<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[YPL_ZML的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/YPL_ZML</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; YPL_ZML]]></copyright><item><title><![CDATA[flask 开发获取用户IP及请求头信息]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/98482584</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/98482584</guid><author>YPL_ZML</author><pubDate>Mon, 05 Aug 2019 13:38:52 +0800</pubDate><description><![CDATA[flask获取用户IP
from flask import Flask, render_template, request
# Initialize the Flask application
app = Flask(__name__)
# Default route, print user's IP
@app.route('/')
def index():
 ip = request.remot...]]></description><category></category></item><item><title><![CDATA[mysql主从服务器的配置]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/96269850</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/96269850</guid><author>YPL_ZML</author><pubDate>Wed, 17 Jul 2019 08:53:00 +0800</pubDate><description><![CDATA[使用mysql主从复制的好处有：
1、采用主从服务器这种架构，稳定性得以提升。如果主服务器发生故障，我们可以使用从服务器来提供服务。
2、在主从服务器上分开处理用户的请求，可以提升数据处理效率。
3、将主服务器上的数据复制到从服务器上，保护数据免受意外的损失。
环境描述：
新企业要搭建架构为主从复制的mysql数据库。
主服务器（mysql-master）：IP地址：192.168.48.128，...]]></description><category></category></item><item><title><![CDATA[djano实现qq一键登录]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94837506</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94837506</guid><author>YPL_ZML</author><pubDate>Sat, 06 Jul 2019 10:34:16 +0800</pubDate><description><![CDATA[#在login登录url下留出qq登录url
#eg:www.323.com/login?type=qq

tp = request.GET.get('type',None)
if tp:
    code_url = 'https://graph.qq.com/oauth2.0/authorize'
    parm = {
          'response_type':'code',
 ...]]></description><category></category></item><item><title><![CDATA[Flask中的session ,自定义实现 session机制, 和 flask-session组件]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94613223</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94613223</guid><author>YPL_ZML</author><pubDate>Thu, 04 Jul 2019 14:11:32 +0800</pubDate><description><![CDATA[session 是基于cookie实现， 保存在服务端的键值对（形式为 {随机字符串：‘xxxxxx’}）, 同时在浏览器中的cookie中也对应一相同的随机字符串，用来再次请求的 时候验证；
注意 ：Flask中的session是存在浏览器中  默认key是session(加密的cookie)， 也可以像Django一样基于上述的方式实现保存在数据库
1 flask中 session的基本概念
...]]></description><category></category></item><item><title><![CDATA[flask cookie设置，获取和删除]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94593757</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94593757</guid><author>YPL_ZML</author><pubDate>Thu, 04 Jul 2019 08:22:13 +0800</pubDate><description><![CDATA[#cookie相关操作，依赖于make_response
#调用cookie依赖request模块
from flask import Flask,make_response,request


#建立对象
app = Flask(__name__)


#从配置文间中加载配置
app.config.from_pyfile("config.ini")


@app.route("/")
def i...]]></description><category></category></item><item><title><![CDATA[MongoDB：查询和投影操作符（参照）]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94412749</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94412749</guid><author>YPL_ZML</author><pubDate>Mon, 01 Jul 2019 22:59:47 +0800</pubDate><description><![CDATA[原帖，请参看这里。
官网：https://docs.mongodb.com/manual/reference/operator/query/。
这一章节都是很简单的英语，就做一个很简单的备注，如果连这个英语都看不懂，那就需要提高了，程序员看不懂基本的英语是很难提高的。 
这一章节还需要完善一些样例，这个有待补充。
查询选择器
比较



  名字
  描述



  $eq
  Matches v...]]></description><category></category></item><item><title><![CDATA[在django中redis数据库的使用]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94302987</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94302987</guid><author>YPL_ZML</author><pubDate>Sun, 30 Jun 2019 11:59:02 +0800</pubDate><description><![CDATA[第一步：
修改setting配置
# django redis
CACHES = {
    "default": {
        "BACKEND": "django_redis.cache.RedisCache",
        # 这里写远程的ip 和 端口
        "LOCATION": "redis://39.105.158.4:6379/1",
        "OPTI...]]></description><category></category></item><item><title><![CDATA[pycharm使用mysql模板]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94301533</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94301533</guid><author>YPL_ZML</author><pubDate>Sun, 30 Jun 2019 11:45:51 +0800</pubDate><description><![CDATA[import pymysql

class MySQLCommand(object):
    # 类的初始化
    def __init__(self):
        self.host = 'localhost'
        self.port = 3306  # 端口号
        self.user = 'root'  # 用户名
        self.password ...]]></description><category></category></item><item><title><![CDATA[tensorflow在windows——python3.7下安装教程（最新教程）]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94291891</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94291891</guid><author>YPL_ZML</author><pubDate>Sun, 30 Jun 2019 10:16:37 +0800</pubDate><description><![CDATA[Tensorflow1.13.1版本已经正式发布，现在Python3.7直接安装Tensorflow即可。
pip install tensorflow
pip install tensorflow
一段时间之后即可安装完成！！
Successfully installed tensorflow-1.13.1
接下来测试一下吧
import ten...]]></description><category></category></item><item><title><![CDATA[redis  正确显示中文命令]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94173477</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94173477</guid><author>YPL_ZML</author><pubDate>Sat, 29 Jun 2019 16:43:50 +0800</pubDate><description><![CDATA[启动redis客户端时加上 --raw
redis-cli -h redis_host --raw


