python爬虫系列：Scrapy安装与使用

这篇博文主要写Scrapy框架的安装与使用

 

Scrapy框架安装

命令行进入C:\Anaconda2\Scripts目录，运行：conda install Scrapy

 

创建Scrapy项目

1）进入打算存储的目录下，执行scrapy startproject 文件名 命令即可创建

新文件目录及内容

demo/
    scrapy.cfg
    tutorial/
        __init__.py
        items.py
        pipelines.py
        settings.py
        spiders/
            __init__.py
            ...

这些文件分别是：

• scrapy.cfg: 项目的配置文件
• demo/: 该项目的python模块.
• demo/items.py: 项目中的item文件，即写将要抓取的内容.
• demo/pipelines.py: 项目中的pipelines文件，即写数据如何存储.
• demo/settings.py: 项目的设置文件，即写如何定制Scrapy组件，这个比较复杂可以忽略.
• demo/spiders/: 放置spider代码的目录，即写如何实现爬取.

 

定义爬虫文件

1）定义Item

#item.py
 import scrapy
 from scrapy.item import Item, Field
 
 class DoubanItem(scrapy.Item):
      # define the fields for your item here like:
      # name = scrapy.Field(
      title = scrapy.Field()
      url = scrapy.Field()
      rate= scrapy.Field()
      tag = scrapy.Field()

2)定义spider

# coding:utf8
import scrapy
from douban.items import DoubanItem
from scrapy.selector import Selector
import re
from douban.pipelines import DoubanPipeline
import json
import urllib

import sys
reload(sys)
sys.setdefaultencoding('utf-8')
class DmozSpider(scrapy.Spider):
    name = "dmoz"
    allowed_domains = ["douban.com"]
    start_urls = [
        "https://movie.douban.com/j/search_subjects?type=movie&tag=热门&sort=recommend&page_limit=1000&page_start=0",
    ]
    
    def start_requests(self):       
        reqs = []
        tags = [u'热门', u'最新', u'经典', u'豆瓣高分', u'冷门佳片', u'华语', u'欧美',
                u'韩国', u'日本', u'动作', u'喜剧', u'爱情', u'科幻', u'悬疑', u'恐怖', u'文艺']
        
        for i in tags:
            url = 'https://movie.douban.com/j/search_subjects?type=movie&tag=' + str(i) + '&sort=recommend&page_limit=1000&page_start=0'
            req = scrapy.Request(url)
            reqs.append(req)

        return reqs

    def parse(self, response):
        html = response.body
        url = response.url
        # print u'地址',url
        tag = re.findall(u'tag=(.*?)&',url)[0]
        tag=urllib.unquote(tag)
        # print type(tag)

        dictt = json.loads(html)
        dd = dictt['subjects']
        items = []
        for a in dd:
            # self.get_tag(tag)
            pre_item = TutorialItem()
            pre_item['url'] = a['url']
            pre_item['title'] = a['title']
            pre_item['rate'] = a['rate']
            pre_item['tag'] = tag           
            items.append(pre_item)

        return items

3)定义pipeline

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

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

import pymongo

class DoubanPipeline(object):

    def process_item(self, item, spider):
        db = spider.settings.get('db')
        dbb = pymongo.MongoClient(db)
        db = dbb['douban']
        # lis = (item['url'],item['rate'])
        db.info.insert(dict(item))
        # lis = (item['title'], item['PORT'], item['POSITION'], item[
        #        'TYPE'], item['SPEED'], item['last_check_time'])
        return item

4）定义setting

MONGO_HOST = "127.0.0.1"  # 主机IP
MONGO_PORT = 27017  # 端口号
MONGO_DB = "Spider"  # 库名 
MONGO_COLL = "douban"  # collection名
# MONGO_USER = "Ryana"
# MONGO_PSW = "123456"

 

运行Spider

进入spider所在的文件夹，执行scrapy crawl  spiderName 命令即可，这里再推荐一个MongoDB可视化工具Robomongo,运行结果如下图