6.20python作业
课堂知识总结：
01 解析库之bs4
'''''' ''' pip3 install beautifulsoup4 # 安装bs4 pip3 install lxml # 下载lxml解析器 ''' html_doc = """ <html><head><title>The Dormouse's story</title></head> <body> <p class="sister"><b>$37</b></p> <p class="story" id="p">Once upon a time there were three little sisters; and their names were <a href="http://example.com/elsie" class="sister" >Elsie</a>, <a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and <a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>; and they lived at the bottom of a well.</p> <p class="story">...</p> """ # 从bs4中导入BeautifulSoup from bs4 import BeautifulSoup # 调用BeautifulSoup实例化得到一个soup对象 # 参数一: 解析文本 # 参数二: # 参数二: 解析器（html.parser、lxml...） soup = BeautifulSoup(html_doc, 'lxml') print(soup) print('*' * 100) print(type(soup)) print('*' * 100) # 文档美化 html = soup.prettify() print(html)
02 bs4之遍历文档树
遍历文档树：
1、直接使用
2、获取标签的名称
3、获取标签的属性
4、获取标签的内容
5、嵌套选择
6、子节点、子孙节点
7、父节点、祖先节点
8、兄弟节点
html_doc = """<html><head><title>The Dormouse's story</title></head><body><p class="sister"><b>$37</b></p><p class="story" id="p">Once upon a time there were three little sisters; and their names were<b>tank</b><a href="http://example.com/elsie" class="sister" >Elsie</a>,<a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and<a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;and they lived at the bottom of a well.<hr></hr></p><p class="story">...</p>""" from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc, 'lxml') ''' 遍历文档树： 1、直接使用 2、获取标签的名称 3、获取标签的属性 4、获取标签的内容 5、嵌套选择 6、子节点、子孙节点 7、父节点、祖先节点 8、兄弟节点 ''' # 1、直接使用 print(soup.p) # 查找第一个p标签 print(soup.a) # 查找第一个a标签 # 2、获取标签的名称 print(soup.head.name) # 获取head标签的名称 # 3、获取标签的属性 print(soup.a.attrs) # 获取a标签中的所有属性 print(soup.a.attrs['href']) # 获取a标签中的href属性 # 4、获取标签的内容 print(soup.p.text) # $37 # 5、嵌套选择 print(soup.html.head) # 6、子节点、子孙节点 print(soup.body.children) # body所有子节点，返回的是迭代器对象 print(list(soup.body.children)) # 强转成列表类型 print(soup.body.descendants) # 子孙节点 print(list(soup.body.descendants)) # 子孙节点 # 7、父节点、祖先节点 print(soup.p.parent) # 获取p标签的父亲节点 # 返回的是生成器对象 print(soup.p.parents) # 获取p标签所有的祖先节点 print(list(soup.p.parents)) # 8、兄弟节点 # 找下一个兄弟 print(soup.p.next_sibling) # 找下面所有的兄弟，返回的是生成器 print(soup.p.next_siblings) print(list(soup.p.next_siblings)) # 找上一个兄弟 print(soup.a.previous_sibling) # 找到第一个a标签的上一个兄弟节点 # 找到a标签上面的所有兄弟节点 print(soup.a.previous_siblings) # 返回的是生成器 print(list(soup.a.previous_siblings))
03 bs4之搜索文档树
搜索文档树:
find() 找一个
find_all() 找多个
标签查找与属性查找:
标签:
name 属性匹配
attrs 属性查找匹配
text 文本匹配
- 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 = """<html><head><title>The Dormouse's story</title></head><body><p class="sister"><b>$37</b></p><p class="story" id="p">Once upon a time there were three little sisters; and their names were<b>tank</b><a href="http://example.com/elsie" class="sister" >Elsie</a>,<a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and<a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;and they lived at the bottom of a well.<hr></hr></p><p class="story">...