]]></description><category></category></item><item><title><![CDATA[Redis和MySQL的4种结合方案]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94170505</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94170505</guid><author>YPL_ZML</author><pubDate>Sat, 29 Jun 2019 16:21:34 +0800</pubDate><description><![CDATA[转自：&nbsp;https://www.cnblogs.com/daydaynobug/p/6649960.html
&nbsp;
方案一：
程序同时写Redis和MySQL
读Redis

&nbsp;
方案二：
程序写MySQL， 使用Gearman调用MySQL的UDF，完成对Redis的写
读Redis

&nbsp;
方案三：
程序写M...]]></description><category></category></item><item><title><![CDATA[使用redis做为MySQL的缓存]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94169970</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94169970</guid><author>YPL_ZML</author><pubDate>Sat, 29 Jun 2019 16:17:32 +0800</pubDate><description><![CDATA[使用redis做为MySQL的缓存
介绍
•在实际项目中，MySQL数据库服务器有时会位于另外一台主机，需要通过网络来访问数据库；即使应用程序与MySQL数据库在同一个主机中，访问MySQL也涉及到磁盘IO操作（MySQL也有一些数据预读技术，能够减少磁盘IO读写，此部分后续继续研究），总之，直接从MySQL中读取数据不如直接从内存中读取数据来的效率高。为了提高数据库访问效率，人们采用了各种各样的...]]></description><category></category></item><item><title><![CDATA[mysql 分布式事务]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94131522</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94131522</guid><author>YPL_ZML</author><pubDate>Sat, 29 Jun 2019 10:31:23 +0800</pubDate><description><![CDATA[版权声明：本文为博主原创文章，支持转载，但转载时请务必在明显位置，给出原文作者名字『DoubleFJ』及原文链接。否则，作者将保留追究法律责任的权利。                        https://blog.youkuaiyun.com/ffj0721/article/details/87091095
前言
MySQL 从 5.0.3 开始支持分布式事务，当前分布式事务只支持 InnoDB 存...]]></description><category></category></item><item><title><![CDATA[MySQL数据库事务处理]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/94127659</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/94127659</guid><author>YPL_ZML</author><pubDate>Sat, 29 Jun 2019 09:56:35 +0800</pubDate><description><![CDATA[事务处理用于有效记录某机构感兴趣的业务活动（称为事务）的数据处理（例如销售、供货的定购或货币传输）。通常，联机事务处理 (OLTP) 系统执行大量的相对较小的事务。——百度百科]]></description><category></category></item><item><title><![CDATA[线性逻辑回归以及稳健性测试]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906685</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906685</guid><author>YPL_ZML</author><pubDate>Thu, 27 Jun 2019 20:10:51 +0800</pubDate><description><![CDATA[import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model.logistic import LogisticRegression
from sklearn.preprocessing import StandardScale...]]></description><category></category></item><item><title><![CDATA[TfidfVectorizer统计词频]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906460</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906460</guid><author>YPL_ZML</author><pubDate>Thu, 27 Jun 2019 20:08:54 +0800</pubDate><description><![CDATA[from sklearn.feature_extraction.text import TfidfVectorizer
import jieba

# text = ['This is the first document.', 'This is the second second document.', 'And the third one.',
#         'Is this the f...]]></description><category></category></item><item><title><![CDATA[CountVectorizer 词频统计]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906264</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906264</guid><author>YPL_ZML</author><pubDate>Thu, 27 Jun 2019 20:06:10 +0800</pubDate><description><![CDATA[from sklearn.feature_extraction.text import CountVectorizer
import  jieba
# 实例化一个con_vec对象
# con_vec = CountVectorizer(min_df=1)


# 准备文本数据
# text = ['This is the first document.', 'This is the second...]]></description><category></category></item><item><title><![CDATA[knn算法KNeighborsClassifier实现]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906184</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93906184</guid><author>YPL_ZML</author><pubDate>Thu, 27 Jun 2019 20:05:29 +0800</pubDate><description><![CDATA[import pandas as pd
import numpy as np
from sklearn.neighbors import KNeighborsClassifier


# 加载数据
mov = pd.read_excel('电影分类数据.xlsx')
# print(mov)
train = mov.iloc[:, 1:6]

train.loc[train.loc[:, '电影类...]]></description><category></category></item><item><title><![CDATA[knn算法原理]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93792672</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93792672</guid><author>YPL_ZML</author><pubDate>Wed, 26 Jun 2019 23:02:23 +0800</pubDate><description><![CDATA[import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt


# 分析--》训练集里面 构建分类器模型
# ---在测试集里面进行应用，来评估分类器性能

# 加载数据
# def deal_data(dir_path):
#     """
#     处理数据
#     :param di...]]></description><category></category></item><item><title><![CDATA[knn算法原理]]></title><link>https://blog.youkuaiyun.com/YPL_ZML/article/details/93792370</link><guid>https://blog.youkuaiyun.com/YPL_ZML/article/details/93792370</guid><author>YPL_ZML</author><pubDate>Wed, 26 Jun 2019 22:59:51 +0800</pubDate><description><![CDATA[import pandas as pd
import numpy as np


def distance(v1, v2):
    """
    自实现距离计算
    :param v1: 点v1
    :param v2: 点v2
    :return: 距离
    """
    # 法一
    # ndim = len(v1)
    # summary = 0
    # f...]]></description><category></category></item></channel></rss>