步骤一 创建爬取项目：

1. 进入你的桌面文件夹
cd desktop
2. 创建爬虫项目
scrapy startproject imove
3.创建爬虫机器人，名字就叫movie
cd imove
scrapy genspider movie
4.调整settings.py
变更user-agent 
USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.79 Safari/537.36'
拒绝机器人协议
ROBOTSTXT_OBEY = False
管道通
ITEM_PIPELINES = {
   'imovie.pipelines.ImoviePipeline': 300,
}

步骤二 初始化

1. 在填入需要爬入的网站：http://****.com
   填入最开始的那个网页 ： http://****.com.index.html

allowed_domains = ['www.dytt8.net']
start_urls = ['https://www.dytt8.net/html/gndy/dyzz/index.html']
2. 爬取内容的结构化数据类型 items.py
import scrapy

class ImovieItem(scrapy.Item):
    title = scrapy.Field()
    date = scrapy.Field()
    url = scrapy.Field()

步骤三 填写爬虫规则

观察网站，需要爬取电影名字、时间、详情url地址，方便继续深入爬取

网页的规则为：
（Xpath 语言）
//table
名字 = .//a/text()
日期 = .//td[@style='padding-left:3px']/font/text()
URL= 域名+  ".//a/@href" 

步骤四 实现自动翻页

1. 判断是否存在下一页
if response.xpath("//a[text()='下一页']"):
2. 找出下一页网址
（Xpath 语言）
//a[text()='下一页']/@href
3. 点击它！
yield self.make_requests_from_url(next_page)

步骤五 入库

1. import sqlite3
2. sql 建表：
create table if not exists movies (title text ,date text , url text);
3. sql 查表
insert into movies (title,date,url) values (?,?,?);",(item["title"],item["date"],item["url"])
4. 数据库验证（可以不做）parse_sqlite.py

import sqlite3
import pandas as pd

conn = sqlite3.connect("data.sqlite")
df = pd.read_sql_query("select * from movies limit 5;", conn)
print(df)

步骤六 运行

scrapy crawl movie

运行结果：

image.png

全都保存在数据库中，方便下步操作

全部代码：

# movie.py
# -*- coding: utf-8 -*-
import scrapy
from imovie.items import ImovieItem


class MovieSpider(scrapy.Spider):
    name = 'movie'
    allowed_domains = ['www.dytt8.net']
    start_urls = ['https://www.dytt8.net/html/gndy/dyzz/index.html']

    def parse(self, response):
        tables = response.xpath("//table")
        imoveitem = ImovieItem()
        for table in tables:
            try:
                imoveitem["title"] = table.xpath(".//a/text()").extract_first()
                imoveitem["date"] = table.xpath(".//td[@style='padding-left:3px']/font/text()").extract_first().split()[0]
                imoveitem["url"] = "https://www.dytt8.net"+table.xpath(".//a/@href").extract_first()
            except:pass
            print(imoveitem)
            yield imoveitem

        if response.xpath("//a[text()='下一页']"):
            next_page = "https://www.dytt8.net/html/gndy/dyzz/"+response.xpath("//a[text()='下一页']/@href").extract_first()
            yield self.make_requests_from_url(next_page)


# items.py
import scrapy


class ImovieItem(scrapy.Item):
    title = scrapy.Field()
    date = scrapy.Field()
    url = scrapy.Field()


# pipelines.py

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
import sqlite3


class ImoviePipeline(object):
    def __init__(self):
        self.conn = sqlite3.connect("data.sqlite")
        cur = self.conn.cursor()
        # with  self.conn.cursor() as cur:
        #     cur.execute("create table movies (titie text ,date text , url text);")
        cur.execute("create table if not exists movies (title text ,date text , url text);")
        cur.close()

    def process_item(self, item, spider):
        cur = self.conn.cursor()
        # with self.conn.cursor() as cur:
        #     cur.execute("insert into movies (title,date,url) values (?,?,?);",(item["title"],item["date"],item["url"]))
        cur.execute("insert into movies (title,date,url) values (?,?,?);",(item["title"],item["date"],item["url"]))
        self.conn.commit()
        print("插入成功!")
        cur.close()
        return item

# parse_sqlite.py

import sqlite3
import pandas as pd

conn = sqlite3.connect("data.sqlite")
df = pd.read_sql_query("select * from movies;", conn)
print(df)