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优化数据获取

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oficcejo
2025-10-11 20:59:19 +08:00
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fund_flow_akshare.py
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"""
资金流向数据获取模块（akshare版本）
使用akshare的stock_individual_fund_flow接口获取个股资金流向
"""
import pandas as pd
import sys
import io
import warnings
from datetime import datetime
import akshare as ak
warnings.filterwarnings('ignore')
# 设置标准输出编码为UTF-8（仅在命令行环境，避免streamlit冲突）
def _setup_stdout_encoding():
"""仅在命令行环境设置标准输出编码"""
if sys.platform == 'win32' and not hasattr(sys.stdout, '_original_stream'):
try:
# 检测是否在streamlit环境中
import streamlit
# 在streamlit中不修改stdout
return
except ImportError:
# 不在streamlit环境，可以安全修改
try:
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='ignore')
except:
pass
_setup_stdout_encoding()
class FundFlowAkshareDataFetcher:
"""资金流向数据获取类（使用akshare数据源）"""
def __init__(self):
self.days = 20 # 获取最近20个交易日
self.available = True
print("[OK] 资金流向数据获取器初始化成功（akshare数据源）")
def get_fund_flow_data(self, symbol):
"""
获取个股资金流向数据
Args:
symbol: 股票代码（6位数字）
Returns:
dict: 包含资金流向数据的字典
"""
data = {
"symbol": symbol,
"fund_flow_data": None,
"data_success": False,
"source": "akshare"
}
# 只支持中国股票
if not self._is_chinese_stock(symbol):
data["error"] = "资金流向数据仅支持中国A股股票"
return data
try:
print(f"[资金流向] 正在获取 {symbol} 的资金流向数据...")
# 确定市场
market = self._get_market(symbol)
# 获取资金流向数据
fund_flow_data = self._get_individual_fund_flow(symbol, market)
if fund_flow_data:
data["fund_flow_data"] = fund_flow_data
print(f" [OK] 成功获取 {len(fund_flow_data.get('data', []))} 个交易日的资金流向数据")
data["data_success"] = True
print("[完成] 资金流向数据获取完成")
else:
print("[警告] 未能获取到资金流向数据")
except Exception as e:
print(f"[ERROR] 获取资金流向数据失败: {e}")
data["error"] = str(e)
return data
def _is_chinese_stock(self, symbol):
"""判断是否为中国股票"""
return symbol.isdigit() and len(symbol) == 6
def _get_market(self, symbol):
"""
根据股票代码判断市场
上海证券交易所: sh (60开头, 688开头)
深圳证券交易所: sz (00开头, 30开头)
北京证券交易所: bj (8开头, 4开头)
"""
if symbol.startswith('60') or symbol.startswith('688'):
return 'sh'
elif symbol.startswith('00') or symbol.startswith('30'):
return 'sz'
elif symbol.startswith('8') or symbol.startswith('4'):
return 'bj'
else:
# 默认深圳
return 'sz'
def _get_individual_fund_flow(self, symbol, market):
"""获取个股资金流向数据"""
try:
# 使用akshare的stock_individual_fund_flow接口
print(f" 使用 akshare 获取资金流向 (市场: {market})...")
df = ak.stock_individual_fund_flow(stock=symbol, market=market)
if df is None or df.empty:
print(f" 未找到资金流向数据")
return None
# akshare 返回的数据是按时间正序排列（从旧到新），所以使用 tail() 获取最近N天的数据
df = df.tail(self.days)
# 按日期倒序排列，让最新的数据在前面
df = df.iloc[::-1].reset_index(drop=True)
# 转换为字典列表
data_list = []
for idx, row in df.iterrows():
item = {}
for col in df.columns:
value = row.get(col)
if value is None or (isinstance(value, float) and pd.isna(value)):
continue
try:
# 保持数值类型
if isinstance(value, (int, float)):
item[col] = value
else:
item[col] = str(value)
except:
item[col] = "N/A"
if item:
data_list.append(item)
return {
"data": data_list,
"days": len(data_list),
"columns": df.columns.tolist(),
"market": market,
"query_time": datetime.now().strftime('%Y-%m-%d %H:%M:%S')
}
except Exception as e:
print(f" 获取资金流向数据异常: {e}")
import traceback
traceback.print_exc()
return None
