np.asfarray的用法

量化交易李魔佛 发表了文章 • 0 个评论 • 11 次浏览 • 2018-09-24 10:52 • 来自相关话题

以前很少用的一个函数,见到别人的代码里面有,所以查了下文档,看看该函数的用法。
numpy.asfarray(a, dtype=<class 'numpy.float64'>)

Return an array converted to a float type.

Parameters:
a : array_like
The input array.

dtype : str or dtype object, optional
Float type code to coerce input array a. If dtype is one of the ‘int’ dtypes, it is replaced with float64.

Returns:
out : ndarray
The input a as a float ndarray.
用法就是把一个普通的数组转为一个浮点类型的数组:
 
Examples

>>>
>>> np.asfarray([2, 3])
array([ 2., 3.])
>>> np.asfarray([2, 3], dtype='float')
array([ 2., 3.])
>>> np.asfarray([2, 3], dtype='int8')
array([ 2., 3.]) 查看全部
以前很少用的一个函数,见到别人的代码里面有,所以查了下文档,看看该函数的用法。
numpy.asfarray(a, dtype=<class 'numpy.float64'>)

Return an array converted to a float type.

Parameters:
a : array_like
The input array.

dtype : str or dtype object, optional
Float type code to coerce input array a. If dtype is one of the ‘int’ dtypes, it is replaced with float64.

Returns:
out : ndarray
The input a as a float ndarray.

用法就是把一个普通的数组转为一个浮点类型的数组:
 
Examples

>>>
>>> np.asfarray([2, 3])
array([ 2., 3.])
>>> np.asfarray([2, 3], dtype='float')
array([ 2., 3.])
>>> np.asfarray([2, 3], dtype='int8')
array([ 2., 3.])

个人推荐免费VPN翻墙 windscribe 推荐送10GB流量 https://windscribe.com/?affid=9ye3iz2u

网络李魔佛 发表了文章 • 0 个评论 • 18 次浏览 • 2018-09-23 22:43 • 来自相关话题

目前来说速度比蓝灯快,而且免费。每个月可用流量要比蓝灯多的多。
蓝灯免费只有500MB,上一下youtube就没了。 
windscribe 有11GB的免费流量,对于一般的用户来说,已经够用的了。
 
翻墙
 
使用推荐链接,还可以获得额外的10GB流量。不使用推荐链接就没有10GB了呀,所以墙裂推荐!
我的推荐链接:https://windscribe.com/?affid=9ye3iz2u
 





  查看全部
目前来说速度比蓝灯快,而且免费。每个月可用流量要比蓝灯多的多。
蓝灯免费只有500MB,上一下youtube就没了。 
windscribe 有11GB的免费流量,对于一般的用户来说,已经够用的了。
 
翻墙
 
使用推荐链接,还可以获得额外的10GB流量。不使用推荐链接就没有10GB了呀,所以墙裂推荐!
我的推荐链接:https://windscribe.com/?affid=9ye3iz2u
 

youtube.JPG

 

jupyter notebook 显示 opencv的图片

python李魔佛 发表了文章 • 0 个评论 • 21 次浏览 • 2018-09-22 22:55 • 来自相关话题

import sys
import cv2
from matplotlib import pyplot as plt
import matplotlib
%matplotlib inlineimg = cv2.imread('forest.jpg')
plt.imshow(img)效果如图:





  查看全部
import sys
import cv2
from matplotlib import pyplot as plt
import matplotlib
%matplotlib inline
img = cv2.imread('forest.jpg')
plt.imshow(img)
效果如图:

cv_副本_副本_副本.png

 

kindle使用率低

书籍Freedom 回复了问题 • 2 人关注 • 1 个回复 • 305 次浏览 • 2018-09-05 17:15 • 来自相关话题

python爬虫集思录所有用户的帖子 scrapy写入mongodb数据库

python爬虫李魔佛 发表了文章 • 0 个评论 • 121 次浏览 • 2018-09-02 21:52 • 来自相关话题

好久没更新了,把之前做的一些爬虫分享一下。不然都没有用户来了。-. -
 
项目采用scrapy的框架,数据写入到mongodb的数据库。 整个站点爬下来大概用了半小时,数据有12w条。
 
项目中的主要代码如下:
 
主spider# -*- coding: utf-8 -*-
import re
import scrapy
from scrapy import Request, FormRequest
from jsl.items import JslItem
from jsl import config
import logging

class AllcontentSpider(scrapy.Spider):
name = 'allcontent'

headers = {
'Host': 'www.jisilu.cn', 'Connection': 'keep-alive', 'Pragma': 'no-cache',
'Cache-Control': 'no-cache', 'Accept': 'application/json,text/javascript,*/*;q=0.01',
'Origin': 'https://www.jisilu.cn', 'X-Requested-With': 'XMLHttpRequest',
'User-Agent': 'Mozilla/5.0(WindowsNT6.1;WOW64)AppleWebKit/537.36(KHTML,likeGecko)Chrome/67.0.3396.99Safari/537.36',
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
'Referer': 'https://www.jisilu.cn/login/',
'Accept-Encoding': 'gzip,deflate,br',
'Accept-Language': 'zh,en;q=0.9,en-US;q=0.8'
}

def start_requests(self):
login_url = 'https://www.jisilu.cn/login/'
headers = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
'Accept-Encoding': 'gzip,deflate,br', 'Accept-Language': 'zh,en;q=0.9,en-US;q=0.8',
'Cache-Control': 'no-cache', 'Connection': 'keep-alive',
'Host': 'www.jisilu.cn', 'Pragma': 'no-cache', 'Referer': 'https://www.jisilu.cn/',
'Upgrade-Insecure-Requests': '1',
'User-Agent': 'Mozilla/5.0(WindowsNT6.1;WOW64)AppleWebKit/537.36(KHTML,likeGecko)Chrome/67.0.3396.99Safari/537.36'}

yield Request(url=login_url, headers=headers, callback=self.login,dont_filter=True)

def login(self, response):
url = 'https://www.jisilu.cn/account/ajax/login_process/'
data = {
'return_url': 'https://www.jisilu.cn/',
'user_name': config.username,
'password': config.password,
'net_auto_login': '1',
'_post_type': 'ajax',
}

yield FormRequest(
url=url,
headers=self.headers,
formdata=data,
callback=self.parse,
dont_filter=True
)

