基于Python爬虫的淘宝服装数据分析项目
该项目是基于Python爬虫的淘宝服装数据分析项目,以致于帮助商家了解当前服装市场的需求,制定更加精确的营销策略。首先,需要爬取淘宝中关于服装的大量数据,然后对数据进行处理和分析,比如处理重复值,提取关键信息,统计分析等等,最后,通过Echarts将处理后的数据进行可视化展示,可以更为直观的看到服装市场的趋势和变化。代码分析导入模块代码首先从主函数进入,传入三个参数,运行TaobaoCrawler
一.项目介绍
该项目是基于Python爬虫的淘宝服装数据分析项目,以致于帮助商家了解当前服装市场的需求,制定更加精确的营销策略。首先,需要爬取淘宝中关于服装的大量数据,然后对数据进行处理和分析,比如处理重复值,提取关键信息,统计分析等等,最后,通过Echarts将处理后的数据进行可视化展示,可以更为直观的看到服装市场的趋势和变化。
二.爬虫代码
import json
import os
import requests
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from pyquery import PyQuery as pq # 作用:解析网页
import time
import openpyxl as op
class TaobaoCrawler:
# 初始化
def __init__(self, keyword, start_page, end_page):
self.keyword = keyword
self.start_page = start_page
self.end_page = end_page
self.count = 1
self.driver = self.init_driver()
self.wait = WebDriverWait(self.driver, 10)
self.wb, self.ws = self.init_excel()
self.products = []
self.create_images_folder()
# 创建图片文件夹
def create_images_folder(self):
if not os.path.exists('images'):
os.makedirs('images')
# 下载图片
def download_image(self, img_url, img_name):
if img_url:
response = requests.get(img_url)
if response.status_code == 200:
with open(f'images/{img_name}.png', 'wb') as f:
f.write(response.content)
else:
print(f"Image URL is None for {img_name}, skipping download.")
# 初始化浏览器
def init_driver(self):
options = webdriver.ChromeOptions()
options.add_experimental_option("excludeSwitches", ['enable-automation'])
driver = webdriver.Chrome(options=options)
driver.maximize_window()
return driver
# 初始化Excel
def init_excel(self):
wb = op.Workbook()
ws = wb.create_sheet(index=0)
title_list = ['Page', 'Num', 'Title', 'Price', 'Deal', 'Location', 'Shop', 'IsPostFree', 'Title_URL', 'Shop_URL', 'Img_URL']
for i, title in enumerate(title_list):
ws.cell(row=self.count, column=i + 1, value=title)
self.count += 1
return wb, ws
# 搜索商品
def search_goods(self):
try:# 搜索商品
print('正在搜索: ')
self.driver.get('https://www.taobao.com')
self.driver.execute_cdp_cmd("Page.addScriptToEvaluateOnNewDocument",
{"source": """Object.defineProperty(navigator, 'webdriver', {get: () => undefined})"""})
input = self.wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, "#q")))
# 提交搜索
submit = self.wait.until(EC.element_to_be_clickable((By.CSS_SELECTOR, '#J_TSearchForm > div.search-button > button')))
# 输入关键字
input.send_keys(self.keyword)
submit.click()
# 等待页面加载完成
if self.start_page != 1:
time.sleep(3)
page_input = self.wait.until(EC.presence_of_element_located((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/span[3]/input')))
page_input.send_keys(self.start_page)
admit = self.wait.until(EC.element_to_be_clickable((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/button[3]')))
admit.click()
# 获取商品信息
self.get_goods(self.start_page)
for i in range(self.start_page + 1, self.end_page + 1):
self.page_turning(i)
# 捕获异常
except TimeoutException:
print("search_goods: error")
self.search_goods()
# 翻页
def page_turning(self, page_number):
print('正在翻页: ', page_number)
try:
time.sleep(2)
submit = self.wait.until(EC.element_to_be_clickable((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/button[2]')))
submit.click()
self.wait.until(EC.text_to_be_present_in_element((By.XPATH, '//*[@id="sortBarWrap"]/div[1]/div[2]/div[2]/div[8]/div/span/em'), str(page_number)))
self.get_goods(page_number)
except TimeoutException:
print("page_number: error")
self.page_turning(page_number)
# 获取商品信息
def get_goods(self, page):
time.sleep(10)
html = self.driver.page_source
doc = pq(html)
