目录
- 需求
- 1. Scrapy项目创建
- 2. 全局配置 settings.py
- 3. 爬虫程序.py
- 4. 数据结构 items.py
- 5. 管道 pipelines.py
- 6. 程序执行 start.py
需求
通过python,Scrapy框架，爬取古诗文网上的诗词数据，具体包括诗词的标题信息，作者，朝代，诗词内容，及译文。爬取过程需要逐页爬取，共4页。第一页的url为（https://www.gushiwen.cn/default_1.aspx）。
1. Scrapy项目创建
首先创建Scrapy项目及爬虫程序
在目标目录下，创建一个名为prose的项目：
scrapy startproject prose
进入项目目录下，然后创建一个名为gs的爬虫程序，爬取范围为 gushiwen.cn
cd prose scrapy genspider gs gushiwen.cn
2. 全局配置 settings.py
对配置文件settings.py做如下编辑：
①选择不遵守robots协议
②下载间隙设置为1
③并添加请求头，启用管道
④此外设置打印等级：LOG_LEVEL=“WARNING”
具体如下：
# Scrapy settings for prose project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# https://docs.scrapy.org/en/latest/topics/settings.html
# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
BOT_NAME = \'prose\'
SPIDER_MODULES = [\'prose.spiders\']
NEWSPIDER_MODULE = \'prose.spiders\'
LOG_LEVEL = \"WARNING\"
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = \'prose (+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://docs.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 = {
\'user-agent\': \'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36\',
\'Accept\': \'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\',
\'Accept-Language\': \'en\',
}
# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
# \'prose.middlewares.ProseSpiderMiddleware\': 543,
#}
# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
# \'prose.middlewares.ProseDownloaderMiddleware\': 543,
#}
# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
# \'scrapy.extensions.telnet.TelnetConsole\': None,
#}
# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
\'prose.pipelines.ProsePipeline\': 300,
}
# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.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://docs.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\'
3. 爬虫程序.py
首先是进行页面分析，这里不再赘述该过程。
这部分代码，也即需要编辑的核心部分。
首先是要把初始URL加以修改，修改为要爬取的界面的第一页，而非古诗文网的首页。
需求：我们要爬取的内容包括：诗词的标题信息，作者，朝代，诗词内容，及译文。爬取过程需要逐页爬取。
其中，标题信息，作者，朝代，诗词内容，及译文都存在于同一个<div>标签中。
为了体现两种不同的操作方式，
标题信息，作者，朝代，诗词内容 四项，我们使用一种方法获取。并在该for循环中使用到一个异常处理语句（try…except…）来避免取到空值时使用索引导致的报错；
对于译文，我们额外定义一个parse_detail函数，并在scrapy.Request()中传入其，来获取。
关于翻页，我们的思路是：遍历获取完每一页需要的数据后（即一大轮循环结束后），从当前页面上获取下一页的链接，然后判断获取到的链接是否为空。如若不为空则表示获取到了，则再一次使用scrapy.Requests()方法，传入该链接，并再次调用parse函数。如果为空，则表明这已经是最后一页了，程序就会在此处结束。
具体代码如下：
import scrapy
from prose.items import ProseItem
class GsSpider(scrapy.Spider):
name = \'gs\'
allowed_domains = [\'gushiwen.cn\']
start_urls = [\'https://www.gushiwen.cn/default_1.aspx\']
# 解析列表页面
def parse(self, response):
# 一个class=\"sons\"对应的是一首诗
div_list = response.xpath(\'//div[@class=\"left\"]/div[@class=\"sons\"]\')
for div in div_list:
try:
# 提取诗词标题信息
title = div.xpath(\'.//b/text()\').get()
# 提取作者和朝代
source = div.xpath(\'.//p[@class=\"source\"]/a/text()\').getall()
# 作者
# replace
author = source[0]
# 朝代
dynasty = source[1]
content_list = div.xpath(\'.//div[@class=\"contson\"]//text()\').getall()
content_plus = \'\'.join(content_list).strip()
# 拿到诗词详情页面的url
detail_url = div.xpath(\'.//p/a/@href\').get()
item = ProseItem(title=title, author=author, dynasty=dynasty, content_plus=content_plus, detail_url=detail_url)
# print(item)
yield scrapy.Request(
url=detail_url,
callback=self.parse_detail,
meta={\'prose_item\': item}
)
except:
pass
next_url = response.xpath(\'//a[@id=\"amore\"]/@href\').get()
if next_url:
print(next_url)
yield scrapy.Request(
url=next_url,
callback=self.parse
)
# 用于解析详情页面
def parse_detail(self, response):
item = response.meta.get(\'prose_item\')
translation = response.xpath(\'//div[@class=\"sons\"]/div[@class=\"contyishang\"]/p//text()\').getall()
item[\'translation\'] = \'\'.join(translation).strip()
# print(item)
yield item
pass
4. 数据结构 items.py
在这里定义了ProseItem类，以便在上边的爬虫程序中调用。（此外要注意的是，爬虫程序中导入了该模块，有必要时需要将合适的文件夹标记为根目录。）
import scrapy
class ProseItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
# 标题
title = scrapy.Field()
# 作者
author = scrapy.Field()
# 朝代
dynasty = scrapy.Field()
# 诗词内容
content_plus = scrapy.Field()
# 详情页面的url
detail_url = scrapy.Field()
# 译文
translation = scrapy.Field()
pass
5. 管道 pipelines.py
管道，在这里编辑数据存储的过程。
from itemadapter import ItemAdapter
import json
class ProsePipeline:
def __init__(self):
self.f = open(\'gs.txt\', \'w\', encoding=\'utf-8\')
def process_item(self, item, spider):
# 将item先转化为字典， 再转化为 json类型的字符串
item_json = json.dumps(dict(item), ensure_ascii=False)
self.f.write(item_json + \'\\n\')
return item
def close_spider(self, spider):
self.f.close()
6. 程序执行 start.py
定义一个执行命令的程序。
from scrapy import cmdline cmdline.execute(\'scrapy crawl gs\'.split())
程序执行效果如下：
我们需要的数据，被保存在了一个名为gs.txt的文本文件中了。
以上就是Python Scrapy实战之古诗文网的爬取的详细内容，更多关于Python Scrapy爬取古诗文网的资料请关注其它相关文章！
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