def format_fund_flow_for_ai(self, data):
"""
将资金流向数据格式化为适合AI阅读的文本
"""
if not data or not data.get("data_success"):
return "未能获取资金流向数据"
text_parts = []
fund_flow_data = data.get("fund_flow_data")
if fund_flow_data:
text_parts.append(f"""
【个股资金流向数据 - akshare数据源】
股票代码：{data.get('symbol', 'N/A')}
市场：{fund_flow_data.get('market', 'N/A').upper()}
交易日数：最近{fund_flow_data.get('days', 0)}个交易日
查询时间：{fund_flow_data.get('query_time', 'N/A')}
═══════════════════════════════════════
[资金流向详细数据]
═══════════════════════════════════════
""")
# 显示每个交易日的数据
for idx, item in enumerate(fund_flow_data.get('data', []), 1):
date = item.get('日期', 'N/A')
close_price = item.get('收盘价', 'N/A')
change_pct = item.get('涨跌幅', 'N/A')
text_parts.append(f"""
第 {idx} 个交易日 ({date}):
基本信息:
- 收盘价: {close_price}
- 涨跌幅: {change_pct}%
主力资金:
- 主力净流入-净额: {item.get('主力净流入-净额', 'N/A')}
- 主力净流入-净占比: {item.get('主力净流入-净占比', 'N/A')}%
超大单:
- 超大单净流入-净额: {item.get('超大单净流入-净额', 'N/A')}
- 超大单净流入-净占比: {item.get('超大单净流入-净占比', 'N/A')}%
大单:
- 大单净流入-净额: {item.get('大单净流入-净额', 'N/A')}
- 大单净流入-净占比: {item.get('大单净流入-净占比', 'N/A')}%
中单:
- 中单净流入-净额: {item.get('中单净流入-净额', 'N/A')}
- 中单净流入-净占比: {item.get('中单净流入-净占比', 'N/A')}%
小单:
- 小单净流入-净额: {item.get('小单净流入-净额', 'N/A')}
- 小单净流入-净占比: {item.get('小单净流入-净占比', 'N/A')}%
""")
# 添加统计汇总
text_parts.append("""
═══════════════════════════════════════
[统计汇总 - 最近20个交易日]
═══════════════════════════════════════
""")
# 计算统计数据
data_list = fund_flow_data.get('data', [])
if data_list:
# 主力净流入统计
main_inflow_list = [item.get('主力净流入-净额', 0) for item in data_list if isinstance(item.get('主力净流入-净额'), (int, float))]
if main_inflow_list:
total_main_inflow = sum(main_inflow_list)
avg_main_inflow = total_main_inflow / len(main_inflow_list)
positive_days = len([x for x in main_inflow_list if x > 0])
negative_days = len([x for x in main_inflow_list if x < 0])
text_parts.append(f"""
主力资金统计:
- 累计净流入: {total_main_inflow:.2f}
- 平均每日净流入: {avg_main_inflow:.2f}
- 净流入天数: {positive_days}天
- 净流出天数: {negative_days}天
- 净流入占比: {positive_days/len(main_inflow_list)*100:.1f}%
""")
# 涨跌幅统计
change_pct_list = [item.get('涨跌幅', 0) for item in data_list if isinstance(item.get('涨跌幅'), (int, float))]
if change_pct_list:
avg_change = sum(change_pct_list) / len(change_pct_list)
up_days = len([x for x in change_pct_list if x > 0])
down_days = len([x for x in change_pct_list if x < 0])
text_parts.append(f"""
股价统计:
- 平均涨跌幅: {avg_change:.2f}%
- 上涨天数: {up_days}天
- 下跌天数: {down_days}天
- 上涨占比: {up_days/len(change_pct_list)*100:.1f}%
""")
return "\n".join(text_parts)
# 测试函数
if __name__ == "__main__":
print("测试资金流向数据获取（akshare数据源）...")
print("="*60)
fetcher = FundFlowAkshareDataFetcher()
if not fetcher.available:
print("[ERROR] 资金流向数据获取器不可用")
sys.exit(1)
# 测试股票
test_symbols = [
("000001", "平安银行"),
("600519", "贵州茅台"),
("000858", "五粮液")
]
for symbol, name in test_symbols:
print(f"\n{'='*60}")
print(f"正在测试股票: {name} ({symbol})")
print(f"{'='*60}\n")
data = fetcher.get_fund_flow_data(symbol)
if data.get("data_success"):
print("\n" + "="*60)
print("资金流向数据获取成功！")
print("="*60)
formatted_text = fetcher.format_fund_flow_for_ai(data)
# 只显示前2000个字符
preview = formatted_text[:2000] if len(formatted_text) > 2000 else formatted_text
print(preview)
if len(formatted_text) > 2000:
print(f"... (共 {len(formatted_text)} 字符)")
else:
print(f"\n获取失败: {data.get('error', '未知错误')}")
print("\n")