python之scrapy爬取jingdong招聘信息到mysql数据库

1、创建工程

scrapy startproject jd

2、创建项目

scrapy genspider jingdong

3、安装pymysql

pip install pymysql

4、settings.py文件，主要是全局字段的定义，包括数据库信息

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

# Scrapy settings for jd 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 = 'jd'

SPIDER_MODULES = ['jd.spiders']

NEWSPIDER_MODULE = 'jd.spiders'

LOG_LEVEL="WARNING"

LOG_FILE="./jingdong1.log"

# Crawl responsibly by identifying yourself (and your website) on the user-agent

#USER_AGENT = 'jd (+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 = {

#    'jd.middlewares.JdSpiderMiddleware': 543,

#}

# Enable or disable downloader middlewares

# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html

#DOWNLOADER_MIDDLEWARES = {

#    'jd.middlewares.JdDownloaderMiddleware': 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 = {

   'jd.pipelines.JdPipeline': 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'

# 连接数据MySQL

# 数据库地址

MYSQL_HOST = 'localhost'

# 数据库用户名:

MYSQL_USER = 'root'

# 数据库密码

MYSQL_PASSWORD = 'yang156122'

# 数据库端口

MYSQL_PORT = 3306

# 数据库名称

MYSQL_DBNAME = 'test'

# 数据库编码

MYSQL_CHARSET = 'utf8'

5、items.py文件定义数据库字段

# -*- 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 JdItem(scrapy.Item):

    # define the fields for your item here like:

    # name = scrapy.Field()

    appTime = scrapy.Field()

    applicantErp = scrapy.Field()

    formatPublishTime = scrapy.Field()

    jobType = scrapy.Field()

    positionName = scrapy.Field()

    positionNameOpen = scrapy.Field()

    publishTime = scrapy.Field()

    qualification= scrapy.Field()

    pass

6、jingdong.py文件主要是爬取所需数据

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

import scrapy

import logging

import json

logger = logging.getLogger(__name__)

class JingdongSpider(scrapy.Spider):

    name = 'jingdong'

    allowed_domains = ['zhaopin.jd.com']

    start_urls = ['http://zhaopin.jd.com/web/job/job_list?page=1']

    pageNum = 1

    def parse(self, response):

        content  = response.body.decode()

        content = json.loads(content)

        ##########去除列表中字典集中的空值###########

        for i in range(len(content)):

            #list(content[i].keys()获取当前字典中的key

            # for key in list(content[i].keys()): #content[i]为字典

            #     if not content[i].get(key):#content[i].get(key)根据key获取value

            #         del content[i][key] #删除空值字典

            yield content[i]

        # for i in range(len(content)):

        #     logging.warning(content[i])

        self.pageNum = self.pageNum+1

        if self.pageNum<=355:

            next_url = "http://zhaopin.jd.com/web/job/job_list?page="+str(self.pageNum)

            yield scrapy.Request(

                next_url,

                callback=self.parse

            )

        pass

7、pipelines.py文件主要是对爬取的数据进行清洗和处理，包括数据的入库操作

　　这里和tencent相比，主要是增加了时间处理

# -*- 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 logging

from pymysql import cursors

from twisted.enterprise import adbapi

import time

import copy

class JdPipeline(object):

    # 函数初始化

    def __init__(self, db_pool):

        self.db_pool = db_pool

    @classmethod

    def from_settings(cls, settings):

        """类方法，只加载一次，数据库初始化"""

        db_params = dict(

            host=settings['MYSQL_HOST'],

            user=settings['MYSQL_USER'],

            password=settings['MYSQL_PASSWORD'],

            port=settings['MYSQL_PORT'],

            database=settings['MYSQL_DBNAME'],

            charset=settings['MYSQL_CHARSET'],

            use_unicode=True,

            # 设置游标类型

            cursorclass=cursors.DictCursor

        )

        # 创建连接池

        db_pool = adbapi.ConnectionPool('pymysql', **db_params)

        # 返回一个pipeline对象

        return cls(db_pool)

    def process_item(self, item, spider):

        myItem = {}

        myItem["appTime"]=item["appTime"]

        myItem["applicantErp"] = item["applicantErp"]

        myItem["formatPublishTime"] = item["formatPublishTime"]

        myItem["jobType"] = item["jobType"]

        myItem["positionName"] = item["positionName"]

        #时间转换

        publishTime = item["publishTime"]

        publishTime = time.localtime(int(str(publishTime)[:10])) #时间格式转换

        myItem["publishTime"] = time.strftime("%Y-%m-%d %H:%M:%S", publishTime)

        myItem["positionNameOpen"]=item["positionNameOpen"]

        myItem["qualification"] = item["qualification"]

        logging.warning(item)

        # 对象拷贝，深拷贝  --- 这里是解决数据重复问题！！！

        asynItem = copy.deepcopy(myItem)

        # 把要执行的sql放入连接池

        query = self.db_pool.runInteraction(self.insert_into, asynItem)

        # 如果sql执行发送错误,自动回调addErrBack()函数

        query.addErrback(self.handle_error, myItem, spider)

        return myItem

        # 处理sql函数

    def insert_into(self, cursor, item):

        # 创建sql语句

        sql = "INSERT INTO jingdong (appTime,applicantErp,formatPublishTime,jobType,positionName,publishTime,positionNameOpen,qualification) " \

              "VALUES ('{}','{}','{}','{}','{}','{}','{}','{}')".format(

            item['appTime'], item['applicantErp'],item['formatPublishTime'] , item['jobType'],

            item['positionName'], item['publishTime'], item['positionNameOpen'],item['qualification'])

        # 执行sql语句

        cursor.execute(sql)

        # 错误函数

    def handle_error(self, failure, item, spider):

        # #输出错误信息

        print("failure", failure)

完美收官！！！

巴特西

python之scrapy爬取jingdong招聘信息到mysql数据库

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