169 lines
5.4 KiB
Python
169 lines
5.4 KiB
Python
import requests
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import pandas as pd
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import json
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from datetime import datetime
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import matplotlib.pyplot as plt
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import matplotlib
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import numpy as np
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import tkinter as tk
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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from matplotlib.figure import Figure
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matplotlib.rcParams['font.sans-serif'] = ['SimHei'] # 设置中文字体为黑体
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matplotlib.rcParams['axes.unicode_minus'] = False # 解决负号显示问题
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def get_fund_flow_data():
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"""获取资金流向数据，包括板块和股票名称"""
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url = "https://push2delay.eastmoney.com/api/qt/clist/get"
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params = {
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'fid': 'f184',
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'po': '1',
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'pz': '50',
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'pn': '1',
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'np': '1',
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'fltt': '2',
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'invt': '2',
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'fields': 'f2,f3,f12,f13,f14,f62,f184,f225,f165,f263,f109,f175,f264,f160,f100,f124,f265,f1',
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'ut': 'b2884a393a59ad64002292a3e90d46a5',
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'fs': 'm:0+t:6+f:!2,m:0+t:13+f:!2,m:0+t:80+f:!2,m:1+t:2+f:!2,m:1+t:23+f:!2,m:0+t:7+f:!2,m:1+t:3+f:!2',
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}
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headers = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
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'Referer': 'https://data.eastmoney.com/zjlx/list.html'
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}
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try:
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response = requests.get(url, params=params, headers=headers)
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print(response.text)
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data = json.loads(response.text)
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if 'data' not in data or 'diff' not in data['data']:
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raise Exception("未能获取到数据")
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items = data['data']['diff']
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parsed_data = []
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for idx, item in enumerate(items[:50]):
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# 获取每个板块的股票名称
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stock_names = item.get('f14', '')
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# 打印调试信息，检查 f62 字段的内容
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print(f"板块 {item['f14']} - f62 字段内容: {stock_names}")
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if isinstance(stock_names, str):
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stock_names = stock_names.split(';') # 假设股票名称以分号分隔
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else:
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stock_names = [] # 如果 f62 为空或格式不正确，设置为空列表
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# 如果股票名称为空，则跳过该项
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if not stock_names:
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print(f"板块 {item['f14']} 没有有效的股票名称")
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continue
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# 计算三者的平均排名
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avg_rank = np.mean([item['f225'], item['f263'], item['f264']])
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parsed_data.append({
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'股票名称': stock_names[0], # 只取第一个股票名称
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'今日排名': item['f225'],
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'5日排名': item['f263'],
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'10日排名': item['f264'],
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'平均排名': avg_rank
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})
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return pd.DataFrame(parsed_data)
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except Exception as e:
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print(f"获取数据时发生错误: {str(e)}")
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return None
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def create_ranking_visualization(data):
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"""创建排名可视化窗口"""
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root = tk.Tk()
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root.title("股票资金流向排名对比")
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root.geometry("1500x900")
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root.configure(bg='#2C3E50') # 深色背景
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fig = Figure(figsize=(15, 10))
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ax = fig.add_subplot(111)
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# 设置样式
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ax.set_facecolor('#FFFFFF') # 设置背景色
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fig.patch.set_facecolor('#FFFFFF') # 设置背景色
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# 准备数据
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stock_names = data['股票名称'].tolist()[:30] # 只显示前15个股票，避免过于拥挤
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avg_ranks = data['平均排名'].tolist()[:30]
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# 设置柱状图位置
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x = np.arange(len(stock_names))
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width = 0.5 # 设置柱状图宽度
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# 绘制柱状图
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rects1 = ax.bar(x, avg_ranks, width, label='平均排名', color='#2980B9', alpha=0.9, edgecolor='black')
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# 设置标题和标签
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ax.set_title('股票资金流向排名对比（排名越高表示资金流入越多）', fontsize=18, pad=20, color='black')
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ax.set_xlabel('股票名称', fontsize=14, color='black')
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ax.set_ylabel('平均排名', fontsize=14, color='black')
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# 设置x轴刻度
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ax.set_xticks(x)
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ax.set_xticklabels(stock_names, rotation=45, ha='right', fontsize=12, color='black')
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# 设置y轴范围和刻度
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ax.set_ylim(0, 55)
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ax.set_yticks(np.arange(0, 51, 10))
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# 添加图例
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ax.legend(loc='upper right', fontsize=12)
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# 设置网格
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ax.grid(True, linestyle='--', alpha=0.3, axis='y')
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# 调整布局
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fig.tight_layout()
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# 创建canvas
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canvas = FigureCanvasTkAgg(fig, master=root)
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canvas.draw()
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canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
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# 生成并显示词云
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plt.figure(figsize=(8, 6))
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plt.axis('off')
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plt.show()
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# 添加关闭按钮
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close_button = tk.Button(root, text="关闭", command=root.quit, font=('SimHei', 12), bg='#C82423', fg='white', padx=10, pady=5)
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close_button.pack(side=tk.BOTTOM, pady=10)
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return root
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def main():
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# 获取资金流向数据
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print("正在获取资金流向数据...")
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data = get_fund_flow_data()
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if data is not None:
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# 保存数据到Excel
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current_date = datetime.now().strftime('%Y%m%d')
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output_file = f'fund_flow_ranking_{current_date}.xlsx'
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data.to_excel(output_file, index=False)
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print(f"资金流向数据已保存到: {output_file}")
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# 创建并显示可视化窗口
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print("正在创建可视化窗口...")
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root = create_ranking_visualization(data)
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root.mainloop()
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else:
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print("获取数据失败，请检查网络连接或接口可用性。")
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if __name__ == "__main__":
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main()
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