标签：匹配 xargs cdc 来源 proc doc modify key aik
? zsh
? on-my-zsh
? plugin
? git
? autojump
? osx(man-preview/quick-look/pfd(print Finder director)/cdf(cd Finder))
? 常用快捷键(bindkey)
? 演示: 高亮/git/智能补全/跳转(j,d)…
关于Mac相关的技巧, 更多的可以参考以下三篇文章: Mac 软件推荐, Mac 软件推荐(续) -- !程序猿篇, 和 Mac 软件推荐(续)之程序猿篇
? which/whereis, 常用 whatis, man, --help
? ? .oh-my-zsh git:(master)$ whereis ls
? /bin/ls
? ? .oh-my-zsh git:(master)$ which ls
ls: aliased to ls -G? 基本文件目录操作
rm, mkdir, mv, cp, cd, ls, ln, file, stat, wc(-l/w/c), head, more, tail, cat...? 利器 管道: |
Shell 文本处理
这里就是通过案例讲了一下12个命令的大致用法和参数, 可以通过点击右边的目录直达你想要了解的命令.
find, grep, xargs, cut, paste, comm
join, sort, uniq, tr, sed, awkfind
? 常用参数
? 文件名 -name, 文件类型-type, 查找最大深度-maxdepth
? 时间过滤(create/access/modify) -[cam]time
? 执行动作 -exec
? 示例
? find ./ -name "*.json"
? find . -maxdepth 7 -name "*.json" -type f
? find . -name "*.log.gz" -ctime +7 -size +1M -delete (atime/ctime/mtime)
find . -name "*.scala" -atime -7 -exec du -h {} \;grep
? 常用参数
? -v(invert-match),
? -c(count),
? -n(line-number),
? -i(ignore-case),
? -l, -L, -R(-r, —recursive), -e
? 示例
grep ‘partner‘ ./*.scala -l
grep -e ‘World‘ -e ‘first‘ -i -R ./ (-e: or)? 相关命令: grep -z / zgrep / zcat xx | grep
xargs
? 常用参数
? -n(每行列数),
? -I(变量替换)
? -d(分隔符), Mac 不支持, 注意与GNU版本的区别
? 示例
find . -type f -name "*.jpg" | xargs -n1 -I {} du -sh {}cut
? 常用参数
? -b(字节)
? -c(字符)
? -f(第几列), -d(分隔符), f范围: n, n-, -m, n-m
? 示例
echo "helloworldhellp" | cut -c1-10
cut -d, -f2-8 csu.db.export.csvpaste
? 常用参数
? -d 分隔符
? -s 列转行
? 示例
? ? Documents$ cat file1 1 11
? 2 22
? 3 33
? 4 44
? ? Documents$ cat file2
? one 1
? two 2
? three 3
? one1 4
?
? ? Documents$ paste -d, file1 file2 1 11,one 1
? 2 22,two 2
? 3 33,three 3
? 4 44,one1 4
? ? Documents$ paste -s -d: file1 file2
? a 11:b bb:3 33:4 44
one 1:two 2:three 3:one1 4join
类似sql中的 ...inner join ...on ..., -t 分隔符, 默认为空格或tab
? Documents$ cat j11 112 223 334 445 55? Documents$ cat j2
one 1 0one 2 1two 4 2three 5 3one1 5 4? Documents$ join -1 1 -2 3 j1 j21 11 one 22 22 two 43 33 three 54 44 one1 5comm
? 常用参数
? 用法 comm [-123i] file1 file2
? 字典序列, 3列: 只在file1/file2/both
? - 去掉某列, i 忽略大小写
? 示例
? ? Documents$ seq 1 5 >file11
? ? Documents$ seq 2 6 >file22
? ? Documents$ cat file11 1
? 2
? 3
? 4
? 5
? ? Documents$ cat file22 2
? 3
? 4
? 5
? 6
? ? Documents$ comm file11 file22 1
? 2
? 3
? 4
? 5
? 6
? ? Documents$ comm -1 file11 file22 2
? 3
? 4
? 5
? 6
? ? Documents$ comm -2 file11 file22 1
? 2
? 3
? 4
? 5
? Documents$ comm -23 file11 file22 1相关命令 diff(类似git diff)
sort
? 常用参数
? -d, —dictionary-order
? -n, —numeric-sort
? -r, —reverse
? -b, —ignore-leading-blanks
? -k, —key
? 示例
? ? Documents$ cat file2
? one 1
? two 2
? three 3
? one1 4
? ? Documents$ sort file2
? one 1
? one1 4
? three 3
? two 2
? ? Documents$ sort -b -k2 -r file2
? one1 4
? three 3
? two 2
one 1uniq
? 常用参数
? -c 重复次数
? -d 重复的
? -u 没重复的
? -f 忽略前几列
? 示例
? ? Documents$ cat file4 11
? 22
? 33
? 11
? 11
? ? Documents$ sort file4 | uniq -c 3 11
? 1 22
? 1 33
? ? Documents$ sort file4 | uniq -d
? 11
