1、创建Scrapy项目
scrapy startproject ExGrain2.进入项目目录，使用命令genspider创建Spider
scrapy genspider exgrain ex-grain.cn3、定义要抓取的数据（处理items.py文件）
# -*- coding: utf-8 -*-
import scrapy
class ExgrainItem(scrapy.Item):
# 文章的目录
news_path = scrapy.Field()
# 文章的分类
news_cate = scrapy.Field()
# 文章标题
news_title = scrapy.Field()
# 文章发布日期
news_date = scrapy.Field()
# 文章来源
news_source = scrapy.Field()
# 文章导读
news_guide = scrapy.Field()
# 文章内容
news_content = scrapy.Field()
# 文章链接
news_url = scrapy.Field()4、编写提取item数据的Spider（在spiders文件夹下：exgrain.py）
# -*- coding: utf-8 -*-
# 爬取中国谷物网玉米、小麦、水稻信息数据到本地为网页形式和mysql数据库中，偶尔出现抓取数据不准确的情况
import scrapy
from ExGrain.items import ExgrainItem
import re
import os
import requests
from bs4 import BeautifulSoup
import time
class ExgrainSpider(scrapy.Spider):
name = 'exgrain'
allowed_domains = ['ex-grain.cn']
# 玉米、小麦、稻米信息
start_urls = ['http://www.ex-grain.cn/xxfb/list.htm?type=010301','http://www.ex-grain.cn/xxfb/list.htm?type=010302',
'http://www.ex-grain.cn/xxfb/list.htm?type=010201']
url = "http://www.ex-grain.cn"
def parse(self, response):
items = []
# 获取下一页
next_url = response.xpath('//tr/td[@class="grayr"]/a/@href').extract()
news_url = response.xpath('//tr/td/a[@class="new List"]/@href').extract()
for i in range(len(news_url)):
item = ExgrainItem()
item['news_url'] = self.url + news_url[i]
items.append(item)
for item in items:
time.sleep(2)
yield scrapy.Request(url=item['news_url'], meta={'meta_1': item}, callback=self.parse_news)
# 处理下一页
for url in next_url:
full_url = self.url + url
yield scrapy.Request(url=full_url, callback=self.parse)
def parse_news(self, response):
item = ExgrainItem()
# 提取每次Response的meta数据
meta_1 = response.meta['meta_1']
# 获取文章标题,有空格
news_title = response.xpath('//tr/td[@class="h13"]/span/text()').extract()[0].replace(" ", "")
# print("news_title_1",news_title)
item['news_title'] = news_title
# 获取文章来源,需要处理数据:发布时间：2018-07-18 10:54:46 |来源： |作者：
source_list = response.xpath('//tr[2]/td[@class="h3"]/text()').extract()[0]
# 获取来源后的字段
source = source_list.split("|")[1][3:].strip()
if source == "":
item["news_source"] = "中国谷物网"
else:
item["news_source"] = source
# 获取发布时间：2018-07-18
news_date = source_list.split("：")[1].split(" ")[0]
html = requests.get(meta_1['news_url'])
# 正则匹配文章内容
patt = re.compile(r'<td style="width:890px;display:block;word-break:(.*) align="left">(.*)')
# 匹配结果
result = patt.search(html.text)
# 获取文章内容
news_content = result.group(2)
# 将文字内容结果字体改变成微软雅黑
item['news_content'] = news_content.replace('宋体', '微软雅黑').replace('仿宋','微软雅黑').replace('Courier New','微软雅黑')
# 获取文章导读,只获取文章内容的一部分
soup = BeautifulSoup(html.text, "lxml")
content_list = []
for i in soup.select("p"):
content_list.append(i.get_text())
# 将列表连接起来并去掉首尾空格
news_guide_list = "".join(content_list).replace(" ", "")
# 如果文章内容是以"<p> </p><table"开头的，文章可能是表格，导读就是文章标题
if news_content[:19] == "<p> </p><table":
news_guide = news_title
else:
if len(news_guide_list[:70]) != 0:
news_guide = news_guide_list[:70].replace("\xa0", "") + "......"