items = doc('div.PageContent--contentWrap--mep7AEm > div.LeftLay--leftWrap--xBQipVc > div.LeftLay--leftContent--AMmPNfB > div.Content--content--sgSCZ12 > div > a').items()
for item in items:
title = item.find('.Title--title--jCOPvpf span').text()
price_int = item.find('.Price--priceInt--ZlsSi_M').text()
price_float = item.find('.Price--priceFloat--h2RR0RK').text()
price = float(f"{price_int}{price_float}") if price_int and price_float else 0.0
deal = item.find('.Price--realSales--FhTZc7U').text()
location = item.find('.Price--procity--_7Vt3mX').text()
shop = item.find('.ShopInfo--TextAndPic--yH0AZfx a').text()
postText = "包邮" if "包邮" in item.find('.SalesPoint--subIconWrapper--s6vanNY span').text() else "/"
t_url = item.attr('href')
shop_url = item.find('.ShopInfo--TextAndPic--yH0AZfx a').attr('href')
img_url = item.find('.MainPic--mainPicWrapper--iv9Yv90 img').attr('src')
product = {
'Page': page,
'Num': self.count - 1,
'title': title,
'price': price,
'deal': deal,
'location': location,
'shop': shop,
'isPostFree': postText,
'url': t_url,
'shop_url': shop_url,
'img_url': img_url
}
print(product)
self.products.append(product)
self.ws.cell(row=self.count, column=1, value=page)
self.ws.cell(row=self.count, column=2, value=self.count - 1)
self.ws.cell(row=self.count, column=3, value=title)
self.ws.cell(row=self.count, column=4, value=price)
self.ws.cell(row=self.count, column=5, value=deal)
self.ws.cell(row=self.count, column=6, value=location)
self.ws.cell(row=self.count, column=7, value=shop)
self.ws.cell(row=self.count, column=8, value=postText)
self.ws.cell(row=self.count, column=9, value=t_url)
self.ws.cell(row=self.count, column=10, value=shop_url)
self.ws.cell(row=self.count, column=11, value=img_url)
self.count += 1
self.download_image(img_url, f'img_{self.count - 1}')
# 保存数据
def save_excel(self, filename):
self.wb.save(filename=filename)
print(f"{filename} 存储成功~")
# 保存json
def save_json(self, filename):
with open(filename, 'w', encoding='utf-8') as f:
json.dump(self.products, f, ensure_ascii=False, indent=4)
print(f"{filename} 存储成功~")
# 运行
def run(self):
self.search_goods()
excel_filename = 'data/服装(From-Tao).xlsx'
self.save_excel(excel_filename)
json_filename = 'data/content.json'
self.save_json(json_filename)
self.driver.quit()
# 主函数
if __name__ == '__main__':
crawler = TaobaoCrawler(keyword='服装', start_page=1, end_page=45)
crawler.run()
代码分析
import json
import os
import requests
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from pyquery import PyQuery as pq # 作用:解析网页
import time
import openpyxl as op
导入模块
模块 | 作用 |
---|---|
json | 用于处理 JSON 数据。 |
os | 用于操作系统相关功能,如文件路径操作。 |
requests | 用于发送 HTTP 请求。 |
selenium 相关模块 | 用于自动化浏览器操作。 |
pyquery | 用于解析 HTML 文档。 |
time | 用于时间相关操作。 |
openpyxl | 用于操作 Excel 文件` |
# 主函数
if __name__ == '__main__':
crawler = TaobaoCrawler(keyword='服装', start_page=1, end_page=45)
crawler.run()
代码首先从主函数进入,传入三个参数,运行TaobaoCrawler爬虫类
# 初始化
def __init__(self, keyword, start_page, end_page):
self.keyword = keyword
self.start_page = start_page
self.end_page = end_page
self.count = 1
self.driver = self.init_driver()
self.wait = WebDriverWait(self.driver, 10)
self.wb, self.ws = self.init_excel()
self.products = []
self.create_images_folder()
# 创建图片文件夹
def create_images_folder(self):
if not os.path.exists('images'):
os.makedirs('images')
# 下载图片
def download_image(self, img_url, img_name):
if img_url:
response = requests.get(img_url)
if response.status_code == 200:
with open(f'images/{img_name}.png', 'wb') as f:
f.write(response.content)
else:
print(f"Image URL is None for {img_name}, skipping download.")
