python学习之-用scrapy框架来创建爬虫(spider)

scrapy简单说明

scrapy  为一个框架  
        框架和第三方库的区别：
        库可以直接拿来就用，
        框架是用来运行，自动帮助开发人员做很多的事，我们只需要填写逻辑就好

命令：

创建一个 项目  ：

cd 到需要创建工程的目录中，

scrapy startproject stock_spider

其中 stock_spider 为一个项目名称


创建一个爬虫

cd  ./stock_spider/spiders

scrapy genspider tonghuashun "http://basic.10jqka.com.cn/600004/company.html"

其中 tonghuashun 为一个爬虫名称 

"http://basic.10jqka.com.cn/600004/company.html"  为爬虫的地址

执行命令

1，创建一个工程:

cd 到需要创建工程的目录

scrapy startproject my_spide

2,创建一个简单的爬虫

cd  ./stock_spider/spiders

scrapy genspider tonghuashun "http://basic.10jqka.com.cn/600004/company.html"

其中 tonghuashun 为一个爬虫名称 

"http://basic.10jqka.com.cn/600004/company.html"  为爬虫的地址

tonghuashun.py代码

import scrapy


class TonghuashunSpider(scrapy.Spider):
    name = 'tonghuashun'
    allowed_domains = ['http://basic.10jqka.com.cn/600004/company.html']
    start_urls = ['http://basic.10jqka.com.cn/600004/company.html']

    def parse(self, response):

        # //*[@id="maintable"]/tbody/tr[1]/td[2]/a
        # res_selector = response.xpath("//*[@id="maintable"]/tbody/tr[1]/td[2]/a")
        # print(res_selector)

        # /Users/eddy/PycharmProjects/helloWord/stock_spider/stock_spider/spiders

        res_selector = response.xpath("//*[@id="ml_001"]/table/tbody/tr[1]/td[1]/a/text()")

        name = res_selector.extract()

        print(name)

        tc_names = response.xpath("//*[@class="tc name"]/a/text()").extract()

        for tc_name in tc_names:
            print(tc_name)

        positions = response.xpath("//*[@class="tl"]/text()").extract()

        for position in positions:
            print(position)

        pass

xpath :

'''
xpath
/   从根节点来进行选择元素
//  从匹配选择的当前节点来对文档中的节点进行选择
.   选择当前的节点
..  选择当前节点的父节点
@   选择属性

body/div    选取属于body的子元素中的所有div元素
//div       选取所有div标签的子元素，不管它们在html中的位置

@lang  选取名称为lang的所有属性

通配符

* 匹配任意元素节点
@* 匹配任何属性节点

//* 选取文档中的所有元素

//title[@*]  选取所有带有属性的title元素

|
在xpath中 | 是代表和的意思

//body/div | //body/li  选取body元素中的所有div元素和li元素


'''

scrapy shell 的使用过程:

'''
scrapy shell 的使用过程

可以很直观的看到自己选择元素的打印

命令：
scrapy shell http://basic.10jqka.com.cn/600004/company.html


查看指定元素命令：
response.xpath("//*[@id="ml_001"]/table/tbody/tr[1]/td[1]/a/text()").extract()


查看 class="tc name" 的所有元素
response.xpath("//*[@class="tc name"]").extract()

查看 class="tc name" 的所有元素 下a标签的text
response.xpath("//*[@class="tc name"]/a/text()").extract()

['邱嘉臣', '刘建强', '马心航', '张克俭', '关易波', '许汉忠', '毕井双', '饶品贵', '谢泽煌', '梁慧', '袁海文', '邱嘉臣', '戚耀明', '武宇', '黄浩', '王晓勇', '于洪才', '莫名贞', '谢冰心']


'''

scrapy框架在爬虫中的应用

在上个工程项目中cd 到 spidders 目录中，此处为存放爬虫类的包

栗子2：
cd  ./stock_spider/spiders

scrapy genspider stock "pycs.greedyai.com"

stock.py

# -*- coding: utf-8 -*-
import scrapy
import re

from urllib import parse
from ..items import MySpiderItem2

class StockSpider(scrapy.Spider):
    name = 'stock'
    allowed_domains = ['pycs.greedyai.com']
    start_urls = ['http://pycs.greedyai.com']

    def parse(self, response):
        hrefs = response.xpath("//a/@href").extract()

        for href in hrefs:
            yield scrapy.Request(url= parse.urljoin(response.url, href), callback=self.parse_detail, dont_filter=True)


    def parse_detail(self,response):

        stock_item = MySpiderItem2()

