Python 学习day8
1.基于豌豆荚爬取剩下的简介截图图片地址、网友评论。
2.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
如下：
import requests
from bs4 import BeautifulSoup
from pymongo import MongoClient
client = MongoClient('localhost',27017)
index_col = client['wandoujia']['index']
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')
try:
name= soup.find(name="span",attrs={"class":"title"}).text
except Exception:
name = None
try:
love = soup.find(name='span',attrs={"class":"love"}).text
except Exception:
love = None
try:
commit_num = soup.find(name='a',attrs={"class":"comment-open"}).text
except Exception:
commit_num = None
try:
commit_content = soup.find(name='div',attrs={"class":"con"}).text
except Exception:
commit_content = None
try:
download_url = soup.find(name='a',attrs={"class":"normal-dl-btn"}).attrs['href']
except Exception:
download_url = None
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
}
if not love:
detail_data={
'name': name,
'love': "没人点赞",
'commit_num': commit_num,
'commit_content': commit_content,
'download_url': download_url
}
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"
}
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()
课堂内容
1.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>
"""
from bs4 import BeautifulSoup
#从bs4中导入BeautifulSoup对象
#参数一：解析文本
#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)
2.bs4之遍历文档树
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>""" from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc,'lxml') ''' 1、用法 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_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_sibling)#返回的是生成器 print(list(soup.a.previous_sibling))
3.bs4之搜索文档树
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')
#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)
4.爬取豌豆荚app数据
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
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:
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
#获取class为detail-check-btn的a标签中的href属性
detail_url = app.find(name='a').attrs['href']
print(detail_url)
#3.往详情页发送请求
response = get_page(detail_url)
#4.解析app详情页
parse_detail(response.text)
def parse_detail(text):
soup = BeautifulSoup(text,'lxml')
#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(
f'''
=========begin============
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===============
'''
)
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=1XgmoJKndXkl17m9HGiCMmJx"
#1.往app接口发送请求
response = get_page(url)
#print(respnse.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()
5.pymongo的简单使用方法
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': '*',
'age': 18,
'sex': 'male'
}
data2 = {
'name': '**,
'age': 21,
'sex': 'female'
}
data3 = {
'name': '***,
'age': 73,
'sex': 'female'
}
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()
浙公网安备 33010602011771号