xpath()导致内存泄漏
我发现response.xpath()方法在使用scrapy编写爬行器时泄漏内存。代码如下:xpath()导致内存泄漏,xpath,memory-leaks,scrapy,Xpath,Memory Leaks,Scrapy,我发现response.xpath()方法在使用scrapy编写爬行器时泄漏内存。代码如下: def extract_data(self, response): aomen_host_water = None aomen_pankou = None aomen_guest_water = None sb_host_water = None sb_pankou = None sb_guest_water = None # response
def extract_data(self, response):
aomen_host_water = None
aomen_pankou = None
aomen_guest_water = None
sb_host_water = None
sb_pankou = None
sb_guest_water = None
# response.xpath('//div[@id="webmain"]/table[@id="odds"]/tr')
# for tr in all_trs:
# # cname(company name)
# cname = tr.xpath('td[1]/text()').extract()
# if len(cname) == 0:
# continue
# # remove extra space and other stuff
# cname = cname[0].split(' ')[0]
# if cname == u'澳彩':
# aomen_host_water = tr.xpath('td[9]/text()').extract()
# if len(aomen_host_water) != 0:
# aomen_pankou = tr.xpath('td[10]/text()').extract()
# aomen_guest_water = tr.xpath('td[11]/text()').extract()
# else:
# aomen_host_water = tr.xpath('td[6]/text()').extract()
# aomen_pankou = tr.xpath('td[7]/text()').extract()
# aomen_guest_water = tr.xpath('td[8]/text()').extract()
# elif cname == u'SB':
# sb_host_water = tr.xpath('td[9]/text()').extract()
# if len(sb_host_water) != 0:
# sb_pankou = tr.xpath('td[10]/text()').extract()
# sb_guest_water = tr.xpath('td[11]/text()').extract()
# else:
# sb_host_water = tr.xpath('td[6]/text()').extract()
# sb_pankou = tr.xpath('td[7]/text()').extract()
# sb_guest_water = tr.xpath('td[8]/text()').extract()
# if (aomen_host_water is None) or (aomen_pankou is None) or (aomen_guest_water is None) or \
# (sb_host_water is None) or (sb_pankou is None) or (sb_guest_water is None):
# return None
# if (len(aomen_host_water) == 0) or (len(aomen_pankou) == 0) or (len(aomen_guest_water) == 0) or \
# (len(sb_host_water) == 0) or (len(sb_pankou) == 0) or (len(sb_guest_water) == 0):
# return None
# item = YPItem()
# item['aomen_host_water'] = float(aomen_host_water[0])
# item['aomen_pankou'] = aomen_pankou[0].encode('utf-8') # float(pankou.pankou2num(aomen_pankou[0]))
# item['aomen_guest_water'] = float(aomen_guest_water[0])
# item['sb_host_water'] = float(sb_host_water[0])
# item['sb_pankou'] = sb_pankou[0].encode('utf-8') # float(pankou.pankou2num(sb_pankou[0]))
# item['sb_guest_water'] = float(sb_guest_water[0])
item = YPItem()
item['aomen_host_water'] = 1.0
item['aomen_pankou'] = '111' # float(pankou.pankou2num(aomen_pankou[0]))
item['aomen_guest_water'] = 1.0
item['sb_host_water'] = 1.0
item['sb_pankou'] = '111' # float(pankou.pankou2num(sb_pankou[0]))
item['sb_guest_water'] = 1.0
return item
在这里,我对有用的语句进行了注释,并使用了伪数据,spider使用了大约45M内存,当我取消注释注释行时,spider使用了100+M内存,内存使用率不断上升。以前有人遇到过这种问题吗?您可以通过切换到
extract\u first()
而不是extract()
来减少内存使用,这样会创建不必要的列表
我还将scrapy
和lxml
升级到最新版本:
pip install --upgrade scrapy
pip install --upgrade lxml
您可以通过切换到
extract\u first()
而不是extract()
来减少内存使用,这将创建不必要的列表
我还将scrapy
和lxml
升级到最新版本:
pip install --upgrade scrapy
pip install --upgrade lxml
我试着取消注释第一行,蜘蛛的内存使用率仍然很高,而且还在上升continuously@bob当然,你看到页面了吗?是的,我看到页面并使用了prefs()和guppy的hpy.heap(),我没有看到内存泄漏。我对python不熟悉,但是,大多数变量都是本地的,并且没有交叉引用。我不知道为什么还有内存泄漏。@bob嘿,伙计,我也有同样的问题。你解决了吗?我试着取消第一行的注释,蜘蛛的内存使用率仍然很高,而且还在上升continuously@bob当然,你看到页面了吗?是的,我看到页面并使用了prefs()和guppy的hpy.heap(),我没有看到内存泄漏。我对python不熟悉,但是,大多数变量都是本地的,并且没有交叉引用。我不知道为什么还有内存泄漏。@bob嘿,伙计,我也有同样的问题。你设法修好了吗?