def parse(self, response):
for i in range(1,3726):
focus_url = 'https://www.jisilu.cn/home/explore/sort_type-new__day-0__page-{}'.format(i)
yield Request(url=focus_url, headers=self.headers, callback=self.parse_page,dont_filter=True)

def parse_page(self, response):
nodes = response.xpath('//div[@class="aw-question-list"]/div')
for node in nodes:
each_url=node.xpath('.//h4/a/@href').extract_first()
yield Request(url=each_url,headers=self.headers,callback=self.parse_item,dont_filter=True)

def parse_item(self,response):
item = JslItem()
title = response.xpath('//div[@class="aw-mod-head"]/h1/text()').extract_first()
s = response.xpath('//div[@class="aw-question-detail-txt markitup-box"]').xpath('string(.)').extract_first()
ret = re.findall('(.*?)\.donate_user_avatar', s, re.S)

try:
content = ret[0].strip()
except:
content = None

createTime = response.xpath('//div[@class="aw-question-detail-meta"]/span/text()').extract_first()

resp_no = response.xpath('//div[@class="aw-mod aw-question-detail-box"]//ul/h2/text()').re_first('\d+')

url = response.url
item['title'] = title.strip()
item['content'] = content
try:
item['resp_no']=int(resp_no)
except Exception as e:
logging.warning('e')
item['resp_no']=None

item['createTime'] = createTime
item['url'] = url.strip()
resp =
for index,reply in enumerate(response.xpath('//div[@class="aw-mod-body aw-dynamic-topic"]/div[@class="aw-item"]')):
replay_user = reply.xpath('.//div[@class="pull-left aw-dynamic-topic-content"]//p/a/text()').extract_first()
rep_content = reply.xpath(
'.//div[@class="pull-left aw-dynamic-topic-content"]//div[@class="markitup-box"]/text()').extract_first()
# print rep_content
agree=reply.xpath('.//em[@class="aw-border-radius-5 aw-vote-count pull-left"]/text()').extract_first()
resp.append({replay_user.strip()+'_{}'.format(index): [int(agree),rep_content.strip()]})

item['resp'] = resp
yield item




login函数是模拟登录集思录,通过抓包就可以知道一些上传的data。
然后就是分页去抓取。逻辑很简单。
 
然后pipeline里面写入mongodb。import pymongo
from collections import OrderedDict
class JslPipeline(object):
def __init__(self):
self.db = pymongo.MongoClient(host='10.18.6.1',port=27017)
# self.user = u'neo牛3' # 修改为指定的用户名 如 毛之川 ,然后找到用户的id,在用户也的源码哪里可以找到 比如持有封基是8132
self.collection = self.db['db_parker']['jsl']
def process_item(self, item, spider):
self.collection.insert(OrderedDict(item))
return item
抓取到的数据入库mongodb:





 点击查看大图

原创文章
转载请注明出处:http://30daydo.com/publish/article/351
 
  查看全部
好久没更新了,把之前做的一些爬虫分享一下。不然都没有用户来了。-. -
 
项目采用scrapy的框架,数据写入到mongodb的数据库。 整个站点爬下来大概用了半小时,数据有12w条。
 
项目中的主要代码如下:
 
主spider
# -*- coding: utf-8 -*-
import re
import scrapy
from scrapy import Request, FormRequest
from jsl.items import JslItem
from jsl import config
import logging

class AllcontentSpider(scrapy.Spider):
name = 'allcontent'

headers = {
'Host': 'www.jisilu.cn', 'Connection': 'keep-alive', 'Pragma': 'no-cache',
'Cache-Control': 'no-cache', 'Accept': 'application/json,text/javascript,*/*;q=0.01',
'Origin': 'https://www.jisilu.cn', 'X-Requested-With': 'XMLHttpRequest',
'User-Agent': 'Mozilla/5.0(WindowsNT6.1;WOW64)AppleWebKit/537.36(KHTML,likeGecko)Chrome/67.0.3396.99Safari/537.36',
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
'Referer': 'https://www.jisilu.cn/login/',
'Accept-Encoding': 'gzip,deflate,br',
'Accept-Language': 'zh,en;q=0.9,en-US;q=0.8'
}

def start_requests(self):
login_url = 'https://www.jisilu.cn/login/'
headers = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
'Accept-Encoding': 'gzip,deflate,br', 'Accept-Language': 'zh,en;q=0.9,en-US;q=0.8',
'Cache-Control': 'no-cache', 'Connection': 'keep-alive',
'Host': 'www.jisilu.cn', 'Pragma': 'no-cache', 'Referer': 'https://www.jisilu.cn/',
'Upgrade-Insecure-Requests': '1',
'User-Agent': 'Mozilla/5.0(WindowsNT6.1;WOW64)AppleWebKit/537.36(KHTML,likeGecko)Chrome/67.0.3396.99Safari/537.36'}

yield Request(url=login_url, headers=headers, callback=self.login,dont_filter=True)

def login(self, response):
url = 'https://www.jisilu.cn/account/ajax/login_process/'
data = {
'return_url': 'https://www.jisilu.cn/',
'user_name': config.username,
'password': config.password,
'net_auto_login': '1',
'_post_type': 'ajax',
}

yield FormRequest(
url=url,
headers=self.headers,
formdata=data,
callback=self.parse,
dont_filter=True
)

def parse(self, response):
for i in range(1,3726):
focus_url = 'https://www.jisilu.cn/home/explore/sort_type-new__day-0__page-{}'.format(i)
yield Request(url=focus_url, headers=self.headers, callback=self.parse_page,dont_filter=True)

def parse_page(self, response):
nodes = response.xpath('//div[@class="aw-question-list"]/div')
for node in nodes:
each_url=node.xpath('.//h4/a/@href').extract_first()
yield Request(url=each_url,headers=self.headers,callback=self.parse_item,dont_filter=True)

def parse_item(self,response):
item = JslItem()
title = response.xpath('//div[@class="aw-mod-head"]/h1/text()').extract_first()
s = response.xpath('//div[@class="aw-question-detail-txt markitup-box"]').xpath('string(.)').extract_first()
ret = re.findall('(.*?)\.donate_user_avatar', s, re.S)

try:
content = ret[0].strip()
except:
content = None

createTime = response.xpath('//div[@class="aw-question-detail-meta"]/span/text()').extract_first()