</p>""" ''' 搜索文档树: find() 找一个 find_all() 找多个 标签查找与属性查找: 标签: name 属性匹配 attrs 属性查找匹配 text 文本匹配 - 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 ''' from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc, 'lxml') # # 字符串过滤器 # # name # p_tag = soup.find(name='p') # print(p_tag) # 根据文本p查找某个标签 # # 找到所有标签名为p的节点 # tag_s1 = soup.find_all(name='p') # print(tag_s1) # # # # attrs # # 查找第一个class为sister的节点 # p = soup.find(attrs={"class": "sister"}) # print(p) # # 查找所有class为sister的节点 # tag_s2 = soup.find_all(attrs={"class": "sister"}) # print(tag_s2) # # # # text # text = soup.find(text="$37") # print(text) # # # # 配合使用: # # 找到一个id为link2、文本为Lacie的a标签 # a_tag = soup.find(name="a", attrs={"id": "link2"}, text="Lacie") # print(a_tag) # # 正则过滤器 # import re # # name # p_tag = soup.find(name=re.compile('p')) # print(p_tag) # 列表过滤器 # import re # # name # tags = soup.find_all(name=['p', 'a', re.compile('html')]) # print(tags) # - bool过滤器 # True匹配 # 找到有id的p标签 # p = soup.find(name='p', attrs={"id": True}) # print(p) # 方法过滤器 # 匹配标签名为a、属性有id没有class的标签 # def have_id_class(tag): # if tag.name == 'a' and tag.has_attr('id') and tag.has_attr('class'): # return tag # # tag = soup.find(name=have_id_class) # print(tag)
04 爬取豌豆荚app数据（提取游戏主页）
主页:
图标地址、下载次数、大小、详情页地址
详情页:
游戏名、图标名、好评率、评论数、小编点评、简介、网友评论、1-5张截图链接地址、下载地址
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
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''' 主页: 图标地址、下载次数、大小、详情页地址 详情页: 游戏名、图标名、好评率、评论数、小编点评、简介、网友评论、1-5张截图链接地址、下载地址 https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B 32 ''' import requests from bs4 import BeautifulSoup # 1、发送请求 def get_page(url): response = requests.get(url) return response # 2、开始解析 # 解析主页 def parse_index(data): soup = BeautifulSoup(data, 'lxml') # 获取所有app的li标签 app_list = soup.find_all(name='li', attrs={"class": "card"}) for app in app_list: # print('tank *' * 1000) # print(app) # 图标地址 img = app.find(name='img').attrs['data-original'] print(img) # 下载次数 down_num = app.find(name='span', attrs={"class": "install-count"}).text print(down_num) import re # 大小 size = soup.find(name='span', text=re.compile("\d+MB")).text print(size) # 详情页地址 detail_url = soup.find(name='a', attrs={"class": "detail-check-btn"}).attrs['href'] print(detail_url) def main(): for line in range(1, 33): url = f"https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page={line}&ctoken=FRsWKgWBqMBZLdxLaK4iem9B" # 1、往app接口发送请求 response = get_page(url) # print(response.text) print('*' * 1000) # 反序列化为字典 data = response.json() # 获取接口中app标签数据 app_li = data['data']['content'] # print(app_li) # 2、解析app标签数据 parse_index(app_li) if __name__ == '__main__': main()
05 爬取豌豆荚app数据（提取游戏详情页）
主页:
图标地址、下载次数、大小、详情页地址
详情页:
游戏名、好评率、评论数、小编点评、下载地址、简介、网友评论、1-5张截图链接地址、
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
32
''' 主页: 图标地址、下载次数、大小、详情页地址 详情页: 游戏名、好评率、评论数、小编点评、下载地址、简介、网友评论、1-5张截图链接地址、 https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B 32 ''' import requests from bs4 import BeautifulSoup # 1、发送请求 def get_page(url): response = requests.get(url) return response # 2、开始解析 # 解析详情页 def parse_detail(text): soup = BeautifulSoup(text, 'lxml') # print(soup) # app名称 name = soup.find(name="span", attrs={"class": "title"}).text # print(name) # 好评率 love = soup.find(name='span', attrs={"class": "love"}).text # print(love) # 评论数 commit_num = soup.find(name='a', attrs={"class": "comment-open"}).text # print(commit_num) # 小编点评 commit_content = soup.find(name='div', attrs={"class": "con"}).text # print(commit_content) # app下载链接 download_url = soup.find(name='a', attrs={"class": "normal-dl-btn"}).attrs['href'] # print(download_url) print( f''' ============= tank ============== app名称:{name} 好评率: {love} 评论数: {commit_num} 小编点评: {commit_content} app下载链接: {download_url} ============= end ============== ''' ) # 解析主页 def parse_index(data): soup = BeautifulSoup(data, 'lxml') # 获取所有app的li标签 app_list = soup.find_all(name='li', attrs={"class": "card"}) for app in app_list: # print(app) # print('tank' * 1000) # print('tank *' * 1000) # print(app) # 图标地址 # 获取第一个img标签中的data-original属性 img = app.find(name='img').attrs['data-original'] print(img) # 下载次数 # 获取class为install-count的span标签中的文本 down_num = app.find(name='span', attrs={"class": "install-count"}).text print(down_num) import re # 大小 # 根据文本正则获取到文本中包含 数字 + MB（\d+代表数字）的span标签中的文本 size = soup.find(name='span', text=re.compile("\d+MB")).text print(size) # 详情页地址 # 获取class为detail-check-btn的a标签中的href属性 # detail_url = soup.find(name='a', attrs={"class": "name"}).attrs['href'] # print(detail_url) # 详情页地址 detail_url = app.find(name='a').attrs['href'] print(detail_url) # 3、往app详情页发送请求 response = get_page(detail_url) # 4、解析app详情页 parse_detail(response.text) def main(): for line in range(1, 33): url = f"https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page={line}&ctoken=FRsWKgWBqMBZLdxLaK4iem9B" # 1、往app接口发送请求 response = get_page(url) # print(response.text) print('*' * 1000) # 反序列化为字典 data = response.json() # 获取接口中app标签数据 app_li = data['data']['content'] # print(app_li) # 2、解析app标签数据 parse_index(app_li) if __name__ == '__main__': main()
06 pymongo简单使用
from pymongo import MongoClient # 1、链接mongoDB客户端 # 参数1: mongoDB的ip地址 # 参数2: mongoDB的端口号 默认:27017 client = MongoClient('localhost', 27017) # print(client) # 2、进入tank_db库,没有则创建 # print(client['tank_db']) # 3、创建集合 # print(client['tank_db']['people']) # 4、给tank_db库插入数据 # 1.插入一条 # data1 = { # 'name': 'tank', # 'age': 18, # 'sex': 'male' # } # client['tank_db']['people'].insert(data1) # 2.插入多条 # data1 = { # 'name': 'tank', # 'age': 18, # 'sex': 'male' # } # data2 = { # 'name': '戚志云', # 'age': 84, # 'sex': 'female' # } # data3 = { # 'name': '沈金金', # 'age': 73, # 'sex': 'male' # } # client['tank_db']['people'].insert([data1, data2, data3]) # # # 5、查数据 # # 查看所有数据 # data_s = client['tank_db']['people'].find() # print(data_s) # <pymongo.cursor.Cursor object at 0x000002EEA6720128> # # 需要循环打印所有数据 # for data in data_s: # print(data) # # # 查看一条数据 # data = client['tank_db']['people'].find_one() # print(data) # 官方推荐使用 # 插入一条insert_one # client['tank_db']['people'].insert_one() # 插入多条insert_many # client['tank_db']['people'].insert_many()
今日作业：
'''
主页:
图标地址、下载次数、大小、详情页地址
详情页:
游戏名、好评率、评论数、小编点评、下载地址、简介、网友评论、1-5张截图链接地址、
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B
32
'''
import requests
from bs4 import BeautifulSoup
from pymongo import MongoClient
'''
3、把豌豆荚爬取的数据插入mongoDB中
- 创建一个wandoujia库
- 把主页的数据存放一个名为index集合中
- 把详情页的数据存放一个名为detail集合中
'''
# 连接MongoDB客户端
client = MongoClient('localhost', 27017)
# 创建或选择wandoujia库，index集合
index_col = client['wandoujia']['index']
# 创建或选择wandoujia库，detail集合
detail_col = client['wandoujia']['detail']
