我对Scrapy库很陌生，我在为蜘蛛奋斗。我正在尝试从此网站https://murderpedia.org/male.A/index.A.htm抓取数据
我想做的是页面上的每个链接，我想跟随该链接并刮擦图像以及文本[第3-11行]。
在这里的任何帮助将不胜感激。
这是我的代码：
from scrapy.spiders import Request
from scrapy.linkextractors import LinkExtractor
from scrapy.http import HtmlResponse
import re
BASE_URL = 'http://murderpedia.org/'
PROTOCOL = 'https:'
class SerialKillerItem(scrapy.Item):
name = scrapy.Field()
bio = scrapy.Field()
images = scrapy.Field()
link = scrapy.Field()
image_urls = scrapy.Field()
bio_image = scrapy.Field()
classification = scrapy.Field()
characteristics = scrapy.Field()
number_of_victims = scrapy.Field()
date_of_murders = scrapy.Field()
date_of_birth = scrapy.Field()
victims_profile = scrapy.Field()
method_of_murder = scrapy.Field()
location = scrapy.Field()
status = scrapy.Field()
class SerialKillerBio(scrapy.Spider):
name = 'serial_killer_bio'
start_urls = ['http://murderpedia.org/male.A/index.A.htm']
def parse(self, response):
images = response.css("#AutoNumber3 > tbody > tr:nth-child(2)
> td > font:nth-child(1) > div > center > table:nth-child(2) >
tbody > tr > td > font > div > table > tbody > tr > td:nth-
child(2) > p > img::attr(src)").extract_first()
for row in response.css('#table4 > tbody'):
text = {
'Classification' : row.css('tr[3]::text').extract_first(),
'Characteristics': row.css('tr[4]::text').extract_first(),
'Number of
Victims':row.css('tr[5]::text').extract_first(),
'Date of Murders': row.css('tr[6]::text').extract_first(),
'Date of Birth': row.xpath('tr[7]::text').extract_first(),
'Victims Profile': row.xpath('tr[8]
::text').extract_first(),
'Method of Murder': row.xpath('tr[9]
::text').extract_first(),
'Location' : row.css('tr[10] ::text').extract_first(),
'Status' : row.css('tr[11] ::text').extract_first()}
text2 = ''.join(text)
print(text2)
if images:
yield {'text2':
SerialKillerItem(classification=name['Classification'],
characteristics=name['Characteristics'],
number_of_victims=name['Number of
Victims'],
date_of_murders=name['Date of Murders'],
date_of_birth=name['Date of Birth'],
victims_profile=name['Victims Profile'],
method_of_murder=name['Method of Murder'],
location=name['Location'],
status=name['Status']),
'image_urls': [PROTOCOL+ images][:10]}
else:
yield {'text2':
SerialKillerItem(classification=name['Classification'],
characteristics=name['Characteristics'],
number_of_victims=name['Number of
Victims'],
date_of_murders=name['Date of Murders'],
date_of_birth=name['Date of Birth'],
victims_profile=name['Victims Profile'],
method_of_murder=name['Method of Murder'],
location=name['Location'],
status=name['Status']), 'image_urls':[]}
for next_page in response.css('#table2 > tbody >
tr:nth-child(2) > td > font:nth-child(1) > div > table
> tbody > tr > td:nth-child(2) > p > font > font >
a::attr(href)').extract():
print(BASE_URL + next_page)
yield Request(BASE_URL + next_page, \
callback=self.parse)
这是抓取日志：
2018-10-24 21:11:04 [scrapy.utils.log] INFO: Scrapy 1.5.1 started
(bot: serial_killers)
2018-10-24 21:11:04 [scrapy.utils.log] INFO: Versions: lxml 4.2.3.0,
libxml2 2.9.8, cssselect 1.0.3, parsel 1.5.0, w3lib 1.19.0, Twisted
18.9.0, Python 3.6.5 (default, Apr 25 2018, 14:22:56) - [GCC 4.2.1
Compatible Apple LLVM 8.0.0 (clang-800.0.42.1)], pyOpenSSL 18.0.0
(OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Darwin-
15.2.0-x86_64-i386-64bit
2018-10-24 21:12:19 [scrapy.utils.log] INFO: Scrapy 1.5.1 started
(bot: serial_killers)
2018-10-24 21:12:19 [scrapy.utils.log] INFO: Versions: lxml 4.2.3.0,
libxml2 2.9.8, cssselect 1.0.3, parsel 1.5.0, w3lib 1.19.0, Twisted
18.9.0, Python 3.6.5 (default, Apr 25 2018, 14:22:56) - [GCC 4.2.1
Compatible Apple LLVM 8.0.0 (clang-800.0.42.1)], pyOpenSSL 18.0.0
(OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Darwin-
15.2.0-x86_64-i386-64bit
2018-10-24 21:12:19 [scrapy.crawler] INFO: Overridden settings:
{'BOT_NAME': 'serial_killers', 'FEED_EXPORT_ENCODING': 'utf-8',