# 初始化浏览器
def init_driver(self):
options = webdriver.ChromeOptions()
options.add_experimental_option("excludeSwitches", ['enable-automation'])
driver = webdriver.Chrome(options=options)
driver.maximize_window()
return driver
# 初始化Excel
def init_excel(self):
wb = op.Workbook()
ws = wb.create_sheet(index=0)
title_list = ['Page', 'Num', 'Title', 'Price', 'Deal', 'Location', 'Shop', 'IsPostFree', 'Title_URL', 'Shop_URL', 'Img_URL']
for i, title in enumerate(title_list):
ws.cell(row=self.count, column=i + 1, value=title)
self.count += 1
return wb, ws
初始化方法 _init:
- 初始化爬虫的关键字、起始页和结束页。
- 初始化浏览器驱动、等待对象、Excel 文件和工作表。
- 创建存储图片的文件夹。
方法 create_images_folder: 检查并创建存储图片的文件夹。
方法 download_image: 下载并保存图片到本地。
方法 init_driver: 初始化并配置 Chrome 浏览器驱动。
方法 init_excel: 初始化 Excel 文件和工作表,并设置表头。
# 搜索商品
def search_goods(self):
try:# 搜索商品
print('正在搜索: ')
self.driver.get('https://www.taobao.com')
self.driver.execute_cdp_cmd("Page.addScriptToEvaluateOnNewDocument",
{"source": """Object.defineProperty(navigator, 'webdriver', {get: () => undefined})"""})
input = self.wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, "#q")))
# 提交搜索
submit = self.wait.until(EC.element_to_be_clickable((By.CSS_SELECTOR, '#J_TSearchForm > div.search-button > button')))
# 输入关键字
input.send_keys(self.keyword)
submit.click()
# 等待页面加载完成
if self.start_page != 1:
time.sleep(3)
page_input = self.wait.until(EC.presence_of_element_located((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/span[3]/input')))
page_input.send_keys(self.start_page)
admit = self.wait.until(EC.element_to_be_clickable((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/button[3]')))
admit.click()
# 获取商品信息
self.get_goods(self.start_page)
for i in range(self.start_page + 1, self.end_page + 1):
self.page_turning(i)
# 捕获异常
except TimeoutException:
print("search_goods: error")
self.search_goods()
方法 search_goods:
- 打开淘宝主页,输入关键字并搜索商品。
- 如果起始页不是第一页,跳转到指定页码。
- 获取商品信息。
# 翻页
def page_turning(self, page_number):
print('正在翻页: ', page_number)
try:
time.sleep(2)
submit = self.wait.until(EC.element_to_be_clickable((By.XPATH, '//*[@id="pageContent"]/div[1]/div[3]/div[4]/div/div/button[2]')))
submit.click()
self.wait.until(EC.text_to_be_present_in_element((By.XPATH, '//*[@id="sortBarWrap"]/div[1]/div[2]/div[2]/div[8]/div/span/em'), str(page_number)))
self.get_goods(page_number)
except TimeoutException:
print("page_number: error")
self.page_turning(page_number)
方法 page_turning: 翻页并获取商品信息
# 获取商品信息
def get_goods(self, page):
time.sleep(10)
html = self.driver.page_source
doc = pq(html)
items = doc('div.PageContent--contentWrap--mep7AEm > div.LeftLay--leftWrap--xBQipVc > div.LeftLay--leftContent--AMmPNfB > div.Content--content--sgSCZ12 > div > a').items()
for item in items:
title = item.find('.Title--title--jCOPvpf span').text()
price_int = item.find('.Price--priceInt--ZlsSi_M').text()
