[Python爬虫] scrapy爬虫系列 <一>.安装及入门介绍

        前面介绍了很多Selenium基于自动测试的Python爬虫程序，主要利用它的xpath语句，通过分析网页DOM树结构进行爬取内容，同时可以结合Phantomjs模拟浏览器进行鼠标或键盘操作。但是，更为广泛使用的Python爬虫框架是——Scrapy爬虫。这是一篇在Windows系统下介绍 Scrapy爬虫安装及入门介绍的相关文章。

        官方 Scrapy  ：http://scrapy.org/
        官方英文文档：http://doc.scrapy.org/en/latest/index.html
        官方中文文档：https://scrapy-chs.readthedocs.org/zh_CN/0.24/index.html

一. 安装过程

        本文主要讲述Windows下的安装过程，首先我的Python是2.7.8版本。
        主要通过Python的PIP语句进行安装：

pip install scrapy

        此时，scrapy安装成功，可以进行第二步"第一个scrapy爬虫实现"了~

easy_install的用法：    
1） 安装一个包    
 $ easy_install <package_name>    
 $ easy_install "<package_name>==<version>"    
2) 升级一个包    
 $ easy_install -U "<package_name>>=<version>"    
    
pip的用法    
1) 安装一个包    
 $ pip install <package_name>    
 $ pip install <package_name>==<version>    
2) 升级一个包 (如果不提供version号，升级到最新版本）    
 $ pip install --upgrade <package_name>>=<version>    
3）删除一个包    
 $ pip uninstall <package_name> 

二. 第一个scrapy爬虫程序实现

        官网介绍：
        Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。可以应用在包括数据挖掘，信息处理或存储历史数据等一系列的程序中。其最初是为了 页面抓取 (更确切来说, 网络抓取 )所设计的， 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。
        An open source and collaborative framework for extracting the data you need from websites. In a fast, simple, yet extensible way.
        下面是参考官网在windows下实现的第一个scrapy爬虫程序：

import scrapy

class BlogSpider(scrapy.Spider):
    name = 'blogspider'
    start_urls = ['http://blog.scrapinghub.com']

    def parse(self, response):
        for url in response.css('ul li a::attr("href")').re(r'.*/\d\d\d\d/\d\d/$'):
            yield scrapy.Request(response.urljoin(url), self.parse_titles)

    def parse_titles(self, response):
        for post_title in response.css('div.entries > ul > li a::text').extract():
            yield {'title': post_title}

三. Scrapy入门介绍

        入门介绍参考：初窥Scrapy 和 Scrapy入门教程
        给大家简单举个例子，使用maxliaops的Scrapy爬虫爬取腾讯的职位招聘信息。
        代码下载：https://github.com/maxliaops/scrapy-itzhaopin
        源文链接：http://blog.csdn.net/HanTangSongMing/article/details/24454453
        目标网址为：http://hr.tencent.com/position.php

1.chcp 936
unknown encoding: cp65001异常时，需要将编码(UTF-8)修改为 简体中文(GBK)

2.cd G:\software\Program software\Python\python insert\scrapy project
去到安装Scrapy目录下

3.cd scrapy-itzhaopin-master\itzhaopin
再次去到下载的文件itzhaopin目录下

4.scrapy crawl tencent
运行代码启动这个Spider，进行下载

        其中代码itzhaopin项目的结果图如下所示：参考原文作者博客

├── itzhaopin
│   ├── itzhaopin
│   │   ├── __init__.py
│   │   ├── items.py
│   │   ├── pipelines.py
│   │   ├── settings.py
│   │   └── spiders
│   │      └── __init__.py
│   └── scrapy.cfg

scrapy.cfg: 项目配置文件
items.py: 需要提取的数据结构定义文件
pipelines.py:管道定义，用来对items里面提取的数据做进一步处理，如保存等
settings.py: 爬虫配置文件
spiders: 放置spider的目录

# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html

from scrapy.item import Item, Field  
class TencentItem(Item):  
    name = Field()                # 职位名称  
    catalog = Field()             # 职位类别  
    workLocation = Field()        # 工作地点  
    recruitNumber = Field()       # 招聘人数  
    detailLink = Field()          # 职位详情页链接  
    publishTime = Field()         # 发布时间  

import re
import json

from scrapy.selector import Selector
try:
    from scrapy.spider import Spider
except:
    from scrapy.spider import BaseSpider as Spider
from scrapy.utils.response import get_base_url
from scrapy.utils.url import urljoin_rfc
from scrapy.contrib.spiders import CrawlSpider, Rule
from scrapy.contrib.linkextractors.sgml import SgmlLinkExtractor as sle


from itzhaopin.items import *
from itzhaopin.misc.log import *


class TencentSpider(CrawlSpider):
    name = "tencent"
    allowed_domains = ["tencent.com"]
    start_urls = [
        "http://hr.tencent.com/position.php"
    ]
    rules = [
        Rule(sle(allow=("/position.php\?&start=\d{,4}#a")), follow=True, callback='parse_item')
    ]

    def parse_item(self, response):
        items = []
        sel = Selector(response)
        base_url = get_base_url(response)
        sites_even = sel.css('table.tablelist tr.even')
        for site in sites_even:
            item = TencentItem()
            item['name'] = site.css('.l.square a').xpath('text()').extract()[0]
            relative_url = site.css('.l.square a').xpath('@href').extract()[0]
            item['detailLink'] = urljoin_rfc(base_url, relative_url)
            item['catalog'] = site.css('tr > td:nth-child(2)::text').extract()[0]
            item['workLocation'] = site.css('tr > td:nth-child(4)::text').extract()[0]
            item['recruitNumber'] = site.css('tr > td:nth-child(3)::text').extract()[0]
            item['publishTime'] = site.css('tr > td:nth-child(5)::text').extract()[0]
            items.append(item)
            #print repr(item).decode("unicode-escape") + '\n'

        sites_odd = sel.css('table.tablelist tr.odd')
        for site in sites_odd:
            item = TencentItem()
            item['name'] = site.css('.l.square a').xpath('text()').extract()[0]
            relative_url = site.css('.l.square a').xpath('@href').extract()[0]
            item['detailLink'] = urljoin_rfc(base_url, relative_url)
            item['catalog'] = site.css('tr > td:nth-child(2)::text').extract()[0]
            item['workLocation'] = site.css('tr > td:nth-child(4)::text').extract()[0]
            item['recruitNumber'] = site.css('tr > td:nth-child(3)::text').extract()[0]
            item['publishTime'] = site.css('tr > td:nth-child(5)::text').extract()[0]
            items.append(item)
            #print repr(item).decode("unicode-escape") + '\n'

        info('parsed ' + str(response))
        return items


    def _process_request(self, request):
        info('process ' + str(request))
        return request

# 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

from scrapy import signals
import json
import codecs

class JsonWithEncodingTencentPipeline(object):

    def __init__(self):
        self.file = codecs.open('tencent.json', 'w', encoding='utf-8')

    def process_item(self, item, spider):
        line = json.dumps(dict(item), ensure_ascii=False) + "\n"
        self.file.write(line)
        return item

    def spider_closed(self, spider):
        self.file.close(
)

# Scrapy settings for itzhaopin project
#
# For simplicity, this file contains only the most important settings by
# default. All the other settings are documented here:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#

BOT_NAME = 'itzhaopin'

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

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

ITEM_PIPELINES = {
    'itzhaopin.pipelines.JsonWithEncodingTencentPipeline': 300,
}

LOG_LEVEL = 'INFO'