CSS 选择器 HTML 与 Scrapy Python
CSS Selector HTML with Scrapy Python
我正在尝试制作一个网络爬虫,以作为个人项目从 Yahoo Finance 中提取一些信息。但是,在雅虎财经的分析页面上,我无法提取特定的值。 HTML 对我来说似乎很复杂,我可以得到一些指导吗?
class yhcrawler(scrapy.Spider):
name = 'yahoo'
start_urls = [f'https://ca.finance.yahoo.com/quote/{t}/analysis?p={t}' for t in tkrs]
def parse(self, response):
filename = 'stock_growths.csv'
l = response.css('div#YDC-Col1>div>div>div>div>div>section>table>tbody>tr>td#431::text').extract()
print(l)
这就是我正在尝试的
l = response.css('div#YDC-Col1>div>div>div>div>div>section>table>tbody>tr>td#431::text').extract()
我得到的结果是空的
2021-04-18 15:12:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://ca.finance.yahoo.com/quote/M/analysis?p=M> (referer: None)
[]
我试图获得的值在突出显示的行上,-11.82%
试试这个:
class YahoofinanceSpider(scrapy.Spider):
name = 'yahoofinance'
start_urls = ['https://ca.finance.yahoo.com/quote/aapl/analysis?p=aapl']
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.150 Safari/537.36'
}
def start_requests(self):
for start_url in self.start_urls:
yield scrapy.Request(start_url,headers=self.headers)
def parse(self, response):
item = response.xpath("//td[./span][contains(.,'Next 5 Years')]/following-sibling::td/text()").getall()
yield {"item":item}
我正在尝试制作一个网络爬虫,以作为个人项目从 Yahoo Finance 中提取一些信息。但是,在雅虎财经的分析页面上,我无法提取特定的值。 HTML 对我来说似乎很复杂,我可以得到一些指导吗?
class yhcrawler(scrapy.Spider):
name = 'yahoo'
start_urls = [f'https://ca.finance.yahoo.com/quote/{t}/analysis?p={t}' for t in tkrs]
def parse(self, response):
filename = 'stock_growths.csv'
l = response.css('div#YDC-Col1>div>div>div>div>div>section>table>tbody>tr>td#431::text').extract()
print(l)
这就是我正在尝试的
l = response.css('div#YDC-Col1>div>div>div>div>div>section>table>tbody>tr>td#431::text').extract()
我得到的结果是空的
2021-04-18 15:12:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://ca.finance.yahoo.com/quote/M/analysis?p=M> (referer: None)
[]
我试图获得的值在突出显示的行上,-11.82%
试试这个:
class YahoofinanceSpider(scrapy.Spider):
name = 'yahoofinance'
start_urls = ['https://ca.finance.yahoo.com/quote/aapl/analysis?p=aapl']
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.150 Safari/537.36'
}
def start_requests(self):
for start_url in self.start_urls:
yield scrapy.Request(start_url,headers=self.headers)
def parse(self, response):
item = response.xpath("//td[./span][contains(.,'Next 5 Years')]/following-sibling::td/text()").getall()
yield {"item":item}