目录：
一、基本介绍
二、元素交互操作——点击、清除
三、Actions Chains
四、执行js代码
五、实例：爬取京东商品信息
一、基本介绍：
1.元素交互操作:
- 点击、清除
click
clear
- ActionChains
是一个动作链对象，需要把driver驱动传给它。
动作链对象可以操作一系列设定好的动作行为。
- iframe的切换
driver.switch_to.frame('iframeResult')
- 执行js代码
execute_script()
二、元素交互操作——点击、清除
from selenium import webdriver # 用来驱动浏览器的 from selenium.webdriver import ActionChains # 破解滑动验证码的时候用的 可以拖动图片 from selenium.webdriver.common.keys import Keys # 键盘按键操作 import time driver = webdriver.Chrome() try: driver.implicitly_wait(10) driver.get('https://www.jd.com/') #点击、清除 input = driver.find_element_by_id('key') input.send_keys('围城') #通过class查找搜索按钮 search = driver.find_element_by_class_name('button') search.click() #点击搜索按钮 time.sleep(3) input2 = driver.find_element_by_id('key') input2.clear()# 清空输入框 time.sleep(1) input2.send_keys('墨菲定律') input2.send_keys(Keys.ENTER) time.sleep(10) finally: driver.close()
三、Actions Chains
from selenium import webdriver # 用来驱动浏览器的 from selenium.webdriver import ActionChains # 破解滑动验证码的时候用的 可以拖动图片 from selenium.webdriver.common.keys import Keys # 键盘按键操作 import time driver = webdriver.Chrome() try: driver.implicitly_wait(10) driver.get('http://www.runoob.com/try/try.php?filename=jqueryui-api-droppable') time.sleep(5) # driver.switch_to_frame() 旧方法 driver.switch_to.frame('iframeResult') time.sleep(1) # 获取动作链对象 action = ActionChains(driver) # 起初方块id：draggable source = driver.find_element_by_id('draggable') # 目标方块id：droppable target = driver.find_element_by_id('droppable') # # 方式一：秒移 # #起始方块瞬间移动到目标方块中 # #拟定好一个动作，需要调用执行方法perform # action.drag_and_drop(source,target).perform() # 方式二：一点点移 # print(source.size) # 大小 # print(source.tag_name) # 标签名 # print(source.text) # 文本 # print(source.location) # 坐标：x轴与y轴 # 找到滑动距离 distance = target.location['x'] - source.location['x'] # 摁住起始滑块 ActionChains(driver).click_and_hold(source).perform() s=0 while s < distance: # 获取动作链对象 # 每一次位移s距离 ActionChains(driver).move_by_offset(xoffset=2,yoffset=0).perform() s+= 2 time.sleep(0.1) # 松开起始滑块 ActionChains(driver).release().perform() time.sleep(10) finally: driver.close()
四、执行js代码
from selenium import webdriver # 用来驱动浏览器的 import time driver = webdriver.Chrome() try: driver.implicitly_wait(10) driver.get('https://www.baidu.com') driver.execute_script('alert("hello world")') # 打印警告 time.sleep(5) finally: driver.close()
#模拟浏览器的前进后退 from selenium import webdriver import time browser=webdriver.Chrome() browser.get('https://www.baidu.com') browser.get('https://www.taobao.com') browser.get('http://www.sina.com.cn/') # 回退 browser.back() time.sleep(5) # 前进 browser.forward() time.sleep(3) browser.close()
五、实例：爬取京东商品信息
from selenium import webdriver from selenium.webdriver.common.keys import Keys # 键盘按键操作 import time driver = webdriver.Chrome() def get_good(driver): num = 1 try: time.sleep(5) # 下拉滑动5000px js_code = ''' window.scroll(0,5000) ''' driver.execute_script(js_code) # 等待5秒，待商品数据加载 time.sleep(5) good_list = driver.find_elements_by_class_name('gl-item') for good in good_list: #print(good) # 商品名称 good_name = good.find_element_by_css_selector('.p-name em').text #print(good_name) # 商品链接 good_url = good.find_element_by_css_selector('.p-name a').get_attribute('href') #print(good_url) # 商品价格 good_price = good.find_element_by_class_name('p-price').text #print(good_price) # 商品评价 good_commit = good.find_element_by_class_name('p-commit').text good_content = f''' 商品名称：{good_name} 商品链接：{good_url} 商品价格：{good_price} 商品评价：{good_commit} \n ''' print(good_content) with open('jd.txt','a',encoding='utf-8') as f: f.write(good_content) print('商品信息写入成功!') # 找到下一页并点击 next_tag = driver.find_element_by_class_name('pn-next') next_tag.click() time.sleep(5) # 递归调用函数本身 finally: driver.close() if __name__ == '__main__': driver = webdriver.Chrome() try: driver.implicitly_wait(10) # 往京东发送请求 driver.get('https://www.jd.com') # 往京东主页输入框输入墨菲定律，按回车键 input = driver.find_element_by_id('key') input.send_keys('墨菲定律') input.send_keys(Keys.ENTER) # 调用获取商品信息函数 get_good(driver) finally: driver.close()
二 BeautifulSoup4
BS4
1.什么BeautifulSoup？
bs4是一个解析库，可以通过某种(解析器)来帮我们提取想要的数据。
2.为什么要使用bs4？
因为它可以通过简洁的语法快速提取用户想要的数据内容。
3.解析器的分类
- lxml
- html.parser
4.安装与使用
- 遍历文档树
- 搜索文档树
补充知识点:
数据格式:
json数据:
{
"name": "tank"
}
XML数据:
tank
HTML:
生成器: yield 值（把值放进生成器中）
def f():
# return 1
yield 1
yield 2
yield 3
g = f()
print(g)
for line in g:
print(line)
六、 bs4安装与使用
'''''' ''' 安装解析器: pip3 install lxml 安装解析库: pip3 install bs4 ''' html_doc = """The Dormouse's story $37
Once upon a time there were three little sisters; and their names were Elsie, Lacie and Tillie; and they lived at the bottom of a well.