'HTTPCACHE_ENABLED': True, 'LOG_FILE': 'output.log',
'NEWSPIDER_MODULE': 'serial_killers.spiders', 'ROBOTSTXT_OBEY': True,
'SPIDER_MODULES': ['serial_killers.spiders']}
2018-10-24 21:12:19 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.corestats.CoreStats',
'scrapy.extensions.telnet.TelnetConsole',
'scrapy.extensions.memusage.MemoryUsage',
'scrapy.extensions.logstats.LogStats']
2018-10-24 21:12:19 [scrapy.middleware] INFO: Enabled downloader
middlewares:
['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware',
'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',
'scrapy.dowladermidlewares.downloatimeout.DownloadTi\meoutMidleware'
'scrapy.downloadermiddlewares.defaltheaders.DefaultHedersMidleware',
'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',
'scrapy.downloadermiddlewares.retry.RetryMiddleware',
'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',
'scrapy.dowloadermiddlewares.httpcompression.HtpCompressionMddleware
'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',
'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',
'scrapy.downloadermiddlewares.stats.DownloaderStats',
'scrapy.downloadermiddlewares.httpcache.HttpCacheMiddleware']
2018-10-24 21:12:19 [scrapy.middleware] INFO: Enabled spider
middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
'scrapy.spidermiddlewares.offsite.OffsiteMiddleware',
'scrapy.spidermiddlewares.referer.RefererMiddleware',
'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
'scrapy.spidermiddlewares.depth.DepthMiddleware']
2018-10-24 21:12:19 [scrapy.middleware] INFO: Enabled item
pipelines:
['scrapy.pipelines.images.ImagesPipeline']
2018-10-24 21:12:19 [scrapy.core.engine] INFO: Spider opened
2018-10-24 21:12:19 [scrapy.extensions.logstats] INFO: Crawled 0
pages
(at 0 pages/min), scraped 0 items (at 0 items/min)
2018-10-24 21:12:19 [scrapy.extensions.httpcache] DEBUG: Using
filesystem
cache storage in
/Users/app_10/serial_kil
lers/.scrapy/httpcache
2018-10-24 21:12:19 [scrapy.extensions.telnet] DEBUG: Telnet console
listening on 127.0.0.1:6023
2018-10-24 21:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET
http://murderpedia.org/robots.txt> (referer: None) ['cached']
2018-10-24 21:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET
http://murderpedia.org/male.A/index.A.htm> (referer: None) ['cached']
2018-10-24 21:12:19 [scrapy.core.engine] INFO: Closing spider
(finished)
2018-10-24 21:12:19 [scrapy.statscollectors] INFO: Dumping Scrapy
stats:
{'downloader/request_bytes': 456,
'downloader/request_count': 2,
'downloader/request_method_count/GET': 2,
'downloader/response_bytes': 29306,
'downloader/response_count': 2,
'downloader/response_status_count/200': 2,
'finish_reason': 'finished',
'finish_time': datetime.datetime(2018, 10, 25, 1, 12, 19, 569830),
'httpcache/hit': 2,
'log_count/DEBUG': 4,
'log_count/INFO': 7,
'memusage/max': 47525888,
'memusage/startup': 47525888,
'response_received_count': 2,
'scheduler/dequeued': 1,
'scheduler/dequeued/memory': 1,
'scheduler/enqueued': 1,
'scheduler/enqueued/memory': 1,
'start_time': datetime.datetime(2018, 10, 25, 1, 12, 19, 415905)}
2018-10-24 21:12:19 [scrapy.core.engine] INFO: Spider closed
(finished)
答案 0 :(得分：0)
似乎您的搜寻器未正确链接。
您想要的 搜寻逻辑是：
1. Go to A listing page
2. Go to every listed person
3. Parse html of every person
现在您的代码缺少步骤2
让我们尝试一下：
class MySpider(Spider):
name = 'corn-flake-killers'
start_urls = ['http://murderpedia.org/male.A/index.A.htm']
def parse(self, response):
# find table
# we can find table by looking for text and then going up the xml tree
table= response.xpath('//td[contains(font//font/text(),"Victims")]/../..')
# find every url in the table
urls = table.xpath('//a/@href').extract()
for url in urls:
# for every url download person's page to parse_person callback
yield Request(response.urljoin(url), self.parse_person)
def parse_person(self, response):
item = {}
# parse person html here
yield item