我知道你说过你不能使用lxml.html。但这里是如何使用该库来做到这一点,因为它是非常好的库。因此,为了完整起见,我提供了使用它的代码,因为我不再使用 BeautifulSoup ——它无人维护、速度慢且 API 丑陋。
以下代码解析页面并将结果写入 csv 文件。
import lxml.html
import csv
doc = lxml.html.parse('http://finance.yahoo.com/q/os?s=lly&m=2011-04-15')
# find the first table contaning any tr with a td with class yfnc_tabledata1
table = doc.xpath("//table[tr/td[@class='yfnc_tabledata1']]")[0]
with open('results.csv', 'wb') as f:
cf = csv.writer(f)
# find all trs inside that table:
for tr in table.xpath('./tr'):
# add the text of all tds inside each tr to a list
row = [td.text_content().strip() for td in tr.xpath('./td')]
# write the list to the csv file:
cf.writerow(row)
就是这样! lxml.html 就是这么简单又好听!!可惜不能用。
以下是生成的results.csv 文件中的一些行:
LLY110416C00017500,N/A,0.00,17.05,18.45,0,0,17.50,LLY110416P00017500,0.01,0.00,N/A,0.03,0,182
LLY110416C00020000,15.70,0.00,14.55,15.85,0,0,20.00,LLY110416P00020000,0.06,0.00,N/A,0.03,0,439
LLY110416C00022500,N/A,0.00,12.15,12.80,0,0,22.50,LLY110416P00022500,0.01,0.00,N/A,0.03,2,50