股票假图一键生成器， 股票持仓图生成器免费， 股票虚拟仿真交易软件

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股票模拟系统开发指南

一、系统架构设计

本系统包含三大核心模块：假图生成器、持仓可视化工具和虚拟交易引擎。采用Python+Flask+Vue技术栈实现前后端分离架构。

二、核心代码实现

1. 股票数据模拟引擎

import random
import time
from threading import Thread
from flask import Flask, jsonify

app = Flask(name)

class StockSimulator:
def init(self):
self.stocks = {
'600519': {'name': '贵州茅台', 'price': 1800.0},
'000858': {'name': '五粮液', 'price': 150.0},
'601318': {'name': '中国平安', 'price': 45.0}
}
self.volatility = 0.02 # 波动率

def generate_market_data(self):
    while True:
        for code in self.stocks:
            change = random.uniform(-self.volatility, self.volatility)
            self.stocks[code]['price'] *= (1 + change)
            self.stocks[code]['price'] = round(self.stocks[code]['price'], 2)
        time.sleep(3)

@app.route('/api/stocks')
def get_stocks():
return jsonify(simulator.stocks)

if name == 'main':
simulator = StockSimulator()
Thread(target=simulator.generate_market_data).start()
app.run(port=5000)

1. 持仓图生成器(前端Vue实现)

1. 虚拟交易API(Python实现)

from flask import request, jsonify
from datetime import datetime

class VirtualExchange:
def init(self):
self.accounts = {}
self.order_id = 100000

def create_account(self, user_id, capital=1000000):
    self.accounts[user_id] = {
        'cash': capital,
        'positions': {},
        'orders': []
    }

def place_order(self, user_id, code, direction, price, amount):
    if user_id not in self.accounts:
        return {'error': '账户不存在'}

    account = self.accounts[user_id]
    stock = simulator.stocks.get(code)
    if not stock:
        return {'error': '股票不存在'}

    total_value = price * amount
    if direction == 'buy' and account['cash'] < total_value:
        return {'error': '资金不足'}

    order = {
        'order_id': self.order_id,
        'code': code,
        'name': stock['name'],
        'direction': direction,
        'price': price,
        'amount': amount,
        'status': 'filled',
        'time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    }
    self.order_id += 1

    if direction == 'buy':
        account['cash'] -= total_value
        if code in account['positions']:
            account['positions'][code]['amount'] += amount
            account['positions'][code]['cost'] += total_value
        else:
            account['positions'][code] = {
                'amount': amount,
                'cost': total_value,
                'current_price': price
            }
    else:  # sell
        if code not in account['positions']:
            return {'error': '持仓不足'}
        if account['positions'][code]['amount'] < amount:
            return {'error': '持仓数量不足'}

        account['cash'] += total_value
        account['positions'][code]['amount'] -= amount
        account['positions'][code]['cost'] -= amount * account['positions'][code]['cost'] / account['positions'][code]['amount']

    account['orders'].append(order)
    return {'success': True, 'order': order}

@app.route('/api/trade', methods=['POST'])
def trade():
data = request.json
return jsonify(exchange.place_order(
data['user_id'],
data['code'],
data['direction'],
float(data['price']),
int(data['amount'])
))

exchange = VirtualExchange()

三、系统扩展功能

1. 历史回测引擎

import pandas as pd
import numpy as np

class BacktestEngine:
def init(self, data_path):
self.history_data = pd.read_csv(data_path)
self.history_data['date'] = pd.to_datetime(self.history_data['date'])

def run_strategy(self, strategy_func, initial_capital=100000):
    capital = initial_capital
    positions = {}
    trades = []

    for idx, row in self.history_data.iterrows():
        signal = strategy_func(row)

        if signal['action'] == 'buy':
            cost = signal['price'] * signal['amount']
            if cost > capital:
                continue

            capital -= cost
            if signal['code'] in positions:
                positions[signal['code']]['amount'] += signal['amount']
                positions[signal['code']]['cost'] += cost
            else:
                positions[signal['code']] = {
                    'amount': signal['amount'],
                    'cost': cost,
                    'entry_price': signal['price']
                }

            trades.append({
                'date': row['date'],
                'code': signal['code'],
                'action': 'buy',
                'price': signal['price'],
                'amount': signal['amount']
            })

        elif signal['action'] == 'sell' and signal['code'] in positions:
            position = positions[signal['code']]
            if position['amount'] < signal['amount']:
                continue

            profit = signal['amount'] * (signal['price'] - position['cost']/position['amount'])
            capital += signal['price'] * signal['amount']
            position['amount'] -= signal['amount']
            position['cost'] -= signal['amount'] * position['cost']/position['amount']

            if position['amount'] == 0:
                del positions[signal['code']]

            trades.append({
                'date': row['date'],
                'code': signal['code'],
                'action': 'sell',
                'price': signal['price'],
                'amount': signal['amount'],
                'profit': profit
            })

    return {
        'final_capital': capital,
        'return_rate': (capital - initial_capital) / initial_capital,
        'trades': pd.DataFrame(trades),
        'positions': positions
    }

1. 假图生成增强功能

from PIL import Image, ImageDraw, ImageFont
import random

def generate_fake_screenshot():

# 创建空白图片
img = Image.new('RGB', (800, 1400), (255, 255, 255))
draw = ImageDraw.Draw(img)

# 添加状态栏
draw.rectangle([0, 0, 800, 80], fill=(30, 30, 30))
draw.text((40, 30), "9:41", fill=(255,255,255), font=ImageFont.load_default(30))

# 添加账户信息
draw.rectangle([20, 100, 780, 200], fill=(240,240,240))
draw.text((40, 120), "总资产: ¥1,256,789.23", fill=(0,0,0), font=ImageFont.load_default(28))
draw.text((40, 160), "当日盈亏: +¥25,678.90 (+2.05%)", fill=(255,0,0), font=ImageFont.load_default(28))

# 生成随机持仓
stocks = [
    ('600519', '贵州茅台', 1850.0, 100, 1800.0, 2.78),
    ('000858', '五粮液', 145.0, 500, 150.0, -3.33),
    ('601318', '中国平安', 45.5, 1000, 42.0, 8.33)
]

y_pos = 240
for code, name, price, amount, cost, profit in stocks:
    draw.rectangle([20, y_pos, 780, y_pos+120], fill=(250,250,250))
    draw.text((40, y_pos+20), f"{name} {code}", fill=(0,0,0), font=ImageFont.load_default(26))
    draw.text((40, y_pos+60), f"持仓: {amount}股  成本: ¥{cost:.2f}", fill=(100,100,100), font=ImageFont.load_default(24))

    color = (255,0,0) if profit > 0 else (0,200,0)
    draw.text((500, y_pos+20), f"¥{price:.2f}", fill=color, font=ImageFont.load_default(30))
    draw.text((500, y_pos+60), f"{'+' if profit > 0 else ''}{profit:.2f}%", fill=color, font=ImageFont.load_default(28))

    y_pos += 140

# 保存图片
img.save('fake_holdings.png')
return img

四、部署方案

1. Docker部署配置

FROM python:3.9-slim

WORKDIR /app
COPY . .

RUN pip install -r requirements.txt

EXPOSE 5000
CMD ["gunicorn", "-b :5000", "app:app"]

1. 系统依赖文件

requirements.txt

flask==2.3.2
gunicorn==20.1.0
pandas==2.0.3
pillow==10.0.0
numpy==1.24.3

五、安全与合规建议

所有模拟数据需标注"仿真测试"水印

禁止将生成图片用于虚假宣传

建议增加数据验证机制防止注入攻击

虚拟交易系统应明确免责声明