基于机器学习深度学习的股票基金黄金量化交易预测系统-完整代码可直接运行

视频讲解：

系统演示：

系统演示:

部分核心代码：

from flask import Flask, render_template, redirect, url_for, request, flash
from flask_login import LoginManager, login_user, login_required, logout_user, current_user
import database
import models

app = Flask(__name__)
app.secret_key = 'your_secret_key_here'  # 用于会话管理的密钥

# 配置Flask-Login
login_manager = LoginManager()
login_manager.init_app(app)
login_manager.login_view = 'login'


@login_manager.user_loader
def load_user(user_id):
    return database.get_user(int(user_id))


@app.route('/')
def index():
    if current_user.is_authenticated:
        return redirect(url_for('dashboard'))
    return redirect(url_for('login'))


@app.route('/login', methods=['GET', 'POST'])
def login():
    if request.method == 'POST':
        username = request.form['username']
        password = request.form['password']

        user = database.get_user_by_username(username)
        if user and user.check_password(password):
            login_user(user)
            return redirect(url_for('dashboard'))
        else:
            flash('用户名或密码不正确')

    return render_template('login.html')


@app.route('/register', methods=['GET', 'POST'])
def register():
    if request.method == 'POST':
        username = request.form['username']
        password = request.form['password']
        confirm_password = request.form['confirm_password']

        if password != confirm_password:
            flash('两次输入的密码不一致')
            return render_template('register.html')

        # 去掉了邮箱相关代码
        if database.create_user(username, password):
            flash('注册成功，请登录')
            return redirect(url_for('login'))
        else:
            flash('用户名已被使用')

    return render_template('register.html')


@app.route('/logout')
@login_required
def logout():
    logout_user()
    return redirect(url_for('login'))


@app.route('/dashboard', methods=['GET', 'POST'])
@login_required
def dashboard():
    prediction_result = None
    error = None
    model_type = request.form.get('model_type', 'lstm')

    if request.method == 'POST':
        prediction_result, error = models.run_prediction(model_type)

    return render_template(
        'dashboard.html',
        user=current_user,
        prediction_result=prediction_result,
        error=error,
        selected_model=model_type
    )


if __name__ == '__main__':
    # 创建数据目录（如果不存在）
    import os

    if not os.path.exists('data'):
        os.makedirs('data')

    app.run(debug=True)

完整代码数据：

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