? ? Documents$ sort file4 | uniq -u 22
? 33
? ? Documents$ cat file3
? one 1
? two 1
? three 3
? one1 4
? ? Documents$ uniq -c -f 1 file3 2 one 1
? 1 three 3
1 one1 4注意: uniq比较相邻的是否重复, 一般与sort联用
tr
? 常用参数
? -c 补集
? -d 删除
? -s 压缩相邻重复的
? 示例
? ? Documents$ echo ‘1111234444533hello‘ | tr ‘[1-3]‘ ‘[a-c]‘
? aaaabc44445cchello
? ? Documents$ echo ‘1111234444533hello‘ | tr -d ‘[1-3]‘
? 44445hello
? ? Documents$ echo ‘1111234444533hello‘ | tr -dc ‘[1-3]‘
? 11112333
? ? Documents$ echo ‘1111234444533hello‘ | tr -s ‘[0-9]‘
? 123453hello
? ? Documents$ echo ‘helloworld‘ | tr ‘[:lower:]‘ ‘[:upper:]‘
HELLOWORLD
sed
? 常用参数
? -d 删除
? -s 替换, g 全局
? -e 多个命令叠加
? -i 修改原文件(Mac下加参数 “”, 备份)
? 示例
? ? Documents$ cat file2
? one 1
? two 2
? three 3
? one1 4
? ? Documents$ sed "2,3d" file2
? one 1
? one1 4
? ? Documents$ sed ‘/one/d‘ file2
? two 2
? three 3
? ? Documents$ sed ‘s/one/111/g‘ file2 111 1
? two 2
? three 3
? 1111 4
? #将one替换成111 并将含有two的行删除
? ? Documents$ sed -e ‘s/one/111/g‘ -e ‘/two/d‘ file2 111 1
? three 3
? 1111 4
? # ()标记(转义), \1 引用
? ? Documents$ sed ‘s/\([0-9]\)/\1.html/g‘ file2
? one 1.html
? two 2.html
? three 3.html
? one1.html 4.html # 与上面一样 & 标记匹配的字符
? ? Documents$ sed ‘s/[0-9]/&.html/g‘ file2
? one 1.html
? two 2.html
? three 3.html
? one1.html 4.html
? ? Documents$ cat mobile.csv "13090246026"
? "18020278026"
? "18520261021"
? "13110221022"
? ? Documents$ sed ‘s/\([0-9]\{3\}\)[0-9]\{4\}/\1xxxx/g‘ mobile.csv "130xxxx6026"
? "180xxxx8026"
? "185xxxx1021"
"131xxxx1022"awk
? 基本参数和语法
? NR 行号, NF 列数量
? $1 第1列, $2, $3…
? -F fs fs分隔符，字符串或正则
? 语法: awk ‘BEGIN{ commands } pattern{ commands } END{ commands }‘, 流程如下:
e. 执行begin
f. 对输入每一行执行 pattern{ commands }, pattern 可以是 正则/reg exp/, 关系运算等
g. 处理完毕, 执行 end
? 示例
? ? Documents$ cat file5 11 11 aa cc 22 22 bb 33 33 d 11 11
? 11 11
? #行号, 列数量, 第3列
? ? Documents$ awk ‘{print NR"("NF"):", $3}‘ file5 1(4): aa 2(3): bb 3(3): d 4(2): 5(2): #字符串分割, 打印1，2列
? ? Documents$ awk -F"xxxx" ‘{print $1, $2}‘ mobile.csv "130 6026"
? "180 8026"
? "185 1021"
? "131 1022"
? #添加表达式
? ? Documents$ awk ‘$1>=22 {print NR":", $3}‘ file5 2: bb 3: d #累加1到36，奇数，偶数
? ? Documents$ seq 36 | awk ‘BEGIN{sum=0; print "question:"} {print $1" +"; sum+=$1} END{print "="; print sum}‘ | xargs | sed ‘s/+ =/=/‘
? question: 1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 + 9 + 10 + 11 + 12 + 13 + 14 + 15 + 16 + 17 + 18 + 19 + 20 + 21 + 22 + 23 + 24 + 25 + 26 + 27 + 28 + 29 + 30 + 31 + 32 + 33 + 34 + 35 + 36 = 666
? ? Documents$ seq 36 | awk ‘BEGIN{sum=0; print "question:"} $1 % 2 ==1 {print $1" +"; sum+=$1} END{print "="; print sum}‘ | xargs | sed ‘s/+ =/=/‘
? question: 1 + 3 + 5 + 7 + 9 + 11 + 13 + 15 + 17 + 19 + 21 + 23 + 25 + 27 + 29 + 31 + 33 + 35 = 324
? ? Documents$ seq 36 | awk ‘BEGIN{sum=0; print "question:"} $1 % 2 !=1 {print $1" +"; sum+=$1} END{print "="; print sum}‘ | xargs | sed ‘s/+ =/=/‘
question: 2 + 4 + 6 + 8 + 10 + 12 + 14 + 16 + 18 + 20 + 22 + 24 + 26 + 28 + 30 + 32 + 34 + 36 = 342其他高级语法: for, while 等, 各种函数等, 本身awk是一个强大的语言, 可以掌握一些基本的用法.