resp_no = response.xpath('//div[@class="aw-mod aw-question-detail-box"]//ul/h2/text()').re_first('\d+')

url = response.url
item['title'] = title.strip()
item['content'] = content
try:
item['resp_no']=int(resp_no)
except Exception as e:
logging.warning('e')
item['resp_no']=None

item['createTime'] = createTime
item['url'] = url.strip()
resp =
for index,reply in enumerate(response.xpath('//div[@class="aw-mod-body aw-dynamic-topic"]/div[@class="aw-item"]')):
replay_user = reply.xpath('.//div[@class="pull-left aw-dynamic-topic-content"]//p/a/text()').extract_first()
rep_content = reply.xpath(
'.//div[@class="pull-left aw-dynamic-topic-content"]//div[@class="markitup-box"]/text()').extract_first()
# print rep_content
agree=reply.xpath('.//em[@class="aw-border-radius-5 aw-vote-count pull-left"]/text()').extract_first()
resp.append({replay_user.strip()+'_{}'.format(index): [int(agree),rep_content.strip()]})

item['resp'] = resp
yield item




login函数是模拟登录集思录,通过抓包就可以知道一些上传的data。
然后就是分页去抓取。逻辑很简单。
 
然后pipeline里面写入mongodb。
import pymongo
from collections import OrderedDict
class JslPipeline(object):
def __init__(self):
self.db = pymongo.MongoClient(host='10.18.6.1',port=27017)
# self.user = u'neo牛3' # 修改为指定的用户名 如 毛之川 ,然后找到用户的id,在用户也的源码哪里可以找到 比如持有封基是8132
self.collection = self.db['db_parker']['jsl']
def process_item(self, item, spider):
self.collection.insert(OrderedDict(item))
return item

抓取到的数据入库mongodb:

记实录.PNG

 点击查看大图

原创文章
转载请注明出处:http://30daydo.com/publish/article/351
 
 

docker里运行mongodb,保存的数据在外部使用mongoexport不能导出:提示错误Unrecognized field 'snapshot'

python李魔佛 发表了文章 • 0 个评论 • 162 次浏览 • 2018-08-31 14:21 • 来自相关话题

很无语。 目前还找不到原因。
 
dockery里面运行的mongodb, mongodb的数据挂载到宿主机。 开放了27017端口。
在windows下使用mongoexport工具导出数据:
 
错误信息:C:\Program Files\MongoDB\Server\3.4\bin>mongoexport.exe /h 10.18.6.102 /d stock
/c company /o company.json /type json
2018-08-31T14:13:47.841+0800 connected to: 10.18.6.102
2018-08-31T14:13:47.854+0800 Failed: Failed to parse: { find: "company", filt
er: {}, sort: {}, skip: 0, snapshot: true, $readPreference: { mode: "secondaryPr
eferred" }, $db: "stock" }. Unrecognized field 'snapshot'.

C:\Program Files\MongoDB\Server\3.4\bin> 查看全部
很无语。 目前还找不到原因。
 
dockery里面运行的mongodb, mongodb的数据挂载到宿主机。 开放了27017端口。
在windows下使用mongoexport工具导出数据:
 
错误信息:
C:\Program Files\MongoDB\Server\3.4\bin>mongoexport.exe /h 10.18.6.102 /d stock
/c company /o company.json /type json
2018-08-31T14:13:47.841+0800 connected to: 10.18.6.102
2018-08-31T14:13:47.854+0800 Failed: Failed to parse: { find: "company", filt
er: {}, sort: {}, skip: 0, snapshot: true, $readPreference: { mode: "secondaryPr
eferred" }, $db: "stock" }. Unrecognized field 'snapshot'.

C:\Program Files\MongoDB\Server\3.4\bin>

django不同版本的兼容性太麻烦了

python李魔佛 发表了文章 • 0 个评论 • 75 次浏览 • 2018-08-26 18:20 • 来自相关话题

对于新人来说太坑爹,不同版本,即使是一个小版本,很多函数都作了修改,或者直接被移除。好坑。
 
 
对于新人来说太坑爹,不同版本,即使是一个小版本,很多函数都作了修改,或者直接被移除。好坑。
 
 

哪些淘宝店铺被你列入了黑名单? 让我们一起来曝光

闲聊李魔佛 发表了文章 • 0 个评论 • 150 次浏览 • 2018-08-25 20:59 • 来自相关话题

相信大家平时淘宝购物肯定被坑过,那么下面列出你们拉黑的店铺吧。
1. 以尚牛仔




 
转至知乎的:

让我来一个。

买了一条牛仔裤,收到货没及时拆开,过了一个多星期再拆发现拉链是坏的,于是就去找卖家。

上来就说我买的时间太久了,一句道歉的话都没说。后面再回她干脆不鸟我了...然后我就给了差评“坏了就是坏了,态度还那么差!连句道歉都没有,现在鸟都不鸟了”。接着又过十天,也就是今天下午,打电话给我让我删了差评,然后再给我退20块赔偿,当时刚睡醒,听她态度还行就同意了。然后挂完电话想说晚点再删,没想到她就开始在淘宝上连环call!我就给她删了。




当时也想过会不会删了就被拉黑名单,但想说刚刚态度不错就没继续怀疑!但是!果然!删完以后态度依旧很十多天前一个样!依旧是保持高冷的态度鸟都不鸟,打电话也不接了!呵呵!然后百度了一下,说这是许多卖家惯用的手段,让你先删了评论给你赔偿,然后等你删了就不理你。

告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了!
告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了!
告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了! 查看全部
相信大家平时淘宝购物肯定被坑过,那么下面列出你们拉黑的店铺吧。
1. 以尚牛仔
v2-2142734d754bb9abd0a43a22fe571544_hd.jpg

 
转至知乎的:

让我来一个。

买了一条牛仔裤,收到货没及时拆开,过了一个多星期再拆发现拉链是坏的,于是就去找卖家。

上来就说我买的时间太久了,一句道歉的话都没说。后面再回她干脆不鸟我了...然后我就给了差评“坏了就是坏了,态度还那么差!连句道歉都没有,现在鸟都不鸟了”。接着又过十天,也就是今天下午,打电话给我让我删了差评,然后再给我退20块赔偿,当时刚睡醒,听她态度还行就同意了。然后挂完电话想说晚点再删,没想到她就开始在淘宝上连环call!我就给她删了。