price_float = item.find('.Price--priceFloat--h2RR0RK').text()
price = float(f"{price_int}{price_float}") if price_int and price_float else 0.0
deal = item.find('.Price--realSales--FhTZc7U').text()
location = item.find('.Price--procity--_7Vt3mX').text()
shop = item.find('.ShopInfo--TextAndPic--yH0AZfx a').text()
postText = "包邮" if "包邮" in item.find('.SalesPoint--subIconWrapper--s6vanNY span').text() else "/"
t_url = item.attr('href')
shop_url = item.find('.ShopInfo--TextAndPic--yH0AZfx a').attr('href')
img_url = item.find('.MainPic--mainPicWrapper--iv9Yv90 img').attr('src')
product = {
'Page': page,
'Num': self.count - 1,
'title': title,
'price': price,
'deal': deal,
'location': location,
'shop': shop,
'isPostFree': postText,
'url': t_url,
'shop_url': shop_url,
'img_url': img_url
}
print(product)
self.products.append(product)
self.ws.cell(row=self.count, column=1, value=page)
self.ws.cell(row=self.count, column=2, value=self.count - 1)
self.ws.cell(row=self.count, column=3, value=title)
self.ws.cell(row=self.count, column=4, value=price)
self.ws.cell(row=self.count, column=5, value=deal)
self.ws.cell(row=self.count, column=6, value=location)
self.ws.cell(row=self.count, column=7, value=shop)
self.ws.cell(row=self.count, column=8, value=postText)
self.ws.cell(row=self.count, column=9, value=t_url)
self.ws.cell(row=self.count, column=10, value=shop_url)
self.ws.cell(row=self.count, column=11, value=img_url)
self.count += 1
self.download_image(img_url, f'img_{self.count - 1}')
方法 get_goods: 解析当前页面的商品信息并保存到 Excel 和 JSON 文件中。
# 保存数据
def save_excel(self, filename):
self.wb.save(filename=filename)
print(f"{filename} 存储成功~")
# 保存json
def save_json(self, filename):
with open(filename, 'w', encoding='utf-8') as f:
json.dump(self.products, f, ensure_ascii=False, indent=4)
print(f"{filename} 存储成功~")
# 运行
def run(self):
self.search_goods()
excel_filename = 'data/服装(From-Tao).xlsx'
self.save_excel(excel_filename)
json_filename = 'data/content.json'
self.save_json(json_filename)
self.driver.quit()
方法 save_excel: 保存 Excel 文件。
方法 save_json: 保存 JSON 文件。
方法 run: 执行爬虫任务,保存数据并关闭浏览器。
三. 数据处理
const fs = require('fs').promises;
const path = require('path');
let data = null;
let d = null;
// 定义一个异步函数来加载数据
async function loadData() {
try {
const filePath = path.join(__dirname, '../data', 'content.json');
const fileContent = await fs.readFile(filePath, 'utf8');
data = JSON.parse(fileContent);
console.log('Data loaded successfully:', data);
} catch (error) {
console.error('Failed to load data:', error);
}
}
// 在程序启动时调用loadData函数
loadData().then(() => {
// if (data) {
// console.log('Global data:', data[0].title);
// }
console.log("data.length", data.length)
const dict = data.reduce((acc, item) => {
acc[item.title] = item
return acc
}, {})
// console.log("dict", dict)
const dict_arr = []
for (const title in dict) {