        # 董事会成员信息
        stock_item["names"] = self.get_tc(response)

        # 抓取性别信息
        stock_item["sexes"] = self.get_sex(response)

        # 抓取年龄信息
        stock_item["ages"] = self.get_age(response)

        # 股票代码
        stock_item["codes"] = self.get_cod(response)

        # 职位信息
        stock_item["leaders"] = self.get_leader(response,len(stock_item["names"]))

        yield stock_item
        # 处理信息


    def get_tc(self, response):
        names = response.xpath("//*[@class="tc name"]/a/text()").extract()
        return names

    def get_sex(self, response):
        # //*[@id="ml_001"]/table/tbody/tr[1]/td[1]/div/table/thead/tr[2]/td[1]
        infos = response.xpath("//*[@class="intro"]/text()").extract()
        sex_list = []
        for info in infos:
            try:
                sex = re.findall("[男|女]", info)[0]
                sex_list.append(sex)
            except(IndexError):
                continue

        return sex_list

    def get_age(self, response):
        infos = response.xpath("//*[@class="intro"]/text()").extract()
        age_list = []
        for info in infos:
            try:
                age = re.findall("d+", info)[0]
                age_list.append(age)
            except(IndexError):
                continue

        return age_list

    def get_cod(self, response):
        codes = response.xpath("/html/body/div[3]/div[1]/div[2]/div[1]/h1/a/@title").extract()
        code_list = []
        for info in codes:
            code = re.findall("d+", info)[0]
            code_list.append(code)

        return code_list

    def get_leader(self, response, length):
        tc_leaders = response.xpath("//*[@class="tl"]/text()").extract()
        tc_leaders = tc_leaders[0 : length]
        return tc_leaders

items.py：

import scrapy


class MySpiderItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    pass

class MySpiderItem2(scrapy.Item):
    names = scrapy.Field()
    sexes = scrapy.Field()
    ages = scrapy.Field()
    codes = scrapy.Field()
    leaders = scrapy.Field()

说明：

items.py中的MySpiderItem2 类中的字段用于存储在stock.py的StockSpider类中爬到的字段，交给pipelines.py中的MySpiderPipeline2处理，
需要到settings.py中设置

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

# Scrapy settings for my_spider 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 = 'my_spider'

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


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

# Obey robots.txt rules
ROBOTSTXT_OBEY = True

# 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 = 3
# 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 = {
#    'my_spider.middlewares.MySpiderSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'my_spider.middlewares.MySpiderDownloaderMiddleware': 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 = {
   'my_spider.pipelines.MySpiderPipeline': 300,
   'my_spider.pipelines.MySpiderPipeline2': 1,
}

# 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'

pipelines.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

class MySpiderPipeline(object):
    def process_item(self, item, spider):
        return item



class MySpiderPipeline2(object):

    '''
    # 类被加载时需要创建一个文件

    # 判断文件是否为空
    为空写：高管姓名，性别，年龄，股票代码，职位
    不为空：追加文件写数据

    '''

    def __init__(self):

        self.file = open("executive_prep.csv","a+")


    def process_item(self, item, spider):

        if os.path.getsize("executive_prep.csv"):
            # 写数据
            self.write_content(item)
        else:
            self.file.write("高管姓名，性别，年龄，股票代码，职位
")

        self.file.flush()
        return item


    def write_content(self,item):

        names = item["names"]
        sexes = item["sexes"]
        ages = item["ages"]
        codes = item["codes"]
        leaders = item["leaders"]

        # print(names + sexes + ages + codes + leaders)

        line = ""
        for i in range(len(names)):
            line = names[i] + "," + sexes[i] + "," + ages[i] + "," + codes[0] + "," + leaders[i] + "
"
            self.file.write(line)

文件可以在同级目录中查看