当时也想过会不会删了就被拉黑名单,但想说刚刚态度不错就没继续怀疑!但是!果然!删完以后态度依旧很十多天前一个样!依旧是保持高冷的态度鸟都不鸟,打电话也不接了!呵呵!然后百度了一下,说这是许多卖家惯用的手段,让你先删了评论给你赔偿,然后等你删了就不理你。

告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了!
告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了!
告诫各位下次在淘宝上买的东西不好就是不好,该差评就差评,别被卖家骗了!

how to use proxy in scrapy_splash ?

python爬虫李魔佛 发表了文章 • 0 个评论 • 168 次浏览 • 2018-08-24 21:44 • 来自相关话题

方法一;
yield scrapy.Request(
url=self.base_url.format(i),
meta={'page':str(i),
'splash': {
'args': {
'images':0,
'wait': 15,
'proxy': self.get_proxy(),
},
'endpoint': 'render.html',
},
},
)

其中get_proxy() 返回的是 字符创,类似于 http://8.8.8.8.8:8888 这样的格式代理数据。
这个方式自己试过是可以使用的。
 
当然也可以使用 scrapy_splash 中的 SplashRequest方法进行调用,参数一样,只是位置有点变化。
 
方法二是写中间件,不过自己试了很多次,没有成功。 感觉网上的都是忽悠。
就是在 process_request中修改 request['splash']['args']['proxy']=xxxxxxx
无效,另外一个朋友也沟通过,也是说无法生效。
 
如果有人成功了的话,可以私信交流交流。
  查看全部
方法一;
yield scrapy.Request(
url=self.base_url.format(i),
meta={'page':str(i),
'splash': {
'args': {
'images':0,
'wait': 15,
'proxy': self.get_proxy(),
},
'endpoint': 'render.html',
},
},
)


其中get_proxy() 返回的是 字符创,类似于 http://8.8.8.8.8:8888 这样的格式代理数据。
这个方式自己试过是可以使用的。
 
当然也可以使用 scrapy_splash 中的 SplashRequest方法进行调用,参数一样,只是位置有点变化。
 
方法二是写中间件,不过自己试了很多次,没有成功。 感觉网上的都是忽悠。
就是在 process_request中修改 request['splash']['args']['proxy']=xxxxxxx
无效,另外一个朋友也沟通过,也是说无法生效。
 
如果有人成功了的话,可以私信交流交流。
 

python mongodb大数据(>3GB)转移Mysql数据库

python李魔佛 发表了文章 • 0 个评论 • 133 次浏览 • 2018-08-20 15:44 • 来自相关话题

数据约为5GB左右,如果直接用for i in doc.find({})进行逐行遍历的话,游标就会超时,而且越到后面速度越慢.
 
 于是使用了分段遍历的方法.# -*-coding=utf-8-*-
import pandas as pd
import json
import pymongo
from sqlalchemy import create_engine

# 将mongo数据转移到mysql

client = pymongo.MongoClient('xxx')
doc = client['spider']['meituan']
engine = create_engine('mysql+pymysql://xxx:xxx@xxx:/xxx?charset=utf8')


def classic_method():
temp =
start = 0
# 数据太大还是会爆内存,或者游标丢失
for i in doc.find().batch_size(500):
start += 1
del i['_id']
temp.append(i)
print(start)

print('start to save to mysql')
df = pd.read_json(json.dumps(temp))
df = df.set_index('poiid', drop=True)
df.to_sql('meituan', con=engine, if_exists='replace')
print('done')


def chunksize_move():
block = 10000
total = doc.find({}).count()
iter_number = total // block

for i in range(iter_number + 1):
small_part = doc.find({}).limit(block).skip(i * block)
list_data =

for item in small_part:
del item['_id']
del item['crawl_time']
item['poiid'] = int(item['poiid'])
for k, v in item.items():
if isinstance(v, dict) or isinstance(v, list):

item[k] = json.dumps(v, ensure_ascii=False)

list_data.append(item)

df = pd.DataFrame(list_data)
df = df.set_index('poiid', drop=True)

try:
df.to_sql('meituan', con=engine, if_exists='append')
print('to sql {}'.format(i))
except Exception as e:
print(e)

chunksize_move()

 





速度比一次批量的要快不少. 查看全部
数据约为5GB左右,如果直接用
for i in doc.find({})
进行逐行遍历的话,游标就会超时,而且越到后面速度越慢.
 
 于是使用了分段遍历的方法.
# -*-coding=utf-8-*-
import pandas as pd
import json
import pymongo
from sqlalchemy import create_engine

# 将mongo数据转移到mysql

client = pymongo.MongoClient('xxx')
doc = client['spider']['meituan']
engine = create_engine('mysql+pymysql://xxx:xxx@xxx:/xxx?charset=utf8')


def classic_method():
temp =
start = 0
# 数据太大还是会爆内存,或者游标丢失
for i in doc.find().batch_size(500):
start += 1
del i['_id']
temp.append(i)
print(start)

print('start to save to mysql')
df = pd.read_json(json.dumps(temp))
df = df.set_index('poiid', drop=True)
df.to_sql('meituan', con=engine, if_exists='replace')
print('done')


def chunksize_move():
block = 10000
total = doc.find({}).count()
iter_number = total // block

for i in range(iter_number + 1):
small_part = doc.find({}).limit(block).skip(i * block)
list_data =

for item in small_part:
del item['_id']
del item['crawl_time']
item['poiid'] = int(item['poiid'])
for k, v in item.items():
if isinstance(v, dict) or isinstance(v, list):

item[k] = json.dumps(v, ensure_ascii=False)

list_data.append(item)

df = pd.DataFrame(list_data)
df = df.set_index('poiid', drop=True)

try:
df.to_sql('meituan', con=engine, if_exists='append')
print('to sql {}'.format(i))
except Exception as e:
print(e)

chunksize_move()

 

to_sql.PNG

速度比一次批量的要快不少.

python 把mongodb的数据迁移到mysql

python李魔佛 发表了文章 • 0 个评论 • 149 次浏览 • 2018-08-20 11:02 • 来自相关话题

代码如下: 很简短.
import pymongo
from setting import get_engine

# 将mongo数据转移到mysql

client = pymongo.MongoClient('10.18.6.101')
doc = client['spider']['meituan']
engine = create_engine('mysql+pymysql://localhost:1234@10.18.4.211/spider?charset=utf8')
temp=[]

for i in doc.find({}):
del i['_id']
temp.append(i)
print('start to save to mysql')
df = pd.read_json(json.dumps(temp))
df = df.set_index('poiid',drop=True)
df.to_sql('meituan',con=engine,if_exists='replace')
print('done')