dict_arr.push(dict[title])
}
// console.log("arr", arr)
console.log("dict_arr.length", dict_arr.length)
d = dict_arr.reduce((acc, item) => {
let flag = false
for (const v of acc) {
if (v.name === item.location) {
v.value += 1
flag = true
}
}
if (flag === false) {
acc.push({
name: item.location,
value: 1
})
}
return acc
}, [])
// 按value值降序排序
d.sort((a, b) => b.value - a.value);
console.log("data_handle\n", d)
}).catch(error => {
// 处理加载数据时的错误
console.error('Failed to load data during startup:', error);
});
- 导入模块:
fs:用于文件系统操作,使用 promises 以便使用异步函数。
path:用于处理和转换文件路径。 - 变量声明:
data:用于存储从 JSON 文件加载的数据。
d:用于存储处理后的数据。 - 函数 loadData:
- 异步函数,用于加载 JSON 文件中的数据。
- 使用 fs.readFile 读取文件内容,并将其解析为 JSON 对象。
- 如果读取成功,数据将存储在 data 变量中,并在控制台输出成功消息。
- 如果读取失败,捕获错误并在控制台输出错误消息。
- 数据处理:
- 在程序启动时调用 loadData 函数,并在数据加载完成后进行处理。
- 使用 reduce 方法将数据转换为字典 dict,其中键为商品标题,值为商品对象。
- 将字典转换为数组 dict_arr,以便进一步处理。
- 使用 reduce 方法将 dict_arr 转换为按 location 分组的数组 d,并统计每个 location 的商品数量。
- 按 value 值对 d 进行降序排序。
- 在控制台输出处理后的数据。
四. 数据可视化
<!DOCTYPE html>
<html lang="en" style="height: 100%">
<head>
<meta charset="utf-8">
<title>Region Distribution Map</title>
<style>
body, html {
height: 100%;
margin: 0;
font-family: Arial, sans-serif;
background-color: #f4f4f4;
}
#container {
height: 100%;
width: 100%;
max-width: 1200px;
margin: 0 auto;
padding: 20px;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
background-color: #fff;
border-radius: 8px;
}
</style>
</head>
<body>
<div id="container"></div>
<script src="./js/echarts.min.js"></script>
<script src="./js/china.js"></script>
<script>
document.addEventListener('DOMContentLoaded', () => {
const dom = document.getElementById('container');
const myChart = echarts.init(dom, null, {
renderer: 'canvas',
useDirtyRect: false
});
const data = [
{name: '福建', value: 716},
{name: '浙江', value: 557},
{name: '广东', value: 340},
{name: '湖北', value: 206},
{name: '江苏', value: 67},
{name: '上海', value: 12},
{name: '安徽', value: 10},
{name: '北京', value: 7},
{name: '山东', value: 4},
{name: '江西', value: 3},
{name: '湖南', value: 3},
{name: '广西', value: 3},
{name: '河南', value: 3},
{name: '河北', value: 1},
{name: '四川', value: 1},
{name: '新疆', value: 1},
{name: '辽宁', value: 1}
];
const option = {
title: {
text: '中国服装发出地',
left: 'center',
textStyle: {
color: '#333',
fontSize: 24
}
},
tooltip: {
trigger: 'item',
formatter: '{b}: {c}'
},
visualMap: {
min: 0,
max: 700,
left: 'left',
top: 'bottom',
text: ['High', 'Low'],
calculable: true,
inRange: {
color: ['#e0ffff', '#006edd']
}
},
series: [
{
name: '服装发出地',
type: 'map',
map: 'china',
roam: true,
label: {
show: true
},
data: data
}
]
};
myChart.setOption(option);
window.addEventListener('resize', myChart.resize);
});
</script>
</body>
</html>
效果展示:
中间需要俩个js文件:
- china.js
(function (root, factory) {
if (typeof define === 'function' && define.amd) {
// AMD. Register as an anonymous module.
