121 lines
3.3 KiB
Python
121 lines
3.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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cn-financial-scraper 一键舆情爬取工具 v4.3
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用法：
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方式1（交互式）: python run_sentiment.py
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方式2（命令行）: python run_sentiment.py "贵州茅台最近7天的舆情"
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"""
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import sys
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import os
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from pathlib import Path
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SCRIPTS_DIR = Path(__file__).resolve().parent / "scripts"
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sys.path.insert(0, str(SCRIPTS_DIR))
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sys.dont_write_bytecode = True
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os.environ.setdefault("PYTHONDONTWRITEBYTECODE", "1")
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def check_env():
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issues = []
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if sys.version_info < (3, 8):
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issues.append(f"Python 版本过低: {sys.version}，需要 3.8+")
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missing = []
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for mod, desc in [
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("http_utils", "HTTP 基础"),
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("scraper", "基础爬虫"),
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("sentiment_crawler", "舆情爬虫引擎"),
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("sentiment_chat", "对话入口"),
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]:
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try:
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__import__(mod)
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except ImportError:
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missing.append(desc)
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if missing:
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mod_names = ", ".join(missing)
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issues.append(f"缺少核心模块: {mod_names}")
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issues.append("请先运行: python setup_env.py")
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if issues:
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print("=" * 50)
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print(" 环境检测发现问题:")
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for i in issues:
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print(f" {i}")
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print("=" * 50)
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return False
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return True
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def show_banner():
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print()
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print(" cn-financial-scraper 中国金融舆情爬虫 v5.0.0")
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print(" " + "-" * 46)
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print()
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def run_interactive():
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show_banner()
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print("请输入你想爬取的内容，例如：")
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print(' "贵州茅台最近7天的舆情"')
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print(' "工银瑞信基金最近3天的负面新闻"')
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print(' "哪些媒体可用？"')
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print(' "帮助" 查看完整指南')
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print(' 输入 quit 退出')
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print()
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from sentiment_chat import chat_handle
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while True:
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try:
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user_input = input("> ").strip()
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except (EOFError, KeyboardInterrupt):
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print()
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print("再见！")
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break
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if not user_input:
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continue
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if user_input.lower() in ("quit", "exit", "q", "退出"):
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print("再见！")
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break
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print()
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result = chat_handle(user_input)
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print(result.get("reply", "无法处理该请求"))
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print()
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def main():
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if not check_env():
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ans = input("是否现在运行 setup_env.py 安装依赖? (y/n): ").strip().lower()
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if ans in ("y", "yes"):
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setup_path = Path(__file__).resolve().parent / "setup_env.py"
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if setup_path.exists():
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os.system(f'"{sys.executable}" "{setup_path}"')
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print()
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print("安装完成，请重新运行本脚本。")
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else:
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print("未找到 setup_env.py")
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sys.exit(1)
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from sentiment_chat import chat_handle
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if len(sys.argv) > 1:
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text = " ".join(sys.argv[1:])
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text_clean = text.replace("--export", "").strip()
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show_banner()
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print(f"正在处理: {text_clean}")
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print()
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result = chat_handle(text_clean)
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print(result.get("reply", "无法处理该请求"))
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if "--export" in text and result.get("output"):
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from sentiment_exporter import export as export_sentiment
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export_sentiment(result["output"], fmt="all")
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return
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run_interactive()
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if __name__ == "__main__":
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main()
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