oficcejo
147 lines
4.9 KiB
Python
147 lines
4.9 KiB
Python
"""
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调试风险数据获取和格式化
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检查数据是否真的传递给AI
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"""
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from risk_data_fetcher import RiskDataFetcher
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import json
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def test_full_data_flow(symbol="300433"):
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"""测试完整数据流程"""
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print("=" * 80)
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print(f"测试股票: {symbol}")
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print("=" * 80)
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fetcher = RiskDataFetcher()
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# 1. 获取原始数据
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print("\n【步骤1】获取原始风险数据...")
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risk_data = fetcher.get_risk_data(symbol)
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print(f"\n数据获取成功: {risk_data.get('data_success', False)}")
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# 2. 查看每类数据的详情
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print("\n【步骤2】查看原始数据详情...")
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# 限售解禁
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lifting_ban = risk_data.get('lifting_ban')
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if lifting_ban:
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print(f"\n限售解禁数据:")
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print(f" has_data: {lifting_ban.get('has_data')}")
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df = lifting_ban.get('data')
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if df is not None:
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print(f" 记录数: {len(df)}")
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print(f" 列名: {list(df.columns)}")
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print(f"\n 前3条数据:")
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print(df.head(3))
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else:
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print(f" data字段为None")
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# 大股东减持
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reduction = risk_data.get('shareholder_reduction')
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if reduction:
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print(f"\n大股东减持数据:")
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print(f" has_data: {reduction.get('has_data')}")
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df = reduction.get('data')
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if df is not None:
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print(f" 记录数: {len(df)}")
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print(f" 列名: {list(df.columns)}")
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print(f"\n 前3条数据:")
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print(df.head(3))
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print(f"\n 完整第1条数据:")
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if len(df) > 0:
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first_row = df.iloc[0]
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for col in df.columns:
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print(f" {col}: {first_row[col]}")
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else:
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print(f" data字段为None")
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# 重要事件
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events = risk_data.get('important_events')
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if events:
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print(f"\n重要事件数据:")
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print(f" has_data: {events.get('has_data')}")
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df = events.get('data')
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if df is not None:
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print(f" 记录数: {len(df)}")
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print(f" 列名: {list(df.columns)}")
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print(f"\n 前3条数据:")
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print(df.head(3))
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else:
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print(f" data字段为None")
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# 3. 测试格式化后的数据
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print("\n" + "=" * 80)
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print("【步骤3】测试格式化后传给AI的数据")
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print("=" * 80)
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formatted_data = fetcher.format_risk_data_for_ai(risk_data)
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print("\n格式化后的数据长度:", len(formatted_data), "字符")
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print("\n格式化后的数据内容:")
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print(formatted_data)
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# 4. 保存到文件供查看
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print("\n" + "=" * 80)
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print("【步骤4】保存数据到文件")
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print("=" * 80)
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with open("risk_data_debug_output.txt", "w", encoding="utf-8") as f:
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f.write("=" * 80 + "\n")
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f.write("原始数据结构\n")
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f.write("=" * 80 + "\n\n")
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# 保存原始数据（不包含DataFrame，只保存基本信息）
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f.write("data_success: " + str(risk_data.get('data_success')) + "\n\n")
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for key in ['lifting_ban', 'shareholder_reduction', 'important_events']:
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data = risk_data.get(key)
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if data:
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f.write(f"\n{key}:\n")
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f.write(f" has_data: {data.get('has_data')}\n")
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f.write(f" query: {data.get('query')}\n")
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df = data.get('data')
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if df is not None:
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f.write(f" 记录数: {len(df)}\n")
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f.write(f" 列名: {list(df.columns)}\n")
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f.write("\n" + "=" * 80 + "\n")
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f.write("格式化后传给AI的数据\n")
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f.write("=" * 80 + "\n\n")
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f.write(formatted_data)
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print("✓ 数据已保存到 risk_data_debug_output.txt")
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# 5. 检查数据是否完整
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print("\n" + "=" * 80)
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print("【步骤5】数据完整性检查")
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print("=" * 80)
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if "【大股东减持数据】" in formatted_data:
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print("✓ 格式化数据中包含大股东减持数据")
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# 检查是否有实际内容
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reduction_section = formatted_data.split("【大股东减持数据】")[1].split("=" * 80)[0]
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if len(reduction_section.strip()) > 100:
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print(f"✓ 减持数据部分有 {len(reduction_section)} 字符")
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else:
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print(f"⚠️ 减持数据部分只有 {len(reduction_section)} 字符，可能数据不完整")
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else:
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print("❌ 格式化数据中未找到大股东减持数据")
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print("\n" + "=" * 80)
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print("测试完成！请查看 risk_data_debug_output.txt 文件")
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print("=" * 80)
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if __name__ == "__main__":
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import sys
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# 默认测试300433，也可以通过命令行参数指定其他股票
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symbol = sys.argv[1] if len(sys.argv) > 1 else "300433"
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test_full_data_flow(symbol)
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