我正在编写一个网络抓取工具来获取一组链接
从网站（位于tree.xpath（'// div [@ class =“work_area_content”] / a / @ href'）
返回由leafs父级划分的所有叶子的Title and Url。我有两个刮刀：一个在python中，另一个在Scrapy中用于Python。 Scrapy Request方法中callbacks的目的是什么？信息应该是multidimensional or single dimension list（我相信是多维的，但会增强复杂性）？以下哪个代码更好？如果刮刀代码更好，我如何将python代码迁移到Scrapy代码？
从我对回调的理解是，它将函数的参数传递给另一个函数;但是，如果回调引用自身，则数据会被覆盖并因此丢失，并且您无法返回到根数据。它是否正确？
蟒：
url_storage = [ [ [ [] ] ] ]
page = requests.get('http://1.1.1.1:1234/TestSuites')
tree = html.fromstring(page.content)
urls = tree.xpath('//div[@class="work_area_content"]/a/@href').extract()
i = 0
j = 0
k = 0
for i, url in enumerate(urls):
absolute_url = "".join(['http://1.1.1.1:1234/', url])
url_storage[i][j][k].append(absolute_url)
print(url_storage)
#url_storage.insert(i, absolute_url)
page = requests.get(url_storage[i][j][k])
tree2 = html.fromstring(page.content)
urls2 = tree2.xpath('//div[@class="work_area_content"]/a/@href').extract()
for j, url2 in enumerate(urls2):
absolute_url = "".join(['http://1.1.1.1:1234/', url2])
url_storage[i][j][k].append(absolute_url)
page = requests.get(url_storage[i][j][k])
tree3 = html.fromstring(page.content)
urls3 = tree3.xpath('//div[@class="work_area_content"]/a/@href').extract()
for k, url3 in enumerate(urls3):
absolute_url = "".join(['http://1.1.1.1:1234/', url3])
url_storage[i][j][k].append(absolute_url)
page = requests.get(url_storage[i][j][k])
tree4 = html.fromstring(page.content)
urls3 = tree4.xpath('//div[@class="work_area_content"]/a/@href').extract()
title = tree4.xpath('//span[@class="page_title"]/text()').extract()
yield Request(url_storage[i][j][k], callback=self.end_page_parse_TS, meta={"Title": title, "URL": urls3 })
#yield Request(absolute_url, callback=self.end_page_parse_TC, meta={"Title": title, "URL": urls3 })
def end_page_parse_TS(self, response):
print(response.body)
url = response.meta.get('URL')
title = response.meta.get('Title')
yield{'URL': url, 'Title': title}
def end_page_parse_TC(self, response):
url = response.meta.get('URL')
title = response.meta.get('Title')
description = response.meta.get('Description')
description = response.xpath('//table[@class="wiki_table]/tbody[contains(/td/text(), "description")/parent').extract()
yield{'URL': url, 'Title': title, 'Description':description}
Scrapy：
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractor import LinkExtractor
from scrapy.spiders import Rule, CrawlSpider
from datablogger_scraper.items import DatabloggerScraperItem
class DatabloggerSpider(CrawlSpider):
# The name of the spider
name = "datablogger"
# The domains that are allowed (links to other domains are skipped)
allowed_domains = ['http://1.1.1.1:1234/']
# The URLs to start with
start_urls = ['http://1.1.1.1:1234/TestSuites']
# This spider has one rule: extract all (unique and canonicalized) links, follow them and parse them using the parse_items method
rules = [
Rule(
LinkExtractor(
canonicalize=True,
unique=True
),
follow=True,
callback="parse_items"
)
]
# Method which starts the requests by visiting all URLs specified in start_urls
def start_requests(self):
for url in self.start_urls:
yield scrapy.Request(url, callback=self.parse, dont_filter=True)
# Method for parsing items
def parse_items(self, response):
# The list of items that are found on the particular page
items = []
# Only extract canonicalized and unique links (with respect to the current page)
links = LinkExtractor(canonicalize=True, unique=True).extract_links(response)
# Now go through all the found links
item = DatabloggerScraperItem()
item['url_from'] = response.url
for link in links:
item['url_to'] = link.url
items.append(item)
# Return all the found items
return items