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+from flask import Flask, render_template, request, redirect, url_for
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+import pandas as pd
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+from werkzeug.utils import secure_filename
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+import os
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+from collections import Counter
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+import tushare as ts
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+
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+# 初始化Tushare和Flask应用
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+pro = ts.pro_api('a9b83bc559587ad8b391c631b5e4eb93bd304f918c8700a81b13604f')
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+app = Flask(__name__)
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+app.config['UPLOAD_FOLDER'] = 'uploads/'
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+
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+# 创建 uploads 文件夹，如果不存在
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+if not os.path.exists(app.config['UPLOAD_FOLDER']):
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+ os.makedirs(app.config['UPLOAD_FOLDER'])
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+
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+# 用户提供的函数
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+def tsdate(date):
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+ return date.replace('-', '')
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+
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+def tscode(code):
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+ return code + '.SH' if code[0] == '6' else code + '.SZ'
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+
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+def get_trade_date_after(start_date, n):
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+ start_date = start_date.replace('-', '')
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+ cal = pro.trade_cal(exchange='SSE', start_date=start_date)
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+ cal = cal[cal['is_open'] == 1]
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+ trading_days = cal[cal['cal_date'] >= start_date]
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+ trading_days = trading_days['cal_date'].tolist()[::-1]
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+ return trading_days[n]
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+
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+def extract_code_date(file_path):
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+ df = pd.read_csv(file_path)
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+ code_date_df = df[['code', 'tradedate']].copy()
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+ code_date_df['code'] = code_date_df['code'].astype(str).str.zfill(6)
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+ result_list = code_date_df.values.tolist()
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+ return result_list
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+
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+def get_pct(code, start_date, end_date):
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+ daily_data = pro.daily(ts_code=tscode(code), start_date=tsdate(start_date), end_date=tsdate(end_date))
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+ daily_data.set_index('trade_date', inplace=True)
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+ daily_data.sort_index(inplace=True)
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+ pct = round((daily_data.iloc[-1]['close'] - daily_data.iloc[0]['close']) / daily_data.iloc[0]['close'] * 100, 2)
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+ return pct
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+
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+
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+# 路由定义
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+@app.route('/', methods=['GET', 'POST'])
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+def index():
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+ if request.method == 'POST':
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+ file = request.files['file']
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+ if file:
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+ filename = secure_filename(file.filename)
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+ filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
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+ file.save(filepath)
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+
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+
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+ # 读取CSV文件
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+ code_date_list = extract_code_date(filepath)
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+ pct_list = []
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+ up_down_flags = []
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+
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+ for code, start_date in code_date_list:
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+ end_date = get_trade_date_after(start_date, 10)
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+ pct = get_pct(code, start_date, end_date)
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+ pct_list.append(pct)
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+ up_down_flags.append(1 if pct > 0 else 0)
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+
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+ counter = Counter(up_down_flags)
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+ up_probability = counter[1] / len(up_down_flags) * 100
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+
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+ df = pd.read_csv(filepath)
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+ df['code'] = df['code'].astype(str).str.zfill(6)
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+ df['10_days_pct'] = pct_list
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+
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+ return render_template('index.html',
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+ tables=[df.to_html(classes='table table-striped')],
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+ titles=df.columns.values,
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+ up_probability=up_probability)
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+
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+ return render_template('index.html')
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+
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+if __name__ == '__main__':
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+ app.run(debug=True)
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caijynb
2 年之前