 
居然CPU飙到了90%
  查看全部
代码如下: 很简短.
import pymongo
from setting import get_engine

# 将mongo数据转移到mysql

client = pymongo.MongoClient('10.18.6.101')
doc = client['spider']['meituan']
engine = create_engine('mysql+pymysql://localhost:1234@10.18.4.211/spider?charset=utf8')
temp=[]

for i in doc.find({}):
del i['_id']
temp.append(i)
print('start to save to mysql')
df = pd.read_json(json.dumps(temp))
df = df.set_index('poiid',drop=True)
df.to_sql('meituan',con=engine,if_exists='replace')
print('done')


cpu.PNG

 
居然CPU飙到了90%
 

python json.loads 文件中的字典不能用单引号

python李魔佛 发表了文章 • 0 个评论 • 170 次浏览 • 2018-08-20 09:28 • 来自相关话题

python json.loads 文件中的字典不能用单引号
只能改成双引号,或者使用

with open('cookies', 'r') as f:
# js = json.load(f)
js=eval(f.read())
# cookie=js.get('Cookie','')
headers = js.get('headers', '')

#content为文件的内容 查看全部
python json.loads 文件中的字典不能用单引号
只能改成双引号,或者使用

with open('cookies', 'r') as f:
# js = json.load(f)
js=eval(f.read())
# cookie=js.get('Cookie','')
headers = js.get('headers', '')

#content为文件的内容

有道云笔记经常会保存丢失

闲聊李魔佛 发表了文章 • 0 个评论 • 129 次浏览 • 2018-08-19 16:58 • 来自相关话题

明明已经保存了的内容, 然后就不见了. 经常搜索的时候都搜不到自己保存的内容.
明明已经保存了的内容, 然后就不见了. 经常搜索的时候都搜不到自己保存的内容.

scrapy记录日志的最新方法

python爬虫李魔佛 发表了文章 • 0 个评论 • 131 次浏览 • 2018-08-15 15:01 • 来自相关话题

旧的方法:from scrapy import log
log.msg("This is a warning", level=log.WARING)

在Spider中添加log

在spider中添加log的推荐方式是使用Spider的 log() 方法。该方法会自动在调用 scrapy.log.start() 时赋值 spider 参数。

其它的参数则直接传递给 msg() 方法

 

scrapy.log模块scrapy.log.start(logfile=None, loglevel=None, logstdout=None)启动log功能。该方法必须在记录任何信息之前被调用。否则调用前的信息将会丢失。

但是运行的时候出现警告:

[py.warnings] WARNING: E:\git\CrawlMan\bilibili\bilibili\spiders\bili.py:14: ScrapyDeprecationWarning: log.msg has been deprecated, create a python logger and log through it instead
log.msg

原来官方以及不推荐使用log.msg了


最新的用法:# -*- coding: utf-8 -*-
import scrapy
from scrapy_splash import SplashRequest
import logging
# from scrapy import log
class BiliSpider(scrapy.Spider):
name = 'ordinary' # 这个名字就是上面连接中那个启动应用的名字
allowed_domain = ["bilibili.com"]
start_urls = [
"https://www.bilibili.com/"
]

def parse(self, response):
logging.info('====================================================')
content = response.xpath("//div[@class='num-wrap']").extract_first()
logging.info(content)
logging.info('====================================================') 查看全部
旧的方法:
from scrapy import log
log.msg("This is a warning", level=log.WARING)

在Spider中添加log

在spider中添加log的推荐方式是使用Spider的 log() 方法。该方法会自动在调用 scrapy.log.start() 时赋值 spider 参数。

其它的参数则直接传递给 msg() 方法

 

scrapy.log模块scrapy.log.start(logfile=None, loglevel=None, logstdout=None)启动log功能。该方法必须在记录任何信息之前被调用。否则调用前的信息将会丢失。

但是运行的时候出现警告:

[py.warnings] WARNING: E:\git\CrawlMan\bilibili\bilibili\spiders\bili.py:14: ScrapyDeprecationWarning: log.msg has been deprecated, create a python logger and log through it instead
log.msg


原来官方以及不推荐使用log.msg了


最新的用法:
# -*- coding: utf-8 -*-
import scrapy
from scrapy_splash import SplashRequest
import logging
# from scrapy import log
class BiliSpider(scrapy.Spider):
name = 'ordinary' # 这个名字就是上面连接中那个启动应用的名字
allowed_domain = ["bilibili.com"]
start_urls = [
"https://www.bilibili.com/"
]

def parse(self, response):
logging.info('====================================================')
content = response.xpath("//div[@class='num-wrap']").extract_first()
logging.info(content)
logging.info('====================================================')

adbapi查询语句 -- python3

python李魔佛 发表了文章 • 0 个评论 • 107 次浏览 • 2018-08-12 19:40 • 来自相关话题

Introduction to Twisted Enterprise
Abstract

Twisted is an asynchronous networking framework, but most database API implementations unfortunately have blocking interfaces -- for this reason, twisted.enterprise.adbapi was created. It is a non-blocking interface to the standardized DB-API 2.0 API, which allows you to access a number of different RDBMSes.

What you should already know

Python :-)
How to write a simple Twisted Server (see this tutorial to learn how)
Familiarity with using database interfaces (see the documentation for DBAPI 2.0 or this article by Andrew Kuchling)

Quick Overview

Twisted is an asynchronous framework. This means standard database modules cannot be used directly, as they typically work something like:# Create connection... db = dbmodule.connect('mydb', 'andrew', 'password') # ...which blocks for an unknown amount of time # Create a cursor cursor = db.cursor() # Do a query... resultset = cursor.query('SELECT * FROM table WHERE ...') # ...which could take a long time, perhaps even minutes.Those delays are unacceptable when using an asynchronous framework such as Twisted. For this reason, twisted provides twisted.enterprise.adbapi, an asynchronous wrapper for any DB-API 2.0-compliant module. It is currently best tested with the pyPgSQL module for PostgreSQL.

enterprise.adbapi will do blocking database operations in seperate threads, which trigger callbacks in the originating thread when they complete. In the meantime, the original thread can continue doing normal work, like servicing other requests.

