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Filename too long in git for windows

匿名 (未验证) 提交于 2019-12-03 01:18:02
可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效,请关闭广告屏蔽插件后再试): 问题: I'm using Git-1.9.0-preview20140217 for Windows. As I know, this release should fix the issue with too long filenames. But not for me. Surely I'm doing something wrong: I did git config core.longpaths true and git add . then git commit . Everything went well. But when I now do a git status , I get a list of files with Filename too long , e.g. node_modules/grunt-contrib-imagemin/node_modules/pngquant-bin/node_modules/bin-wrapper/node_modules/download/node_modules/request/node_modules/form-data/node_modules/combined-stream/node_modules/delayed

redis中bitmaps进行状态统计

匿名 (未验证) 提交于 2019-12-03 00:44:02
Bitmap //key String key1 = "20180501" ; // id int useId1 = 1 ; int useId2 = 2 ; int useId3 = 3 ; int useId4 = 4 ; int useId20 = 20 ; // redisDao .setBit(key1 , useId1 , true ) ; redisDao .setBit(key1 , useId2 , true ) ; redisDao .setBit(key1 , useId3 , true ) ; redisDao .setBit(key1 , useId4 , true ) ; redisDao .setBit(key1 , useId20 , true ) ; // 0111 1000 0000 0000 0000 1000 16 : 0x7800 0x08 long login1 = redisServiceExtend .bitCount(key1) ; System. out .println( " : " + login1) ; 文章来源: redis中bitmaps进行状态统计

easyUI-layout布局

匿名 (未验证) 提交于 2019-12-03 00:34:01
<!DOCTYPE html> <html> <head> <meta charset = "utf-8" > <title> 按钮 </title> <link rel = "stylesheet" type = "text/css" href = "js/jquery-easyui/themes/default/easyui.css" > <link rel = "stylesheet" type = "text/css" href = "js/jquery-easyui/themes/icon.css" > <link rel = "stylesheet" type = "text/css" href = "js/jquery-easyui/themes/default/layout.css" > <script src = "js/jquery.min.js" type = "text/javascript" ></script> <script type = "text/javascript" src = "js/jquery-easyui/jquery.easyui.min.js" ></script> <style> img { width : 100px ; height : 100px ; overflow : hidden ; } . p - search {

Numpy的用法测试

匿名 (未验证) 提交于 2019-12-03 00:32:02
x =np .random .random ( 10 ) #>0.5 y =np .random .random ( 10 )> 0.5 print( x , y ) x =np .asarray ( x ,np .int 32) y =np .asarray ( y ,np .int 32) print( x , y ) 输出 [ 0.09729203 0.92599196 0.02091592 0.69827894 0.08591189 0.70964561 0.62899646 0.97372343 0.70278155 0.55893902 ] [ True True True False True True False False True False ] [ 0 0 0 0 0 0 0 0 0 0 ] [ 1 1 1 0 1 1 0 0 1 0 ] 顺便记录: np.asarray与np.array都是将结构数据转化为ndarray,但是主要区别就是当数据源是ndarray时,array仍然会copy出一个副本,占用新的内存,但asarray不会。 文章来源: Numpy的用法测试

常用底部滚动选择框

匿名 (未验证) 提交于 2019-12-03 00:18:01
效果: 代码: public class SelectDialog extends BaseDialog { private OnSelectListener selectListener; private List<SelectItemBean> dataList; private WheelVerticalView wheel_select; private TextView tv_cancel; private RelativeLayout rl_select_layout; public SelectDialog(Context context) { super(context); } public SelectDialog(Context context, List dataList, boolean canceledOnTouchOutside, OnSelectListener selectListener) { super(context, canceledOnTouchOutside); this.dataList = dataList; this.selectListener = selectListener; } @Override protected int getLayoutId() { return R.layout.dlg_select; }

