scrapy实例:爬取天气、气温等

1.创建项目

scrapy startproject weather # weather是项目名称

scrapy crawl spidername开始运行，程序自动使用start_urls构造Request并发送请求，然后调用parse函数对其进行解析，

在这个解析过程中使用rules中的规则从html（或xml）文本中提取匹配的链接，通过这个链接再次生成Request，如此不断循环，直到返回的文本中再也没有匹配的链接，或调度器中的Request对象用尽，程序才停止。

2.确定爬取目标:

scrapy构建的爬虫的爬取过程:

scrapy crawl spidername开始运行，程序自动使用start_urls构造Request并发送请求，然后调用parse函数对其进行解析，在这个解析过程中使用rules中的规则从html（或xml）文本中提取匹配的链接，

通过这个链接再次生成Request，如此不断循环，直到返回的文本中再也没有匹配的链接，或调度器中的Request对象用尽，程序才停止。

allowed_domains:顾名思义,允许的域名,爬虫只会爬取该域名下的url

rule:定义爬取规则,爬虫只会爬取符合规则的url

　　rule有allow属性,使用正则表达式书写匹配规则.正则表达式不熟悉的话可以写好后在网上在线校验,尝试几次后,简单的正则还是比较容易的,我们要用的也不复杂.

　　rule有callback属性可以指定回调函数,爬虫在发现符合规则的url后就会调用该函数,注意要和默认的回调函数parse作区分.(爬取的数据在命令行里都可以看到)

　　rule有follow属性.为True时会爬取网页里所有符合规则的url,反之不会. 我这里设置为了False,因为True的话要爬很久.大约两千多条天气信息

import scrapy
from weather.items import WeatherItem
from scrapy.spiders import Rule, CrawlSpider
from scrapy.linkextractors import LinkExtractor

class Spider(CrawlSpider):
    name = 'weatherSpider'
    #allowed_domains = "www.weather.com.cn"
    start_urls = [
        #"http://www.weather.com.cn/weather1d/101020100.shtml#search"
        "http://www.weather.com.cn/forecast/"
    ]
    rules = (
        #Rule(LinkExtractor(allow=('http://www.weather.com.cn/weather1d/101\d{6}.shtml#around2')), follow=False, callback='parse_item'),
        Rule(LinkExtractor(allow=('http://www.weather.com.cn/weather1d/101\d{6}.shtml$')), follow=True,callback='parse_item'),
    )
    
    
    #多页面爬取时需要自定义方法名称,不能用parse
    def parse_item(self, response):
        item = WeatherItem()
        #city = response.xpath("//div[@class='crumbs fl']/a[2]/text()").extract_first()
        item['city'] = response.xpath("//div[@class='crumbs fl']/a[2]/text()").extract_first()  # 获取省或者直辖市名称
        #if city == '>':
        #item['city'] = response.xpath("//div[@class='crumbs fl']/a[last()-1]/text()").extract_first()#获取非直辖省
        #item['city'] = response.xpath("//div[@class ='crumbs fl']/a[2]/text()").extract_first()#获取直辖市

        #item['city_addition'] = response.xpath("//div[@class ='crumbs fl']/a[last()]/text()").extract_first()#获取直辖市
        #city_addition = response.xpath("//div[@class ='crumbs fl']/a[last()]/text()").extract_first() #获取>字符
        #print("aaaaa"+city)
        #print("nnnnn"+city_addition)
        #if city_addition != city:
            #item['city_addition'] = response.xpath("//div[@class='crumbs fl']/a[2]/text()").extract_first()
        item['city_addition'] = response.xpath("//div[@class ='crumbs fl']/a[last()]/text()").extract_first()  # 获取城市名或者直辖市名称
        #else:
            #item['city_addition'] = ''

        #item['city_addition2'] = response.xpath("//div[@class='crumbs fl']/span[3]/text()").extract_first()


        weatherData = response.xpath("//div[@class='today clearfix']/input[1]/@value").extract_first() #获取当前的气温
        item['data'] = weatherData[0:6] #获取日期
        print("data:"+item['data'])
        item['weather'] = response.xpath("//p[@class='wea']/text()").extract_first() #获取天气
        item['temperatureMax'] = response.xpath("//ul[@class='clearfix']/li[1]/p[@class='tem']/span[1]/text()").extract_first() #最高温度
        item['temperatureMin'] = response.xpath("//ul[@class='clearfix']/li[2]/p[@class='tem']/span[1]/text()").extract_first() #最低温度
        yield item

spider.py顾名思义就是爬虫文件

在填写spider.py之前,我们先看看如何获取需要的信息

刚才的命令行应该没有关吧,关了也没关系

win+R在打开cmd,键入:scrapy shell http://www.weather.com.cn/weather1d/101020100.shtml#search #网址是你要爬取的url

这是scrapy的shell命令,可以在不启动爬虫的情况下，对网站的响应response进行处理调试等,主要是调试xpath获取元素的

3.填写Items.py

Items.py只用于存放你要获取的字段:

给自己要获取的信息取个名字:

# -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html
import scrapy

class WeatherItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    city = scrapy.Field()
    city_addition = scrapy.Field()
    city_addition2 = scrapy.Field()
    weather = scrapy.Field()
    data = scrapy.Field()
    temperatureMax = scrapy.Field()
    temperatureMin = scrapy.Field()
    pass

这里写了管道文件,还要在settings.py设置文件里启用这个pipeline:

6.填写settings.py

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

# Scrapy settings for weather project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://doc.scrapy.org/en/latest/topics/settings.html
#     https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://doc.scrapy.org/en/latest/topics/spider-middleware.html