How do I use adbapi?

Rather than creating a database connection directly, use the adbapi.ConnectionPool class to manage a connections for you. This allows enterprise.adbapi to use multiple connections, one per thread. This is easy:# Using the "dbmodule" from the previous example, create a ConnectionPool from twisted.enterprise import adbapi dbpool = adbapi.ConnectionPool("dbmodule", 'mydb', 'andrew', 'password')Things to note about doing this:

There is no need to import dbmodule directly. You just pass the name to adbapi.ConnectionPool's constructor.
The parameters you would pass to dbmodule.connect are passed as extra arguments to adbapi.ConnectionPool's constructor. Keyword parameters work as well.
You may also control the size of the connection pool with the keyword parameters cp_min and cp_max. The default minimum and maximum values are 3 and 5.

So, now you need to be able to dispatch queries to your ConnectionPool. We do this by subclassing adbapi.Augmentation. Here's an example:class AgeDatabase(adbapi.Augmentation): """A simple example that can retrieve an age from the database""" def getAge(self, name): # Define the query sql = """SELECT Age FROM People WHERE name = ?""" # Run the query, and return a Deferred to the caller to add # callbacks to. return self.runQuery(sql, name) def gotAge(resultlist, name): """Callback for handling the result of the query""" age = resultlist[0][0] # First field of first record print "%s is %d years old" % (name, age) db = AgeDatabase(dbpool) # These will *not* block. Hooray! db.getAge("Andrew").addCallbacks(gotAge, db.operationError, callbackArgs=("Andrew",)) db.getAge("Glyph").addCallbacks(gotAge, db.operationError, callbackArgs=("Glyph",)) # Of course, nothing will happen until the reactor is started from twisted.internet import reactor reactor.run()This is straightforward, except perhaps for the return value of getAge. It returns a twisted.internet.defer.Deferred, which allows arbitrary callbacks to be called upon completion (or upon failure). More documentation on Deferred is available here.

Also worth noting is that this example assumes that dbmodule uses the qmarks paramstyle (see the DB-API specification). If your dbmodule uses a different paramstyle (e.g. pyformat) then use that. Twisted doesn't attempt to offer any sort of magic paramater munging -- runQuery(query, params, ...) maps directly onto cursor.execute(query, params, ...).

And that's it!

That's all you need to know to use a database from within Twisted. You probably should read the adbapi module's documentation to get an idea of the other functions it has, but hopefully this document presents the core ideas. 查看全部
Introduction to Twisted Enterprise
Abstract

Twisted is an asynchronous networking framework, but most database API implementations unfortunately have blocking interfaces -- for this reason, twisted.enterprise.adbapi was created. It is a non-blocking interface to the standardized DB-API 2.0 API, which allows you to access a number of different RDBMSes.

What you should already know

Python :-)
How to write a simple Twisted Server (see this tutorial to learn how)
Familiarity with using database interfaces (see the documentation for DBAPI 2.0 or this article by Andrew Kuchling)

Quick Overview

Twisted is an asynchronous framework. This means standard database modules cannot be used directly, as they typically work something like:# Create connection... db = dbmodule.connect('mydb', 'andrew', 'password') # ...which blocks for an unknown amount of time # Create a cursor cursor = db.cursor() # Do a query... resultset = cursor.query('SELECT * FROM table WHERE ...') # ...which could take a long time, perhaps even minutes.Those delays are unacceptable when using an asynchronous framework such as Twisted. For this reason, twisted provides twisted.enterprise.adbapi, an asynchronous wrapper for any DB-API 2.0-compliant module. It is currently best tested with the pyPgSQL module for PostgreSQL.

enterprise.adbapi will do blocking database operations in seperate threads, which trigger callbacks in the originating thread when they complete. In the meantime, the original thread can continue doing normal work, like servicing other requests.

How do I use adbapi?

Rather than creating a database connection directly, use the adbapi.ConnectionPool class to manage a connections for you. This allows enterprise.adbapi to use multiple connections, one per thread. This is easy:# Using the "dbmodule" from the previous example, create a ConnectionPool from twisted.enterprise import adbapi dbpool = adbapi.ConnectionPool("dbmodule", 'mydb', 'andrew', 'password')Things to note about doing this:

There is no need to import dbmodule directly. You just pass the name to adbapi.ConnectionPool's constructor.
The parameters you would pass to dbmodule.connect are passed as extra arguments to adbapi.ConnectionPool's constructor. Keyword parameters work as well.
You may also control the size of the connection pool with the keyword parameters cp_min and cp_max. The default minimum and maximum values are 3 and 5.

So, now you need to be able to dispatch queries to your ConnectionPool. We do this by subclassing adbapi.Augmentation. Here's an example:class AgeDatabase(adbapi.Augmentation): """A simple example that can retrieve an age from the database""" def getAge(self, name): # Define the query sql = """SELECT Age FROM People WHERE name = ?""" # Run the query, and return a Deferred to the caller to add # callbacks to. return self.runQuery(sql, name) def gotAge(resultlist, name): """Callback for handling the result of the query""" age = resultlist[0][0] # First field of first record print "%s is %d years old" % (name, age) db = AgeDatabase(dbpool) # These will *not* block. Hooray! db.getAge("Andrew").addCallbacks(gotAge, db.operationError, callbackArgs=("Andrew",)) db.getAge("Glyph").addCallbacks(gotAge, db.operationError, callbackArgs=("Glyph",)) # Of course, nothing will happen until the reactor is started from twisted.internet import reactor reactor.run()This is straightforward, except perhaps for the return value of getAge. It returns a twisted.internet.defer.Deferred, which allows arbitrary callbacks to be called upon completion (or upon failure). More documentation on Deferred is available here.

Also worth noting is that this example assumes that dbmodule uses the qmarks paramstyle (see the DB-API specification). If your dbmodule uses a different paramstyle (e.g. pyformat) then use that. Twisted doesn't attempt to offer any sort of magic paramater munging -- runQuery(query, params, ...) maps directly onto cursor.execute(query, params, ...).

And that's it!

