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]

scrapy实例:爬取天气、气温等的更多相关文章

  1. scrapy实例:爬取中国天气网

    1.创建项目 在你存放项目的目录下,按shift+鼠标右键打开命令行,输入命令创建项目: PS F:\ScrapyProject> scrapy startproject weather # w ...

  2. [scrapy]实例:爬取jobbole页面

    工程概览: 创建工程 scrapy startproject ArticleSpider 创建spider cd /ArticleSpider/spiders/ 新建jobbole.py # -*- ...

  3. python爬虫爬取天气数据并图形化显示

    前言 使用python进行网页数据的爬取现在已经很常见了,而对天气数据的爬取更是入门级的新手操作,很多人学习爬虫都从天气开始,本文便是介绍了从中国天气网爬取天气数据,能够实现输入想要查询的城市,返回该 ...

  4. 吴裕雄--天生自然PYTHON爬虫:安装配置MongoDBy和爬取天气数据并清洗保存到MongoDB中

    1.下载MongoDB 官网下载:https://www.mongodb.com/download-center#community 上面这张图选择第二个按钮 上面这张图直接Next 把bin路径添加 ...

  5. Python脚本:爬取天气数据并发邮件给心爱的Ta

    第一部分:爬取天气数据 # 在函数调用 get_weather(url = 'https://www.tianqi.com/foshan') 的 url中更改城市,foshan为佛山市 1 impor ...

  6. 毕设之Python爬取天气数据及可视化分析

    写在前面的一些P话:(https://jq.qq.com/?_wv=1027&k=RFkfeU8j) 天气预报我们每天都会关注,我们可以根据未来的天气增减衣物.安排出行,每天的气温.风速风向. ...

  7. 简单的scrapy实战:爬取腾讯招聘北京地区的相关招聘信息

    简单的scrapy实战:爬取腾讯招聘北京地区的相关招聘信息 简单的scrapy实战:爬取腾讯招聘北京地区的相关招聘信息 系统环境:Fedora22(昨天已安装scrapy环境) 爬取的开始URL:ht ...

  8. 使用scrapy框架爬取自己的博文(2)

    之前写了一篇用scrapy框架爬取自己博文的博客,后来发现对于中文的处理一直有问题- - 显示的时候 [u'python\u4e0b\u722c\u67d0\u4e2a\u7f51\u9875\u76 ...

  9. 如何提高scrapy的爬取效率

    提高scrapy的爬取效率 增加并发: 默认scrapy开启的并发线程为32个,可以适当进行增加.在settings配置文件中修改CONCURRENT_REQUESTS = 100值为100,并发设置 ...

随机推荐

  1. Ubuntu19 安装Theano出现“No module named ‘theano.compat.six’”

    解决办法:直接在下载好pythearn2包的目录下,对setup.py文件进行修改:将  from theano.compat.six.moves import input 改为  from six. ...

  2. echart的legend不显示问题

    legend的data与series的name 两者必须同时存在,且数量和文字内容必须一致.

  3. 使用VS2005编译安装openssl1.1.1c

    1.首先获取openssl源码包 openssl-1.1.1c.tar.gz: 2.安装 ActivePerl: 2.解压源码包,打开vs2005命令行工具,通过命令行进入openssl源码包根目录: ...

  4. 网络爬虫引发的问题及robots协议

    一.网络爬虫的尺寸 1.以爬取网页,玩转网页为目的进行小规模,数据量小对爬取速度不敏感的可以使用request库实现功能(占90%) 2.以爬取网站或爬取系列网站为目的,比如说获取一个或多个旅游网站的 ...

  5. JS中遍历对象属性的四种方法

    Object.keys().Object.values().Object.entries().for...in.Map (1)Object.keys(): let ex1 = {c1: 'white' ...

  6. 第二个视频作品《[SpringCloudAlibaba]微服务之注册中心nacos》上线了

    1.场景描述 第二个视频作品出炉了,<[SpringCloudAlibaba]微服务之注册中心nacos>上线了,有需要的朋友可以直接点击链接观看.(如需购买,请通过本文链接购买) 2. ...

  7. Oracle 定时备份数据库

    [操作说明] 在前面的博客中,学习了如何Oracle如何备份数据库,实际开发过程中数据库应该每隔一段时间就要备份一次,所以我们就需要一个定时执行这个代码的功能,同时备份的文件可能进行一些处理,比如压缩 ...

  8. 测试工程师如何使用 CODING 进行测试管理

    CODING 为您的企业提供从概念到软件开发再到产品发布的全流程全周期软件研发管理,为您的研发团队提供全程助力,帮助研发团队捋清需求.不断迭代.快速反馈并能实时追踪项目进度直到完成.同时 CODING ...

  9. Oracle通过SQL语句查看table所引用的对象(View/Function/Procedure/Trigger)

    通过使用user_dependencies进行查看,如下: SELECT * FROM user_dependencies WHERE referenced_name='SFCUSN' --Table ...

  10. css字体效果

    text-shadow还没有出现时,大家在网页设计中阴影一般都是用photoshop做成图片,现在有了css3可以直接使用text-shadow属性来指定阴影.这个属性可以有两个作用,产生阴影和模糊主 ...