持仓图一键生成器，股票账户模拟生成器，交割单制作生成

下载地址：https://www.pan38.com/share.php?code=JCnzE 提取密码：7789

这个完整的股票账户模拟系统包含四个主要模块：主模拟器、持仓可视化、交割单生成和主程序入口。系统可以模拟随机交易、生成持仓图表、创建交割单和投资组合报告。您可以根据需要调整参数或扩展功能。

import random
import matplotlib.pyplot as plt
import pandas as pd
from datetime import datetime, timedelta
import numpy as np
from faker import Faker

class StockAccountSimulator:
def init(self, initial_balance=100000):
self.balance = initial_balance
self.portfolio = {}
self.transaction_history = []
self.fake = Faker()
self.stock_pool = [
"AAPL", "MSFT", "GOOGL", "AMZN", "TSLA",
"FB", "NVDA", "PYPL", "ADBE", "INTC"
]
self.current_prices = {stock: round(random.uniform(50, 500), 2) for stock in self.stock_pool}

def generate_random_trade(self, days=30):
    start_date = datetime.now() - timedelta(days=days)
    for i in range(days*3):  # 3 trades per day on average
        trade_date = start_date + timedelta(days=i//3, hours=random.randint(9, 15), minutes=random.randint(0, 59))
        stock = random.choice(self.stock_pool)
        action = random.choice(["BUY", "SELL"])
        quantity = random.randint(1, 100)
        price = self.current_prices[stock] * random.uniform(0.95, 1.05)
        amount = round(quantity * price, 2)

        if action == "BUY" and self.balance >= amount:
            self.execute_trade(trade_date, stock, action, quantity, price)
        elif action == "SELL" and stock in self.portfolio and self.portfolio[stock] >= quantity:
            self.execute_trade(trade_date, stock, action, quantity, price)

        # Update price randomly
        self.current_prices[stock] *= random.uniform(0.98, 1.02)
        self.current_prices[stock] = round(self.current_prices[stock], 2)

PortfolioVisualizer:
@staticmethod
def generate_holdings_chart(portfolio, prices):
if not portfolio:
print("Portfolio is empty")
return

    stocks = list(portfolio.keys())
    quantities = [portfolio[stock] for stock in stocks]
    values = [portfolio[stock] * prices[stock] for stock in stocks]

    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 6))

    # Pie chart by value
    ax1.pie(values, labels=stocks, autopct='%1.1f%%')
    ax1.set_title('Portfolio Allocation by Value')

    # Bar chart by quantity
    ax2.bar(stocks, quantities)
    ax2.set_title('Holdings by Quantity')
    ax2.set_ylabel('Shares')

    plt.tight_layout()
    plt.savefig('portfolio_holdings.png')
    plt.close()
    return 'portfolio_holdings.png'

@staticmethod
def generate_performance_chart(history):
    if not history:
        print("No transaction history")
        return

    df = pd.DataFrame(history)
    df['date'] = pd.to_datetime(df['date'])
    df['cumulative'] = df['amount'].cumsum()

    plt.figure(figsize=(12, 6))
    plt.plot(df['date'], df['cumulative'])
    plt.title('Account Performance Over Time')
    plt.xlabel('Date')
    plt.ylabel('Cumulative Value ($)')
    plt.grid(True)
    plt.savefig('performance_chart.png')
    plt.close()
    return 'performance_chart.png'