Python Learning Day8

bp4解析库

pip3 install beautifulsoup4 # 安装bs4
pip3 install lxml # 下载lxml解析器

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.

...

""" # 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)


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))


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)

爬取豌豆荚游戏主页

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/morecatId=6001&subCatId=0&page=1&ctoken=FRsWKgWBqMBZLdxLaK4iem9B

https://www.wandoujia.com/wdjweb/api/category/morecatId=6001&subCatId=0&page=2&ctoken=FRsWKgWBqMBZLdxLaK4iem9B

https://www.wandoujia.com/wdjweb/api/category/morecatId=6001&subCatId=0&page=3&ctoken=FRsWKgWBqMBZLdxLaK4iem9B

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()

爬取豌豆荚数据

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
# 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()

pymongo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)  # 
# # 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()

 

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