简介

scrapy做简单的大量数据的爬虫太方便了，一般就三个文件 setting.py，item.py ，xxx_spider.py，代码量很少。存json的时候最高爬取过600多MB的文本。去年存入postgresql的时候最多的一次大概一次性爬取了1000多万的关键词（key,[related1,related2]，key,related对调的时候靠用redis放内存中分批计算才成功，把老化的机械硬盘换成固态硬盘之后，就不用redis了）。

代码部分

spider 代码，从本地muci.txt中获取关键词，setting控制爬取深度（DEEP_LIMIT = 1就是只爬取当前关键词的相关搜索词）

# -*- coding:utf8 -*-

from scrapy.spiders import CrawlSpider
from scrapy import Request

from mbaidu.items import baiduItemtj
import os
from scrapy.conf import settings

settings.overrides['RESULT_JSONFILE'] = 'mbaidutj.json'

class MbaiduSpider(CrawlSpider):

    name = 'mbaidu_xg'
    allowed_domains = ['m.baidu.com']
    def start_requests(self):
        mucifile = open(os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), "muci.txt"), 'r')
        for key in mucifile.readlines():
            nextword = key.strip("\n").strip()
            if nextword != "":
                yield Request('https://m.baidu.com/s?word=' + nextword, self.parse)

    def parse(self, response):
        related = response.css('#reword .rw-list a::text').extract()
        if related:
            for rw in related:
                item = baiduItemtj()
                item['keyword'],item['description'] = [rw,'']
                yield item
        rwlink = response.css('#reword .rw-list a::attr(href)').extract()
        if rwlink:
            for link in rwlink:
                yield Request(link,self.parse)
        tj = response.css('.wa-sigma-celebrity-rela-entity.c-scroll-element-gap a')
        if tj:
            for i in tj:
                item = baiduItemtj()
                item['keyword'],item['description'] = i.css('p::text').extract()
                yield item
            tjlink = response.css('.wa-sigma-celebrity-rela-entity.c-scroll-element-gap a::attr(href)').extract()
            if tjlink:
                for link in tjlink:
                    yield Request(link,self.parse)

处理json编码的代码 piplines.py中，本地存储python乱码是使用（加入setting.py中），估计是python2的锅，python3不一定要

class JsonWriterPipeline(object):
    def __init__(self):
        self.file = codecs.open(settings.get('RESULT_JSONFILE','default.json'), 'w', encoding='utf-8')

    def process_item(self, item, spider):
        line = json.dumps(dict(item)) + "\n"
        self.file.write(line.decode('unicode_escape'))
        # item = {"haha": "hehe"}
        # return {"log": "可以不需要return数据了,返回的数据会再次转成Unicode,交给系统自带的输出"}
        # return item

item.py

class baiduItemtj(scrapy.Item):
    # 右侧推荐有description 底部相关搜索没有 为空
    keyword = scrapy.Field()
    description = scrapy.Field()