# 創(chuàng)建虛擬環(huán)境（推薦）
python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

# 安裝必要庫
pip install requests beautifulsoup4 flask pyecharts websockets

客戶端瀏覽器 → WebSocket/AJAX → Flask后端 → Python爬蟲 → 目標網(wǎng)站
                ↑               ↓
           數(shù)據(jù)更新請求       原始數(shù)據(jù)返回

import requests
from bs4 import BeautifulSoup
import time
import random

def fetch_product_data(url):
    headers = {
        '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',
        'Referer': 'https://www.example.com/'
    }
    
    try:
        # 隨機延遲避免被封
        time.sleep(random.uniform(1, 3))
        
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        
        soup = BeautifulSoup(response.text, 'html.parser')
        
        # 假設(shè)價格在class="price"的span標簽中
        price = soup.select_one('span.price').get_text(strip=True)
        
        # 假設(shè)銷量在class="sales"的div標簽中
        sales = soup.select_one('div.sales').get_text(strip=True)
        
        return {
            'price': float(price.replace('￥', '')),
            'sales': int(sales.replace('件', '')),
            'timestamp': int(time.time() * 1000)  # ECharts需要毫秒時間戳
        }
    except Exception as e:
        print(f"Error fetching {url}: {e}")
        return None

# 簡單代理示例（實際建議使用付費代理服務）
proxies = [
    {'http': 'http://123.123.123.123:8080'},
    {'http': 'http://124.124.124.124:8080'}
]

def fetch_with_proxy(url):
    proxy = random.choice(proxies)
    try:
        return requests.get(url, proxies=proxy, timeout=10)
    except:
        return fetch_with_proxy(url)  # 失敗重試

from pyecharts.charts import Line
from pyecharts import options as opts

def create_price_chart(data_list):
    line = (
        Line()
        .add_xaxis([item['timestamp'] for item in data_list])
        .add_yaxis("價格", [item['price'] for item in data_list])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="商品價格實時監(jiān)控"),
            tooltip_opts=opts.TooltipOpts(trigger="axis"),
            xaxis_opts=opts.AxisOpts(type_="time"),  # 時間軸
            yaxis_opts=opts.AxisOpts(name="價格(元)"),
        )
    )
    return line

// 每5秒更新一次數(shù)據(jù)
setInterval(function() {
    fetch('/api/price')
        .then(response => response.json())
        .then(data => {
            // 更新ECharts實例
            myChart.setOption({
                xAxis: { data: data.timestamps },
                series: [{ data: data.prices }]
            });
        });
}, 5000);

from pyecharts.charts import Page

def create_dashboard(price_data, sales_data):
    page = Page(layout=Page.DraggablePageLayout)  # 可拖拽布局
    
    # 價格折線圖
    price_chart = create_price_chart(price_data)
    page.add(price_chart)
    
    # 銷量柱狀圖
    sales_chart = (
        Bar()
        .add_xaxis([item['timestamp'] for item in sales_data])
        .add_yaxis("銷量", [item['sales'] for item in sales_data])
        .set_global_opts(title_opts=opts.TitleOpts(title="商品銷量趨勢"))
    )
    page.add(sales_chart)
    
    return page.render_embed()  # 返回HTML片段

from flask import Flask, jsonify
import threading
import time

app = Flask(__name__)

# 模擬數(shù)據(jù)存儲
price_history = []
sales_history = []

# 模擬爬蟲持續(xù)運行
def background_crawler():
    while True:
        # 這里替換為實際爬蟲調(diào)用
        new_data = fetch_product_data("https://example.com/product/123")
        if new_data:
            price_history.append(new_data)
            sales_history.append(new_data)  # 實際中銷量可能不同源
            
            # 保持最近100條數(shù)據(jù)
            if len(price_history) > 100:
                price_history.pop(0)
                sales_history.pop(0)
        time.sleep(5)  # 每5秒爬取一次

# 啟動后臺爬蟲線程
crawler_thread = threading.Thread(target=background_crawler)
crawler_thread.daemon = True
crawler_thread.start()

@app.route('/api/price')
def get_price_data():
    # 返回最近20個數(shù)據(jù)點
    recent_data = price_history[-20:] if len(price_history) >= 20 else price_history
    return jsonify({
        'timestamps': [item['timestamp'] for item in recent_data],
        'prices': [item['price'] for item in recent_data]
    })

@app.route('/')
def dashboard():
    # 這里應該調(diào)用create_dashboard()生成實際圖表
    # 為簡化示例，直接返回靜態(tài)HTML
    return """
    <!DOCTYPE html>
    <html>
    <head>
        <meta charset="utf-8">
        <title>實時數(shù)據(jù)大屏</title>
        <script src="https://cdn.jsdelivr.net/npm/echarts@5.3.2/dist/echarts.min.js"></script>
    </head>
    <body>
        <div id="price-chart" style="width: 800px;height:400px;"></div>
        <script>
            var chart = echarts.init(document.getElementById('price-chart'));
            var option = {
                title: { text: '商品價格監(jiān)控' },
                tooltip: {},
                xAxis: { type: 'time' },
                yAxis: {},
                series: [{ name: '價格', type: 'line', data: [] }]
            };
            chart.setOption(option);
            
            // 模擬數(shù)據(jù)更新（實際應調(diào)用API）
            setInterval(function() {
                // 這里應該是fetch('/api/price')的調(diào)用
                // 為演示使用模擬數(shù)據(jù)
                var now = new Date();
                var newData = {
                    timestamp: now.getTime(),
                    price: 100 + Math.random() * 10
                };
                
                // 實際項目中需要處理歷史數(shù)據(jù)
                chart.setOption({
                    series: [{
                        data: [newData].concat(chart.getOption().series[0].data.slice(0, 19))
                    }]
                });
            }, 5000);
        </script>
    </body>
    </html>
    """

if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0', port=5000)

from selenium import webdriver
from selenium.webdriver.chrome.options import Options

options = Options()
options.add_argument('--headless')  # 無頭模式
options.add_argument('--disable-gpu')
driver = webdriver.Chrome(options=options)

driver.get("https://example.com")
price = driver.find_element_by_css_selector("span.price").text
driver.quit()

window.addEventListener('resize', function() {
    myChart.resize();
});