本文介绍: 只不过运行过程变成了红色,但可以像普通python代码一样可以随时暂停。

一、网页信息

二、检查网页,找出目标内容

三、根据网页格式写正常爬虫代码

from bs4 import BeautifulSoup
import requests

headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36',
}
url = 'http://tuijian.hao123.com/'
response = requests.get(url=url,headers=headers)
response.encoding='utf-8'

soup = BeautifulSoup(response.text, 'html.parser')
list_div = soup.find('div', class_='v2-nav')
ul_tags = list_div.find_all('ul')[0]
li_tags = ul_tags.find_all('li')

for li in li_tags:
    a_tag = li.find('a')
    if a_tag:
        title = a_tag.text
        href = a_tag['href']
        if title in ["娱乐", "体育", "财经", "科技", "历史"]:
            print(f"{title}: {href}")

四、创建Scrapy项目haohao

1.进入相关目录中,执行:scrapy startproject haohao

2.创建结果

五、创建爬虫项目haotuijian.py

1.进入相关目录中,执行:scrapy genspider haotuijian http://tuijian.hao123.com/

2.执行结果,目录中出现haotuijian.py文件

六、写爬虫代码和配置相关文件

1.haotuijian.py文件代码
import scrapy
from bs4 import BeautifulSoup
from ..items import HaohaoItem

class HaotuijianSpider(scrapy.Spider):
    name = 'haotuijian'
    allowed_domains = ['tuijian.hao123.com']
    start_urls = ['http://tuijian.hao123.com/']

    def parse(self, response):
        soup = BeautifulSoup(response.text, 'html.parser')
        list_div = soup.find('div', class_='v2-nav')
        ul_tags = list_div.find_all('ul')[0]
        li_tags = ul_tags.find_all('li')

        for li in li_tags:
            a_tag = li.find('a')
            if a_tag:
                title = a_tag.text
                href = a_tag['href']
                if title in ["娱乐", "体育", "财经", "科技", "历史"]:
                    item = HaohaoItem()  # 创建一个HaohaoItem实例来传输保存数据
                    item['title'] = title
                    item['href'] = href
                    yield item
2.items.py文件代码
# Define here the models for your scraped items
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/items.html

import scrapy


class HaohaoItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title = scrapy.Field()
    href = scrapy.Field()
3.pipelines.py文件代码(保存数据到Mongodb、Mysql、Excel中)
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html


# useful for handling different item types with a single interface
from itemadapter import ItemAdapter
from pymongo import MongoClient
import openpyxl
import pymysql

#保存到mongodb中
class HaohaoPipeline:
    def __init__(self):
        self.client = MongoClient('mongodb://localhost:27017/')
        self.db = self.client['qiangzi']
        self.collection = self.db['hao123']
        self.data = []

    def close_spider(self, spider):
        if len(self.data) > 0:
            self._write_to_db()
        self.client.close()

    def process_item(self, item, spider):
        self.data.append({
            'title': item['title'],
            'href': item['href'],
        })
        if len(self.data) == 100:
            self._write_to_db()
            self.data.clear()
        return item

    def _write_to_db(self):
        self.collection.insert_many(self.data)
        self.data.clear()

#保存到mysql中
class MysqlPipeline:
    def __init__(self):
        self.conn = pymysql.connect(
            host='localhost',
            port=3306,
            user='root',
            password='789456MLq',
            db='pachong',
            charset='utf8mb4'
        )
        self.cursor = self.conn.cursor()
        self.data = []
    def close_spider(self,spider):
        if len(self.data) > 0:
            self._writer_to_db()
        self.conn.close()
    def process_item(self, item, spider):
        self.data.append(
            (item['title'],item['href'])
        )
        if len(self.data) == 100:
            self._writer_to_db()
            self.data.clear()
        return item

    def _writer_to_db(self):
        self.cursor.executemany(
            'insert into haohao (title,href)'
            'values (%s,%s)',
            self.data
        )
        self.conn.commit()
    

#保存到excel中
class ExcelPipeline:
    def __init__(self):
        self.wb = openpyxl.Workbook()
        self.ws = self.wb.active
        self.ws.title = 'haohao'
        self.ws.append(('title','href'))
    def open_spider(self,spider):
        pass
    def close_spider(self,spider):
        self.wb.save('haohao.xlsx')
    def process_item(self,item,spider):
        self.ws.append(
            (item['title'], item['href'])
        )
        return item
4.settings.py文件配置

七、运行代码

1.进入相关目录,执行:scrapy crawl haotuijian

2.执行过程

3.执行结果
(1) haohao.excel

(2) Mysql:haohao  (需提前创建表)

(3)Mongodb: hao123

八、知识补充

1.创建main.py文件,并编写代码

2.直接运行main.py文件

3.运行结果与使用指令运行结果相同(只不过运行过程变成了红色,但可以像普通python代码一样可以随时暂停

原文地址:https://blog.csdn.net/m0_74972727/article/details/135720787

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