BOT_NAME = 'weather'

SPIDER_MODULES = ['weather.spiders']
NEWSPIDER_MODULE = 'weather.spiders'


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'weather (+http://www.yourdomain.com)'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32

# Configure a delay for requests for the same website (default: 0)
# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
DOWNLOAD_DELAY = 1
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

# Disable cookies (enabled by default)
#COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
#   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#   'Accept-Language': 'en',
#}

# Enable or disable spider middlewares
# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    'weather.middlewares.WeatherSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'weather.middlewares.WeatherDownloaderMiddleware': 543,
#}

# Enable or disable extensions
# See https://doc.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    'scrapy.extensions.telnet.TelnetConsole': None,
#}

# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
    'weather.pipelines.TxtPipeline': 600,
    #'weather.pipelines.JsonPipeline': 6,
    #'weather.pipelines.ExcelPipeline': 300,
}

# Enable and configure the AutoThrottle extension (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

5.填写pipeline.py

但要保存爬取的数据的话,还需写下pipeline.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 os
import codecs
import json
import csv
from scrapy.exporters import JsonItemExporter
from openpyxl import Workbook

base_dir = os.getcwd()
filename = base_dir + '\\' + 'weather.txt'
with open(filename,'w+') as f:#打开文件
    f.truncate()#清空文件内容


class JsonPipeline(object):
    # 使用FeedJsonItenExporter保存数据
    def __init__(self):
        self.file = open('weather1.json','wb')
        self.exporter = JsonItemExporter(self.file,ensure_ascii =False)
        self.exporter.start_exporting()

    def process_item(self,item,spider):
        print('Write')
        self.exporter.export_item(item)
        return item

    def close_spider(self,spider):
        print('Close')
        self.exporter.finish_exporting()
        self.file.close()

        
class TxtPipeline(object):
    def process_item(self, item, spider):
        #获取当前工作目录
        #base_dir = os.getcwd()
        #filename = base_dir + 'weather.txt'
        #print('创建Txt')
        print("city:"+item['city'])
        print("city_addition:"+item['city_addition'])

        #从内存以追加方式打开文件,并写入对应的数据
        with open(filename, 'a') as f: #追加
            if item['city'] != item['city_addition']:
                f.write('城市:' + item['city'] + '>')
                f.write(item['city_addition'] + '\n')
            else:
                f.write('城市:' + item['city'] + '\n')
                #f.write(item['city_addition'] + '\n')
            f.write('日期:' + item['data'] + '\n')
            f.write('天气:' + item['weather'] + '\n')
            f.write('温度:' + item['temperatureMin'] + '~' + item['temperatureMax'] + '℃\n')
    
class ExcelPipeline(object):
    #创建EXCEL,填写表头
    def __init__(self):
        self.wb = Workbook()
        self.ws = self.wb.active
        #设置表头
        self.ws.append(['省', '市', '县(乡)', '日期', '天气', '最高温', '最低温'])
    
    def process_item(self, item, spider):
        line = [item['city'], item['city_addition'], item['city_addition2'], item['data'], item['weather'], item['temperatureMax'], item['temperatureMin']]
        self.ws.append(line) #将数据以行的形式添加仅xlsx中
        self.wb.save('weather.xlsx')
        return item
    '''def process_item(self, item, spider):
        base_dir = os.getcwd()
        filename = base_dir + 'weather.csv'
        print('创建EXCEL')
        with open(filename,'w') as f:
            fieldnames = ['省','市', '县(乡)', '天气', '日期', '最高温','最低温'] # 定义字段的名称
            writer = csv.DictWriter(f,fieldnames=fieldnames) # 初始化一个字典对象
            write.writeheader() # 调用writeheader()方法写入头信息
            # 传入相应的字典数据
            write.writerow(dict(item))
    '''

爬虫效果：

确定爬取目标:

这里选择中国天气网做爬取素材,爬取网页之前一定要先分析网页,要获取那些信息,怎么获取更加方便,网页源代码这里只展示部分:

<div class="ctop clearfix">
            <div class="crumbs fl">
                <a href="http://js.weather.com.cn" target="_blank">江苏</a>
                <span>></span>
                <a href="http://www.weather.com.cn/weather/101190801.shtml" target="_blank">徐州</a><span>></span>  <span>鼓楼</span>
            </div>
            <div class="time fr"></div>
        </div>

如果是非直辖市：获取省名称

//div[@class='crumbs fl']/a[last()-1]/text()

取xpath最后一个book元素

book[last()]

取xpath最后第二个book元素

book[last()-1]

posted @ 2019-09-12 16:31 Agoly 阅读(1057) 评论(0) 编辑收藏举报

刷新页面返回顶部

Agoly

欢迎加入：湖北软件测试群
专注性能瓶颈优化分析、安全渗透测试、自动化持续集成测试

scrapy实例:爬取天气、气温等

1.创建项目

scrapy startproject weather # weather是项目名称

2.确定爬取目标:

3.填写Items.py

6.填写settings.py

5.填写pipeline.py

确定爬取目标:

公告

Agoly

欢迎加入：湖北软件测试群 专注性能瓶颈优化分析、安全渗透测试、自动化持续集成测试

scrapy实例:爬取天气、气温等

1.创建项目

scrapy startproject weather # weather是项目名称

2.确定爬取目标:

3.填写Items.py

6.填写settings.py

5.填写pipeline.py

确定爬取目标:

公告

欢迎加入：湖北软件测试群
专注性能瓶颈优化分析、安全渗透测试、自动化持续集成测试