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