...
""" from bs4 import BeautifulSoup # python自带的解析库 # soup = BeautifulSoup(html_doc, 'html.parser') # 调用bs4得到一个soup对象 soup = BeautifulSoup(html_doc, 'lxml') # bs4对象 print(soup) # bs4类型 print(type(soup)) # 美化功能 html = soup.prettify() print(html)
七、bs4解析库之遍历文档树
html_doc = """The Dormouse's story $37
Once upon a time there were three little sisters; and their names were Elsie, Lacie and Tillie; and they lived at the bottom of a well.
...
""" from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc, 'lxml') # print(soup) # print(type(soup)) # 遍历文档树 # 1、直接使用 ***** print(soup.html) print(type(soup.html)) print(soup.a) print(soup.p) # 2、获取标签的名称 print(soup.a.name) # 3、获取标签的属性 ***** print(soup.a.attrs) # 获取a标签中所有的属性 print(soup.a.attrs['href']) # 4、获取标签的文本内容 ***** print(soup.p.text) # $37 # 5、嵌套选择 print(soup.html.body.p) # 6、子节点、子孙节点 print(soup.p.children) # 返回迭代器对象 print(list(soup.p.children)) # [$37] # 7、父节点、祖先节点 print(soup.b.parent) print(soup.b.parents) print(list(soup.b.parents)) # 8、兄弟节点 （sibling: 兄弟姐妹） print(soup.a) # 获取下一个兄弟节点 print(soup.a.next_sibling) # 获取下一个的所有兄弟节点,返回的是一个生成器 print(soup.a.next_siblings) print(list(soup.a.next_siblings)) # 获取上一个兄弟节点 print(soup.a.previous_sibling) # 获取上一个的所有兄弟节点，返回的是一个生成器 print(list(soup.a.previous_siblings))
八、bs4之搜索文档树
'''''' ''' find: 找第一个 find_all: 找所有 标签查找与属性查找: name 属性匹配 name 标签名 attrs 属性查找匹配 text 文本匹配 标签: - 字符串过滤器 字符串全局匹配 - 正则过滤器 re模块匹配 - 列表过滤器 列表内的数据匹配 - bool过滤器 True匹配 - 方法过滤器 用于一些要的属性以及不需要的属性查找。 属性: - class_ - id ''' html_doc = """The Dormouse's story $37
Once upon a time there were three little sisters; and their names wereElsieLacie andTillieand they lived at the bottom of a well.
...
""" from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc, 'lxml') # name 标签名 # attrs 属性查找匹配 # text 文本匹配 # find与find_all搜索文档 ''' 字符串过滤器 ''' p = soup.find(name='p') p_s = soup.find_all(name='p') print(p) print(p_s) # name + attrs p = soup.find(name='p', attrs={"id": "p"}) print(p) # name + text tag = soup.find(name='title', text="The Dormouse's story") print(tag) # name + attrs + text tag = soup.find(name='a', attrs={"class": "sister"}, text="Elsie") print(tag) ''' - 正则过滤器 re模块匹配 ''' import re # name # 根据re模块匹配带有a的节点 a = soup.find(name=re.compile('a')) print(a) a_s = soup.find_all(name=re.compile('a')) print(a_s) # attrs a = soup.find(attrs={"id": re.compile('link')}) print(a) # - 列表过滤器 # 列表内的数据匹配 print(soup.find(name=['a', 'p', 'html', re.compile('a')])) print(soup.find_all(name=['a', 'p', 'html', re.compile('a')])) # - bool过滤器 # True匹配 print(soup.find(name=True, attrs={"id": True})) # - 方法过滤器 # 用于一些要的属性以及不需要的属性查找。 def have_id_not_class(tag): # print(tag.name) if tag.name == 'p' and tag.has_attr("id") and not tag.has_attr("class"): return tag # print(soup.find_all(name=函数对象)) print(soup.find_all(name=have_id_not_class)) # 补充知识点: # id a = soup.find(id='link2') print(a) # class p = soup.find(class_='sister') print(p)
九、作业——爬取豌豆荚数据
'''''' ''' 3.爬取豌豆荚app数据 spider_method: requests + bs4 or selenium url: https://www.wandoujia.com/category/6001 data: 名称、详情页url、下载人数、app大小 app_name, detail_url, download_num, app_size ''' #爬虫三部曲 #1.发送请求 import requests def get_page(url): reponse = requests.get(url) #print(reponse.text) return reponse # 2.解析数据 import re def parse_index(html): movie_list = re.findall('.*?.*?(.*?)万人安装 ・ .*?MB
',html,re.S) #print(movie_list) return movie_list # 3.保存数据 def save_data(movie): detail_url, app_name, download_num, app_size = movie data = f''' =======欢迎观赏======= 游戏名称：{app_name} 详情页url：{detail_url} 下载人数：{download_num}万人 app大小：{app_size}MB =======谢谢观赏======= \n \n ''' print(data) with open('wandoujia.txt','a',encoding='utf-8') as f: f.write(data) if __name__ == '__main__': #拼接所有主页 url=f'https://www.wandoujia.com/category/6001' print(url) #1.往每个主页发送请求 index_res = get_page(url) #2.解析主页获取电影信息 movie_list = parse_index(index_res.text) for movie in movie_list: #3.保存数据 #print(movie_list) save_data(movie)