else:
news_guide = news_guide_list.replace("\xa0", "")
item['news_guide'] = news_guide
item['news_date'] = news_date
# 判断属于哪个类目
# 小麦类目
wheat_news_url = "http://www.ex-grain.cn/island/FX_010302"
wheat_if_belong = meta_1['news_url'].startswith(wheat_news_url)
# 玉米类目
corn_news_url = "http://www.ex-grain.cn/island/FX_010301"
corn_if_belong = meta_1['news_url'].startswith(corn_news_url)
# 水稻类目
rice_news_url = "http://www.ex-grain.cn/island/FX_010201"
rice_if_belong = meta_1['news_url'].startswith(rice_news_url)
if wheat_if_belong:
item['news_cate'] = '小麦'
news_path = "./Data/小麦/" + news_date + "/" + news_title
# 如果目录不存在则创建
if (not os.path.exists(news_path)):
os.makedirs(news_path)
item['news_path'] = news_path
print("处理数据:%s" % (news_path[7:]))
elif corn_if_belong:
item['news_cate'] = '玉米'
news_path = "./Data/玉米/" + news_date + "/" + news_title
# 如果目录不存在则创建
if (not os.path.exists(news_path)):
os.makedirs(news_path)
item['news_path'] = news_path
print("处理数据:%s" % (news_path[7:]))
elif rice_if_belong:
item['news_cate'] = '水稻'
news_path = "./Data/水稻/" + news_date + "/" + news_title
# 如果目录不存在则创建
if (not os.path.exists(news_path)):
os.makedirs(news_path)
item['news_path'] = news_path
print("处理数据:%s" % (news_path[7:]))
item['news_url'] = meta_1['news_url']
yield item
5.处理pipelines管道文件保存数据，可将结果保存到文件中（pipelines.py）
# -*- coding: utf-8 -*-
import json
# 转码操作，继承json.JSONEncoder的子类
class MyEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, bytes):
return str(o, encoding='utf-8')
return json.JSONEncoder.default(self, o)
class ExgrainPipeline(object):
def process_item(self, item, spider):
self.fail_count = 0
try:
file_name = item['news_title']
with open(item['news_path'] + "/" + file_name + ".html", "w+")as f:
f.write(item['news_content'])
except:
self.fail_count += 1
print("%s文件保存失败，请注意！"%item['news_title'])
self.file_name_fail = item['news_title']
with open(item['news_path'] + "/" + "[失败！]/"+self.file_name_fail + ".html", "w+")as f:
f.write("<p>写入失败！</p>")
return item
def close_spider(self, spider):
if self.fail_count != 0:
print("%s文件保存失败了..."%self.file_name_fail)
print("数据保存本地处理完毕，谢谢使用！")6.增加ExGrainpipelines.py文件，同时将数据保存到mysql数据库中
# -*- coding: utf-8 -*-
import json
import pymysql
# 转码操作，继承json.JSONEncoder的子类
class MyEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, bytes):
return str(o, encoding='utf-8')
return json.JSONEncoder.default(self, o)
class DBPipeline(object):
def __init__(self):
# 连接数据库
self.connect = pymysql.connect(
host='localhost',
port=3306,
db='python3',
user='root',
passwd='123456',
charset='utf8',
use_unicode=True)
# 通过cursor执行增删查改
self.cursor = self.connect.cursor()
# 来个计数器，统计写入了多少
self.count = 0
# @classmethod
# def from_settings(cls, settings):
# dbargs = dict(
# host=settings['MYSQL_HOST'],
# db=settings['MYSQL_DBNAME'],
# user=settings['MYSQL_USER'],
# passwd=settings['MYSQL_PASSWD'],
# port=settings['MYSQL_PORT'],
# charset='utf8',
# cursorclass=pymysql.cursors.DictCursor,
# use_unicode=True,
# )
# dbpool = adbapi.ConnectionPool('pymysql', **dbargs)
# return cls(dbpool)
# def __init__(self,dbpool):
# self.dbpool=dbpool
def process_item(self, item, spider):
try:
# 查重处理
self.cursor.execute(
"""SELECT news_url FROM exgrain WHERE news_url = %s""",item['news_url'])
# 是否有重复数据
repetition = self.cursor.fetchone()
# 重复
if repetition:
print("数据库已有此条数据，不再添加",repetition[0])
else:
print("写入数据库中...")
# 插入数据
self.cursor.execute(
"""INSERT INTO exgrain(news_cate,news_title, news_date, news_source, news_guide ,
news_content, news_url)VALUES(%s,%s, %s, %s, %s, %s, %s)""",
(item['news_cate'],item['news_title'],item['news_date'],item['news_source'],
item['news_guide'],item['news_content'],item['news_url']))
self.count += 1
# 提交sql语句
self.connect.commit()
except Exception as error:
# 出现错误时打印错误日志
log(error)
return item
def close_spider(self, spider):
self.cursor.close()
self.connect.close()
print("数据库处理完毕，本次共计增加%d条数据，谢谢使用！"%self.count)7.配置settings文件（settings.py，这里通过设置调用数据库失败，暂时未解决）
# Obey robots.txt rules，具体含义参照：https://blog.csdn.net/z564359805/article/details/80691677
ROBOTSTXT_OBEY = False
# # 将数据保存在mysql
# MYSQL_HOST = 'localhost'
# MYSQL_DBNAME = 'python3'
# MYSQL_USER = 'root'
# MYSQL_PASSWD = '123456'
# MYSQL_PORT = 3306
# 下载延迟
DOWNLOAD_DELAY = 4
# Override the default request headers:添加User-Agent信息
DEFAULT_REQUEST_HEADERS = {
'User-Agent': 'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0);',
# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
# 'Accept-Language': 'en',
}
# Configure item pipelines去掉下面注释，打开管道文件
ITEM_PIPELINES = {
'ExGrain.pipelines.ExgrainPipeline': 100,
'ExGrain.ExGrainpipelines.DBPipeline': 300,
}
# 还可以将日志存到本地文件中（可选添加设置）
LOG_FILE = "exgrain.log"
LOG_LEVEL = "DEBUG"
# 包含打印信息也一起写进日志里
LOG_STDOUT = True8.记得提前打开mysql数据库，并且建立好相应的表
# 创建谷物网文章的数据库表
CREATE TABLE exgrain(id int PRIMARY KEY auto_increment not null,news_cate varchar(2),news_title varchar(100),news_date date,
news_source varchar(30),news_guide VARCHAR(150),news_content MEDIUMTEXT,news_url VARCHAR(90));9.以上设置完毕，进行爬取：执行项目命令crawl，启动Spider：
scrapy crawl exgrainPS:（偶尔出现抓取文章标题或者文章内容不准确的情况，一直未解决，网站本身刷新的时候数据会改变，不知道怎么解决？）