1. 海王评论数据爬取前分析

海王上映了，然后口碑炸了，对咱来说，多了一个可爬可分析的电影，美哉~

摘录一个评论

零点场刚看完，温导的电影一直很不错，无论是速7，电锯惊魂还是招魂都很棒。打斗和音效方面没话说非常棒，特别震撼。总之，DC扳回一分（￣▽￣）。比正义联盟好的不止一点半点（我个人感觉）。还有艾梅伯希尔德是真的漂亮，温导选的人都很棒。

真的第一次看到这么牛逼的电影 转场特效都吊炸天

2. 海王案例开始爬取数据

数据爬取的依旧是猫眼的评论，这部分内容咱们用把牛刀，scrapy爬取，一般情况下，用一下requests就好了

抓取地址

http://m.maoyan.com/mmdb/comments/movie/249342.json?_v_=yes&offset=15&startTime=2018-12-11%2009%3A58%3A43

关键参数

url:http://m.maoyan.com/mmdb/comments/movie/249342.json

offset:15

startTime:起始时间

scrapy 爬取猫眼代码特别简单，我分开几个py文件即可。

Haiwang.py

import scrapy

import json

from haiwang.items import HaiwangItem

class HaiwangSpider(scrapy.Spider):

    name = 'Haiwang'

    allowed_domains = ['m.maoyan.com']

    start_urls = ['http://m.maoyan.com/mmdb/comments/movie/249342.json?_v_=yes&offset=0&startTime=0']

    def parse(self, response):

        print(response.url)

        body_data = response.body_as_unicode()

        js_data = json.loads(body_data)

        item = HaiwangItem()

        for info in js_data["cmts"]:

            item["nickName"] = info["nickName"]

            item["cityName"] = info["cityName"] if "cityName" in info else ""

            item["content"] = info["content"]

            item["score"] = info["score"]

            item["startTime"] = info["startTime"]

            item["approve"] = info["approve"]

            item["reply"] = info["reply"]

            item["avatarurl"] = info["avatarurl"]

            yield item

        yield scrapy.Request("http://m.maoyan.com/mmdb/comments/movie/249342.json?_v_=yes&offset=0&startTime={}".format(item["startTime"]),callback=self.parse)

setting.py

设置需要配置headers

DEFAULT_REQUEST_HEADERS = {

    "Referer":"http://m.maoyan.com/movie/249342/comments?_v_=yes",

    "User-Agent":"Mozilla/5.0 Chrome/63.0.3239.26 Mobile Safari/537.36",

    "X-Requested-With":"superagent"

}

需要配置一些抓取条件

# Obey robots.txt rules

ROBOTSTXT_OBEY = False

# See also autothrottle settings and docs

DOWNLOAD_DELAY = 1

# Disable cookies (enabled by default)

COOKIES_ENABLED = False

开启管道

# Configure item pipelines

# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html

ITEM_PIPELINES = {

   'haiwang.pipelines.HaiwangPipeline': 300,

}

items.py

获取你想要的数据

import scrapy

class HaiwangItem(scrapy.Item):

    # define the fields for your item here like:

    # name = scrapy.Field()

    nickName = scrapy.Field()

    cityName = scrapy.Field()

    content = scrapy.Field()

    score = scrapy.Field()

    startTime = scrapy.Field()

    approve = scrapy.Field()

    reply =scrapy.Field()

    avatarurl = scrapy.Field()

pipelines.py

保存数据，数据存储到csv文件中

import os

import csv

class HaiwangPipeline(object):

    def __init__(self):

        store_file = os.path.dirname(__file__) + '/spiders/haiwang.csv'

        self.file = open(store_file, "a+", newline="", encoding="utf-8")

        self.writer = csv.writer(self.file)

    def process_item(self, item, spider):

        try:

            self.writer.writerow((

                item["nickName"],

                item["cityName"],

                item["content"],

                item["approve"],

                item["reply"],

                item["startTime"],

                item["avatarurl"],

                item["score"]

            ))

        except Exception as e:

            print(e.args)

        def close_spider(self, spider):

            self.file.close()

begin.py

编写运行脚本

from scrapy import cmdline

cmdline.execute(("scrapy crawl Haiwang").split())

走起，搞定，等着数据来到，就可以了