Springboot整合 mybatis-generator

匿名 (未验证) 提交于 2019-12-03 00:18:01
1.pom.xml文件中 生成依赖 < plugin > < groupId > org.mybatis.generator </ groupId > < artifactId > mybatis-generator-maven-plugin </ artifactId > < version > 1.3.2 </ version > < executions > < execution > < id > Generate MyBatis Artifacts </ id > < goals > < goal > generate </ goal > </ goals > </ execution > </ executions > < configuration > <!-- generator --> < configurationFile > src/main/resources/mybatis-generator/generatorConfig.xml </ configurationFile > < verbose > true </ verbose > < overwrite > true </ overwrite > </ configuration > < dependencies > < dependency > < groupId > mysql </

springboot项目 yml基本配置

匿名 (未验证) 提交于 2019-12-02 23:59:01
server : port : 9001 servlet : session : timeout : 30M context - path : / aiwtc tomcat : uri - encoding : UTF - 8 spring : datasource : name : test url : jdbc : mysql : //172.16.10.119:3306/aiwtc?useUnicode=true&characterEncoding=UTF-8&useSSL=false&allowMultiQueries=true&serverTimezone=UTC username : root password : 123456 # 使用druid数据源 type : com . alibaba . druid . pool . DruidDataSource driver - class - name : com . mysql . cj . jdbc . Driver filters : stat maxActive : 20 initialSize : 1 maxWait : 60000 minIdle : 1 timeBetweenEvictionRunsMillis : 60000 minEvictableIdleTimeMillis : 300000

多个表单如何同时验证

匿名 (未验证) 提交于 2019-12-02 23:57:01
最近公司的项目会有大量的表单需要输入很多信息。 比如下面的表单: 我知道的有两种方法: 第一种方法是通过promise.all(),通过promise进行同步验证。代码示例度娘有很多。 我使用的是第二种方法,代码如下: 1 addBaseInfo(){ 2 that.$refs['store'].validate((valid) => { //第一个表单ref="store” 5 if (valid) { 6 this.titleFormValid = true //如果通过,加个true相当于开关判断 7 } 8 }); 9 if(this.store.type==1){ 10 that.$refs['school'].validate((valid) => { //第二个表单ref='school' 11 if(valid){ 12 that.customFormValid = true //同上 13 } 14 }); 15 }else if(this.store.type==3){ 16 that.$refs['company'].validate((valid) => { 17 if(valid){ 18 that.customFormValid = true 19 } 20 }); 21 }else{ 22 that.$refs['community']

Vue 中dev上实现跨域请求

匿名 (未验证) 提交于 2019-12-02 23:40:02
'use strict' // Template version: 1.3.1 // see http://vuejs-templates.github.io/webpack for documentation. const path = require('path') module.exports = { dev: { assetsSubDirectory: 'static', assetsPublicPath: '/', proxyTable: { '/api':{ target:'http://127.0.0.1:8085/', changeOrigin:true, pathRewrite:{ '^/api':'' } } }, host: '127.0.0.1', // can be overwritten by process.env.HOST port: 8080, // can be overwritten by process.env.PORT, if port is in use, a free one will be determined autoOpenBrowser: false, errorOverlay: true, notifyOnErrors: true, poll: false, // https://webpack.js.org

Pandas处理丢失数据

匿名 (未验证) 提交于 2019-12-02 22:56:40
1、创建含NaN的矩阵 >>> dates = pd . date_range ( ‘ 20130101 ‘ , periods = 6 ) >>> df = pd . DataFrame ( np . arange ( 24 ). reshape (( 6 , 4 )), index = dates , columns =[ ‘ A ‘ , ‘ B ‘ , ‘ C ‘ , ‘ D ‘ ]) >>> df . iloc [ 0 , 1 ] = np . nan >>> df . iloc [ 1 , 2 ] = np . nan >>> print ( df ) A B C D 2013 - 01 - 01 0 NaN 2.0 3 2013 - 01 - 02 4 5.0 NaN 7 2013 - 01 - 03 8 9.0 10.0 11 2013 - 01 - 04 12 13.0 14.0 15 2013 - 01 - 05 16 17.0 18.0 19 2013 - 01 - 06 20 21.0 22.0 23 2、pd.dropna():直接去掉有NaN的行或列 >>> df . dropna ( ... axis = 0 , # 0: 对行进行操作; 1: 对列进行操作 ... how = ‘ any ‘ # ‘any‘: 只要存在 NaN 就 drop 掉;