Yahoo Finance Scraper

Enter stock symbols, one per line. US: AAPL, MSFT, GOOGL. HK: 0700.HK (Tencent), 9988.HK (Alibaba). A-share: 600519.SS (Moutai), 000001.SZ (Ping An). | 输入股票代码，每行一个。美股: AAPL, MSFT, GOOGL。港股: 0700.HK(腾讯), 9988.HK(阿里)。A股: 600519.SS(茅台), 000001.SZ(平安)

history: Daily OHLCV data. info: Company profile. financials: Income statement. balance_sheet: Assets & liabilities. cashflow: Cash flow. earnings: Quarterly earnings. dividends: Dividend history. splits: Stock split history. recommendations: Analyst ratings. news: Related news. calendar: Earnings dates. search: Find stocks by keyword. download: Batch download CSV. | history: 日K线数据。info: 公司简介。financials: 利润表。balance_sheet: 资产负债表。cashflow: 现金流量表。earnings: 季度盈利。dividends: 分红历史。splits: 拆股历史。recommendations: 分析师评级。news: 相关新闻。calendar: 财报日期。search: 搜索股票。download: 批量下载CSV

Time range for historical data. Only for 'history' and 'download' actions. Note: 1m/5m only available for last 7 days, 15m/30m for last 60 days, 1h for last 730 days. | 历史数据的时间范围。仅对「历史行情」和「批量下载」有效。注意: 1分钟/5分钟仅最近7天可用，15分钟/30分钟仅最近60天，1小时仅最近730天

K-line interval for historical data. Only for 'history' and 'download' actions. Intraday intervals have limited time range. | K线周期。仅对「历史行情」和「批量下载」有效。日内周期有时间范围限制

Keywords for stock search. Only for 'search' action. Example: Apple, Tesla, Tencent, 腾讯, 阿里巴巴. | 搜索股票的关键词。仅对「搜索股票」有效。例如: Apple, Tesla, 腾讯, 阿里巴巴

For advanced users: Manually specify each API call with full control. Leave empty to use simple mode above. Example below shows how to fetch AAPL history. | 高级用户专用：手动指定每个API调用，完全控制参数。留空使用上面的简化模式。下方示例展示如何获取AAPL历史行情

Continue fetching other stocks when one fails. Recommended: true for batch processing. | 某个股票获取失败时继续获取其他股票。批量处理时建议开启

Number of retries when rate limited by Yahoo Finance API. Set to 3-5 for stable operation. | Yahoo Finance API 限速时的重试次数。建议设置 3-5 次以稳定运行

Delay between requests to avoid rate limiting. Recommended: 0.5-2 seconds. | 请求间隔时间，避免触发限速。建议 0.5-2 秒

Include Python type information in results. Useful for debugging. | 在结果中包含Python类型信息。调试时有用

Flatten DataFrame rows into individual records. Recommended: true for easier data processing. | 将DataFrame按行展开为独立记录。建议开启，便于后续数据处理