实际应用
日志统计分析
例如拿到一个nginx日志文件, 可以做很多事情, 比如看哪些请求是耗时最久的进而进行优化, 比如看每小时的”PV”数 等等.
? Documents$ head -n5 std.nginx.log106.38.187.225 - - [20/Feb/2017:03:31:01 +0800] www.tanglei.name "GET /baike/208344.html HTTP/1.0" 301 486 "-" "Mozilla/5.0 (compatible; MSIE 7.0; Windows NT 5.1; .NET CLR 1.1.4322) 360JK yunjiankong 975382" "106.38.187.225, 106.38.187.225" - 0.000106.38.187.225 - - [20/Feb/2017:03:31:02 +0800] www.tanglei.name "GET /baike/208344.html HTTP/1.0" 301 486 "-" "Mozilla/5.0 (compatible; MSIE 7.0; Windows NT 5.1; .NET CLR 1.1.4322) 360JK yunjiankong 975382" "106.38.187.225, 106.38.187.225" - 0.00010.130.64.143 - - [20/Feb/2017:03:31:02 +0800] stdbaike.bdp.cc "POST /baike/wp-cron.php?doing_wp_cron=1487532662.2058920860290527343750 HTTP/1.1" 200 182 "-" "WordPress/4.5.6; http://www.tanglei.name/baike" "10.130.64.143" 0.205 0.20510.130.64.143 - - [20/Feb/2017:03:31:02 +0800] www.tanglei.name "GET /external/api/login-status HTTP/1.0" 200 478 "-" "-" "10.130.64.143" 0.003 0.00410.130.64.143 - - [20/Feb/2017:03:31:02 +0800] www.tanglei.name "GET /content_util/authorcontents?count=5&offset=0&israndom=1&author=9 HTTP/1.0" 200 11972 "-" "-" "10.130.64.143" 0.013 0.013上面是nginx的一个案例, 例如希望找到top 10 请求的path:
head -n 10000 std.nginx.log | awk ‘{print $8 "," $10}‘ | grep ‘,404‘ | sort | uniq -c | sort -nr -k1 | head -n 10#orhead -n 10000 std.nginx.log | awk ‘$10==404 {print $8}‘ |sort | uniq -c | sort -nr -k1 | head -n 10当然, 你可能一次不会直接处理成功, 一般会先少拿一部分数据进行处理看逻辑是否正常, 或者你可以缓存一些中间结果.
cat std.nginx.log | awk ‘{print $8 "," $10}‘ | grep ‘,404‘ >404.log
sort 404.log | uniq -c | sort -nr -k1 | head -n 10
再比如每小时请求数量, 请求耗时等等
? Documents$ head -n 100000 std.nginx.log | awk -F: ‘{print $1 $2}‘ | cut -f3 -d/ | uniq -c8237 20170315051 20170416083 20170518561 20170622723 20170719345 201708其他实际案例 ip block
案例: db数据批处理
背景: 因为某服务bug, 导致插入到db的图片路径不对, 需要将形如(安全需要已经将敏感数据替换)
https://www.tanglei.name/upload/photos/129630//internal-public/shangtongdai/2017-02-19-abcdefg-eb85-4c24-883e-hijklmn.jpg
替换成
http://www.tanglei.me/internal-public/shangtongdai/2017-02-19-abcdefg-eb85-4c24-883e-hijklmn.jpg, 因为mysql等db貌似不支持直接正则的替换, 所以不能够很方便的进行写sql进行替换.
当然将数据导出, 然后写python等脚本处理也是一种解决方案, 但如果用上面的命令行处理, 只需要几十秒即可完成.