That's all you need to know to use a database from within Twisted. You probably should read the adbapi module's documentation to get an idea of the other functions it has, but hopefully this document presents the core ideas.

python判断身份证的合法性

python李魔佛 发表了文章 • 0 个评论 • 158 次浏览 • 2018-08-10 13:56 • 来自相关话题

输入身份证号码, 判断18位身份证号码是否合法, 并查询信息(性别, 年龄, 所在地)

验证原理

将前面的身份证号码17位数分别乘以不同的系数, 从第一位到第十七位的系数分别为: 7 9 10 5 8 4 2 1 6 3 7 9 10 5 8 4 2
将这17位数字和系数相乘的结果相加.
用加出来和除以11, 看余数是多少?
余数只可能有<0 1 2 3 4 5 6 7 8 9 10>这11个数字, 其分别对应的最后一位身份证的号码为<1 0 X 9 8 7 6 5 4 3 2>.
通过上面得知如果余数是2,就会在身份证的第18位数字上出现罗马数字的Ⅹ。如果余数是10,身份证的最后一位号码就是2.

例如: 某男性的身份证号码是34052419800101001X, 我们要看看这个身份证是不是合法的身份证.

首先: 我们得出, 前17位的乘积和是189.

然后: 用189除以11得出的余数是2.

最后: 通过对应规则就可以知道余数2对应的数字是x. 所以, 这是一个合格的身份证号码.
 
代码如下:
#!/bin/env python
# -*- coding: utf-8 -*-

from sys import platform
import json
import codecs

with codecs.open('data.json', 'r', encoding='utf8') as json_data:
city = json.load(json_data)

def check_valid(idcard):
# 城市编码, 出生日期, 归属地
city_id = idcard[:6]
print(city_id)
birth = idcard[6:14]

city_name = city.get(city_id,'Not found')

# 根据规则校验身份证是否符合规则
idcard_tuple = [int(num) for num in list(idcard[:-1])]
coefficient = [7, 9, 10, 5, 8, 4, 2, 1, 6, 3, 7, 9, 10, 5, 8, 4, 2]
sum_value = sum([idcard_tuple[i] * coefficient[i] for i in range(17)])

remainder = sum_value % 11

maptable = {0: '1', 1: '0', 2: 'x', 3: '9', 4: '8', 5: '7', 6: '6', 7: '5', 8: '4', 9: '3', 10: '2'}

if maptable[remainder] == idcard[17]:
print('<身份证合法>')
sex = int(idcard[16]) % 2
sex = '男' if sex == 1 else '女'
print('性别:' + sex)
birth_format="{}年{}月{}日".format(birth[:4],birth[4:6],birth[6:8])
print('出生日期:' + birth_format)
print('归属地:' + city_name)
return True
else:
print('<身份证不合法>')
return False


if __name__=='__main__':
idcard = str(input('请输入身份证号码:'))
check_valid(idcard)

github源码:https://github.com/Rockyzsu/IdentityCheck
  查看全部
输入身份证号码, 判断18位身份证号码是否合法, 并查询信息(性别, 年龄, 所在地)

验证原理

将前面的身份证号码17位数分别乘以不同的系数, 从第一位到第十七位的系数分别为: 7 9 10 5 8 4 2 1 6 3 7 9 10 5 8 4 2
将这17位数字和系数相乘的结果相加.
用加出来和除以11, 看余数是多少?
余数只可能有<0 1 2 3 4 5 6 7 8 9 10>这11个数字, 其分别对应的最后一位身份证的号码为<1 0 X 9 8 7 6 5 4 3 2>.
通过上面得知如果余数是2,就会在身份证的第18位数字上出现罗马数字的Ⅹ。如果余数是10,身份证的最后一位号码就是2.

例如: 某男性的身份证号码是34052419800101001X, 我们要看看这个身份证是不是合法的身份证.

首先: 我们得出, 前17位的乘积和是189.

然后: 用189除以11得出的余数是2.

最后: 通过对应规则就可以知道余数2对应的数字是x. 所以, 这是一个合格的身份证号码.
 
代码如下:
#!/bin/env python
# -*- coding: utf-8 -*-

from sys import platform
import json
import codecs

with codecs.open('data.json', 'r', encoding='utf8') as json_data:
city = json.load(json_data)

def check_valid(idcard):
# 城市编码, 出生日期, 归属地
city_id = idcard[:6]
print(city_id)
birth = idcard[6:14]

city_name = city.get(city_id,'Not found')

# 根据规则校验身份证是否符合规则
idcard_tuple = [int(num) for num in list(idcard[:-1])]
coefficient = [7, 9, 10, 5, 8, 4, 2, 1, 6, 3, 7, 9, 10, 5, 8, 4, 2]
sum_value = sum([idcard_tuple[i] * coefficient[i] for i in range(17)])

remainder = sum_value % 11

maptable = {0: '1', 1: '0', 2: 'x', 3: '9', 4: '8', 5: '7', 6: '6', 7: '5', 8: '4', 9: '3', 10: '2'}

if maptable[remainder] == idcard[17]:
print('<身份证合法>')
sex = int(idcard[16]) % 2
sex = '男' if sex == 1 else '女'
print('性别:' + sex)
birth_format="{}年{}月{}日".format(birth[:4],birth[4:6],birth[6:8])
print('出生日期:' + birth_format)
print('归属地:' + city_name)
return True
else:
print('<身份证不合法>')
return False


if __name__=='__main__':
idcard = str(input('请输入身份证号码:'))
check_valid(idcard)


github源码:https://github.com/Rockyzsu/IdentityCheck
 

想写一个爬取开奖数据并预测下一期的py

python爬虫李魔佛 回复了问题 • 2 人关注 • 1 个回复 • 185 次浏览 • 2018-08-10 00:22 • 来自相关话题

pymysql.err.InternalError: Packet sequence number wrong - got 4 expected 1

网络安全李魔佛 发表了文章 • 0 个评论 • 318 次浏览 • 2018-07-19 13:59 • 来自相关话题

在django里面使用pymysql的方式进行链接, 结果就悲剧了.
 
PyMySQL is not thread safty to share connections as we did (we shared the class instance between multiple files as a global instance - in the class there is only one connection), it is labled as 1:

threadsafety = 1

According to PEP 249:

1 - Threads may share the module, but not connections.

One of the comments in PyMySQL github issue:

you need one pysql.connect() for each process/thread. As far as I know that's the only way to fix it. PyMySQL is not thread safe, so the same connection can't be used across multiple threads.

