    main()