define(['exports', 'echarts'], factory);
} else if (typeof exports === 'object' && typeof exports.nodeName !== 'string') {
// CommonJS
factory(exports, require('echarts'));
} else {
// Browser globals
factory({}, root.echarts);
}
}(this, function (exports, echarts) {
var log = function (msg) {
if (typeof console !== 'undefined') {
console && console.error && console.error(msg);
}
}
if (!echarts) {
log('ECharts is not Loaded');
return;
}
if (!echarts.registerMap) {
log('ECharts Map is not loaded')
return;
}
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- echarts.min.js
(function (root, factory) {
if (typeof define === 'function' && define.amd) {
// AMD. Register as an anonymous module.
define(['exports', 'echarts'], factory);
} else if (typeof exports === 'object' && typeof exports.nodeName !== 'string') {
// CommonJS
factory(exports, require('echarts'));
} else {
// Browser globals
factory({}, root.echarts);
}
}(this, function (exports, echarts) {
var log = function (msg) {
if (typeof console !== 'undefined') {
console && console.error && console.error(msg);
}
}
if (!echarts) {
log('ECharts is not Loaded');
return;
}
if (!echarts.registerMap) {
log('ECharts Map is not loaded')
return;
}
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}));
<!DOCTYPE html>
<html lang="en" style="height: 100%">
<head>
<meta charset="utf-8">
<title>Clothing Category Distribution</title>
<style>
body {
font-family: Arial, sans-serif;
margin: 0;
padding: 0;
display: flex;
justify-content: center;
align-items: center;
height: 100%;
background-color: #f4f4f4;
}
#container {
width: 80%;
height: 80%;
}
</style>
</head>
<body>
<div id="container"></div>
<script type="text/javascript" src="https://registry.npmmirror.com/echarts/5.5.1/files/dist/echarts.min.js"></script>
<script type="text/javascript">
var dom = document.getElementById('container');
var myChart = echarts.init(dom, null, {
renderer: 'canvas',
useDirtyRect: false
});
var app = {};
var data = [
{ name: '外套', value: 377 },
{ name: '衬衫', value: 170 },
{ name: '长袖', value: 200 },
{ name: '卫衣', value: 57 },
{ name: 'T恤', value: 108 },
{ name: '内衣', value: 8 },
{ name: '裤子', value: 734 },
{ name: '裙子', value: 150 },
{ name: '运动装', value: 805 }
];
// Sort data in descending order
data.sort((a, b) => b.value - a.value);
var option = {
title: {
text: 'Clothing Category Distribution',
subtext: 'Based on the number of items',
left: 'center',
textStyle: {
color: '#333',
fontSize: 24
},
subtextStyle: {
color: '#666',
fontSize: 14
}
},
tooltip: {
trigger: 'axis',
axisPointer: {
type: 'shadow'
},
formatter: '{b}: {c} items'
},
grid: {
left: '3%',
right: '4%',
bottom: '3%',
containLabel: true
},
xAxis: {
type: 'category',
data: data.map(item => item.name),
axisTick: {
alignWithLabel: true
},
axisLabel: {
interval: 0,
rotate: 30,
textStyle: {
fontSize: 12
}
}
},
yAxis: {
type: 'value',
axisLabel: {
textStyle: {
fontSize: 12
}
},
splitLine: {
show: true,
lineStyle: {
color: '#ddd'
}
}
},
series: [
{
name: '数量',
type: 'bar',
barWidth: '60%',
data: data.map(item => item.value),
itemStyle: {
color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [
{ offset: 0, color: '#83bff6' },
{ offset: 0.5, color: '#188df0' },
{ offset: 1, color: '#188df0' }
])
},
showBackground: true,
backgroundStyle: {
color: 'rgba(180, 180, 180, 0.2)'
},
label: {
show: true,
position: 'top',
formatter: '{c}'
}
}
]
};
if (option && typeof option === 'object') {
myChart.setOption(option);
}
window.addEventListener('resize', myChart.resize);
</script>
</body>
</html>
效果展示:
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