# 1、发送请求
def get_page(url):
response = requests.get(url)
return response
# 2、开始解析
# 解析详情页
def parse_detail(text):
soup = BeautifulSoup(text, 'lxml')
# print(soup)
# app名称
try:
name = soup.find(name="span", attrs={"class": "title"}).text
except Exception:
# 若有异常，设置为None
name = None
# print(name)
# 好评率
try:
love = soup.find(name='span', attrs={"class": "love"}).text
except Exception:
love = None
# print(love)
# 评论数
try:
commit_num = soup.find(name='a', attrs={"class": "comment-open"}).text
except Exception:
commit_num = None
# print(commit_num)
# 小编点评
try:
commit_content = soup.find(name='div', attrs={"class": "con"}).text
except Exception:
commit_content = None
# print(commit_content)
# app下载链接
try:
download_url = soup.find(name='a', attrs={"class": "normal-dl-btn"}).attrs['href']
except Exception:
# 若有异常，设置为None
download_url = None
# print(download_url)
# print(
# f'''
# ============= tank ==============
# app名称:{name}
# 好评率: {love}
# 评论数: {commit_num}
# 小编点评: {commit_content}
# app下载链接: {download_url}
# ============= end ==============
# '''
# )
# 判断所有数据都存在，正常赋值
if name and love and commit_num and commit_content and download_url :
detail_data = {
'name': name,
'love': love,
'commit_num': commit_num,
'commit_content': commit_content,
'download_url': download_url
}
# 若love没有值，则设置为 没人点赞，很惨
if not love:
detail_data = {
'name': name,
'love': "没人点赞，很惨",
'commit_num': commit_num,
'commit_content': commit_content,
'download_url': download_url
}
# 若download_url没有值，则设置为 没有安装包
if not download_url:
detail_data = {
'name': name,
'love': love,
'commit_num': commit_num,
'commit_content': commit_content,
'download_url': '没有安装包'
}
# 插入详情页数据
detail_col.insert(detail_data)
print(f'{name}app数据插入成功!')
# 解析主页
def parse_index(data):
soup = BeautifulSoup(data, 'lxml')
# 获取所有app的li标签
app_list = soup.find_all(name='li', attrs={"class": "card"})
for app in app_list:
# print(app)
# print('tank' * 1000)
# print('tank *' * 1000)
# print(app)
# 图标地址
# 获取第一个img标签中的data-original属性
img = app.find(name='img').attrs['data-original']
# print(img)
# 下载次数
# 获取class为install-count的span标签中的文本
down_num = app.find(name='span', attrs={"class": "install-count"}).text
# print(down_num)
import re
# 大小
# 根据文本正则获取到文本中包含 数字 + MB（\d+代表数字）的span标签中的文本
size = soup.find(name='span', text=re.compile("\d+MB")).text
# print(size)
# 详情页地址
# 获取class为detail-check-btn的a标签中的href属性
# detail_url = soup.find(name='a', attrs={"class": "name"}).attrs['href']
# print(detail_url)
# 详情页地址
detail_url = app.find(name='a').attrs['href']
# print(detail_url)
# 拼接数据
index_data = {
'img': img,
'down_num': down_num,
'size': size,
'detail_url': detail_url
}
# 插入数据
index_col.insert(index_data)
print('主页数据插入成功!')
# 3、往app详情页发送请求
response = get_page(detail_url)
# 4、解析app详情页
parse_detail(response.text)
def main():
for line in range(1, 33):
url = f"https://www.wandoujia.com/wdjweb/api/category/more?catId=6001&subCatId=0&page={line}&ctoken=FRsWKgWBqMBZLdxLaK4iem9B"
# 1、往app接口发送请求
response = get_page(url)
# print(response.text)
print('*' * 1000)
# 反序列化为字典
data = response.json()
# 获取接口中app标签数据
app_li = data['data']['content']
# print(app_li)
# 2、解析app标签数据
parse_index(app_li)
# 执行完所有函数关闭mongoDB客户端
client.close()
if __name__ == '__main__':
main()