步骤:
准备数据
select id, photo_url_1, photo_url_2, photo_url_3 from somedb.sometable where
photo_url_1 like ‘https://www.tanglei.name/upload/photos/%//internal-public/%‘ or
photo_url_2 like ‘https://www.tanglei.name/upload/photos/%//internal-public/%‘ or
photo_url_3 like ‘https://www.tanglei.name/upload/photos/%//internal-public/%‘;2.替换原文件
一般在用sed替换的时候, 先测试一下是否正常替换.
``` #测试是否OK
. head -n 5 customers.csv | sed ‘s|https://www.tanglei.name/upload/photos/[0-9]\{1,\}/|http://www.tanglei.me|g‘
sed -i "" ‘s|https://www.tanglei.name/upload/photos/[0-9]\{1,\}/|http://www.tanglei.me|g‘ customers.csv
拼接sql, 然后执行awk -F, ‘{print "update sometable set photo_url_1 = " $2, ", photo_url_2 = " $3, ", photo_url_3 = " $4, " where id = " $1 ";" }‘ customers.csv > customer.sql #然后执行sql 即可
其他
? play framework session
? 老方式: 需要启play环境, 慢
sbt "project site" consoleQuickimport play.api.libs._val sec = "secret...secret"var uid = "97522"Crypto.sign(s"uid=$uid", sec.getBytes("UTF-8")) + s"-uid=$uid"
? 新方式:? Documents$ ~/stdcookie.sh 97522918xxxxdf64abcfcxxxxc465xx7554dxxxx21e-uid=97522? Documents$ cat ~/stdcookie.sh#!/bin/bash ## cannot remove this lineuid=$1hash=echo -n "uid=$uid" | openssl dgst -sha1 -hmac "secret...secret"echo "$hash-uid=$uid"
? 统计文章单词频率: 下面案例统计了川普就职演讲原文中词频最高的10个词.? ? Documents$ head -n3 chuanpu.txt
? Chief Justice Roberts, President Carter, President Clinton, President Bush, President Obama, fellow Americans and people of the world, thank you.
?
? We, the citizens of America, are now joined in a great national effort to rebuild our country and restore its promise for all of our people. Together we will determine the course of America and the world for many, many years to come.
? ? Documents$ cat chuanpu.txt | tr -dc ‘a-zA-Z ‘ | xargs -n 1 | sort | uniq -c | sort -nr -k1 | head -n 20
? 65 the 63 and 48 of 46 our 42 will 37 to 21 We 20 is 18 we 17 America 15 a 14 all 13 in
? 13 for
13 be 13 are 10 your 10 not 10 And 10 American
? 随机数? ? Documents$ cat /dev/urandom | LC_CTYPE=C tr -dc ‘a-zA-Z0-9‘ | fold -w 32 | head -n 5
? cpBnvC0niwTybSSJhUUiZwIz6ykJxBvu
? VDP56NlHnugAt2yDySAB9HU2Nd0LlYCW 0WEDzpjPop32T5STvR6K6SfZMyT6KvAI
? a9xBwBat7tJVaad279fOPdA9fEuDEqUd
? hTLrOiTH5FNP2nU3uflsjPUXJmfleI5c
? ? Documents$ cat /dev/urandom | head -c32 | base64
WoCqUye9mSXI/WhHODHDjzLaSb09xrOtbrJagG7Kfqc=
? 图片处理压缩, 可批量改图片大小等等 sips? ? linux-shell-more-effiency$ sips -g all which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? pixelWidth: 280
? pixelHeight: 81
? typeIdentifier: public.png
? format: png
? formatOptions: default
? dpiWidth: 72.000
? dpiHeight: 72.000
? samplesPerPixel: 4
? bitsPerSample: 8
? hasAlpha: yes
? space: RGB
? profile: DELL U2412M
? ? linux-shell-more-effiency$ sips -Z 250 which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? ? linux-shell-more-effiency$ sips -g all which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? pixelWidth: 250
? pixelHeight: 72
? typeIdentifier: public.png
? format: png
? formatOptions: default
? dpiWidth: 72.000
? dpiHeight: 72.000
? samplesPerPixel: 4
? bitsPerSample: 8
? hasAlpha: yes
? space: RGB
? profile: DELL U2412M
? ? linux-shell-more-effiency$ sips -z 100 30 which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? ? linux-shell-more-effiency$ sips -g pixelWidth -g pixelHeight which-whereis.png
? /Users/tanglei/Documents/linux-shell-more-effiency/which-whereis.png
? pixelWidth: 30
pixelHeight: 100
Reference
? Linux工具快速教程
? Linux命令大全
? Advanced Bash-Scripting Guide
? UNIX环境高级编程
标签：匹配 xargs cdc 来源 proc doc modify key aik
原文地址：https://blog.51cto.com/14890678/2516473