Any way if you were thinking of using other python package called MySQLdb for your threading application, notice to MySQLdb message:

Don't share connections between threads. It's really not worth your effort or mine, and in the end, will probably hurt performance, since the MySQL server runs a separate thread for each connection. You can certainly do things like cache connections in a pool, and give those connections to one thread at a time. If you let two threads use a connection simultaneously, the MySQL client library will probably upchuck and die. You have been warned. For threaded applications, try using a connection pool. This can be done using the Pool module.

Eventually we managed to use Django ORM and we are writing only for our specific table, managed by using inspectdb. 查看全部
在django里面使用pymysql的方式进行链接, 结果就悲剧了.
 
PyMySQL is not thread safty to share connections as we did (we shared the class instance between multiple files as a global instance - in the class there is only one connection), it is labled as 1:

threadsafety = 1

According to PEP 249:

1 - Threads may share the module, but not connections.

One of the comments in PyMySQL github issue:

you need one pysql.connect() for each process/thread. As far as I know that's the only way to fix it. PyMySQL is not thread safe, so the same connection can't be used across multiple threads.

Any way if you were thinking of using other python package called MySQLdb for your threading application, notice to MySQLdb message:

Don't share connections between threads. It's really not worth your effort or mine, and in the end, will probably hurt performance, since the MySQL server runs a separate thread for each connection. You can certainly do things like cache connections in a pool, and give those connections to one thread at a time. If you let two threads use a connection simultaneously, the MySQL client library will probably upchuck and die. You have been warned. For threaded applications, try using a connection pool. This can be done using the Pool module.

Eventually we managed to use Django ORM and we are writing only for our specific table, managed by using inspectdb.

mongodb sort: Executor error during find command: OperationFailed: Sort operation used more than

网络李魔佛 发表了文章 • 0 个评论 • 253 次浏览 • 2018-07-09 10:31 • 来自相关话题

mongodb 排序出现内存溢出:
 Error: error: {
"ok" : 0,
"errmsg" : "Executor error during find command: OperationFailed: Sort operation used more than the maximum 33554432 bytes of RAM. Add an index, or specify a smaller limit.",
"code" : 96,
"codeName" : "OperationFailed"
}
使用limit函数限制其输出就可以了:
 
db.getCollection('老布').find({}).sort({'created_at':-1}).limit(1000) 查看全部
mongodb 排序出现内存溢出:
 
Error: error: {
"ok" : 0,
"errmsg" : "Executor error during find command: OperationFailed: Sort operation used more than the maximum 33554432 bytes of RAM. Add an index, or specify a smaller limit.",
"code" : 96,
"codeName" : "OperationFailed"
}

使用limit函数限制其输出就可以了:
 
db.getCollection('老布').find({}).sort({'created_at':-1}).limit(1000)

每天给小孩子看英语视频可以让小孩学到什么?

闲聊绫波丽 发表了文章 • 0 个评论 • 192 次浏览 • 2018-07-07 11:10 • 来自相关话题

结论是Nothing。
 
没有互动,没有实际使用,语言没有用武之地,最终只是当做一种娱乐消遣。
那么多看美剧的,问问他们的英语水平,会不会比7岁的在国外长大的小孩的英语水平高? 不会,至少他们连流畅沟通都做不到。
 
结论是Nothing。
 
没有互动,没有实际使用,语言没有用武之地,最终只是当做一种娱乐消遣。
那么多看美剧的,问问他们的英语水平,会不会比7岁的在国外长大的小孩的英语水平高? 不会,至少他们连流畅沟通都做不到。
 

最新版的chrome中info lite居然不支持了

python爬虫李魔佛 发表了文章 • 0 个评论 • 219 次浏览 • 2018-06-25 18:58 • 来自相关话题

更新到了v67版本后,info lite居然不见了. 我晕.
只好降级......
 
版本 65.0.3325.162(正式版本) (64 位)
这个版本最新且支持info lite的。
 
 
更新到了v67版本后,info lite居然不见了. 我晕.
只好降级......
 
版本 65.0.3325.162(正式版本) (64 位)
这个版本最新且支持info lite的。
 
 

python sqlalchemy ORM 添加注释

python李魔佛 发表了文章 • 0 个评论 • 225 次浏览 • 2018-06-25 16:17 • 来自相关话题

需要更新sqlalchemy到最新版本,旧版本会不支持。
 
在定义ORM对象的时候,
class CreditRecord(Base):
__tablename__ = 'tb_PersonPunishment'

id = Column(Integer, primary_key=True, autoincrement=True)
name = Column(String(180),comment='名字')
添加一个comment参数即可。
 
  查看全部
需要更新sqlalchemy到最新版本,旧版本会不支持。
 
在定义ORM对象的时候,
class CreditRecord(Base):
__tablename__ = 'tb_PersonPunishment'

id = Column(Integer, primary_key=True, autoincrement=True)
name = Column(String(180),comment='名字')

添加一个comment参数即可。
 
 

新股开板后五日均线上穿10日均线

股票李魔佛 回复了问题 • 2 人关注 • 1 个回复 • 347 次浏览 • 2018-06-24 09:25 • 来自相关话题

windows 7 python3 安装MySQLdb 库

python李魔佛 发表了文章 • 0 个评论 • 227 次浏览 • 2018-06-20 18:04 • 来自相关话题

python3下没有MySQLdb的库,可以直接到这里下载mysqlclient库来替代。https://www.lfd.uci.edu/~gohlke/pythonlibs/#mysqlclient
 
python3下没有MySQLdb的库,可以直接到这里下载mysqlclient库来替代。https://www.lfd.uci.edu/~gohlke/pythonlibs/#mysqlclient
 

工行的app实在是烂到家了,怎么点击都打不开

闲聊量化大师 发表了文章 • 0 个评论 • 218 次浏览 • 2018-06-20 00:12 • 来自相关话题

都什么年代了,完全和招行这些app无法比,而且看起来就跟网页的网银时代一模一样的垃圾作风(只兼容IE,页面杂乱),垃圾的研发延续到app端,实在无法忍,十次九次打开失败,有导致整个系统假死的,或者系统突然极其卡顿,或者没有任何反应。
都什么年代了,完全和招行这些app无法比,而且看起来就跟网页的网银时代一模一样的垃圾作风(只兼容IE,页面杂乱),垃圾的研发延续到app端,实在无法忍,十次九次打开失败,有导致整个系统假死的,或者系统突然极其卡顿,或者没有任何反应。