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提升开发效率N倍的20+命令行神器，赶紧收藏了

2020-09-17  本文已影响0人  Java入门到入坟

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背景

本文主要来源于在之前公司的小组内部的一个小分享，整理成一篇文章po出来。题目叫 “Shell 助力开发效率提升”，更切题的应该是叫“命令行”提升开发效率，这里并没有讲到 Shell 编程，而是主要介绍 Linux 或者 Mac 下常用的一些基本工具命令来帮助处理一些日常事务。

通过本文的介绍，你应该对相关命令有一个初步的了解，知道比如用什么命令可以完成怎样的操作， 至于具体的参数，不需要刻意地背诵，等到需要用到的时候，再去 cmd --help 或者 man cmd，用得多了，常用的命令也就自然记住了。

本文首先介绍了 Linux/Mac 下一些常用的命令行工具，然后用具体的示例阐述了常用的命令用法，最后通过一两个案例来说明这些工具的强大之处：

Mac 环境

Shell 基础命令

➜  .oh-my-zsh git:(master)$ whereis ls
/bin/ls
➜  .oh-my-zsh git:(master)$ which ls
ls: aliased to ls -G

rm， mkdir， mv， cp， cd， ls， ln， file， stat， wc(-l/w/c)， head， more， tail， cat...

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（我博客有目录，公众号上木有）直达你想要了解的命令。

find, grep, xargs, cut, paste, comm
join, sort, uniq, tr, sed, awk

find

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

grep 'partner' ./*.scala -l
grep -e 'World' -e 'first' -i -R ./  (-e: or)

xargs

echo "helloworldhellp" | cut -c1-10
cut -d， -f2-8 csu.db.export.csv

cut

echo "helloworldhellp" | cut -c1-10cut -d， -f2-8 csu.db.export.csv

paste

    ➜  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    4

join

类似sql中的 ...inner join ...on ...， -t 分隔符，默认为空格或tab

➜  Documents$ cat j1
1 11
2 22
3 33
4 44
5 55
➜  Documents$ cat j2
one     1   0
one     2   1
two     4   2
three   5   3
one1    5   4
➜  Documents$ join -1 1 -2 3 j1 j2
1 11 one 2
2 22 two 4
3 33 three 5
4 44 one1 5

comm

    ➜  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

➜  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     1

uniq

➜  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

➜  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

    ➜  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

  1. 执行begin
  2. 对输入每一行执行 pattern{ commands }， pattern 可以是 正则/reg exp/， 关系运算等
  3. 处理完毕， 执行 end
➜  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.log
106.38.187.225 - - [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" - 0.000
106.38.187.225 - - [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" - 0.000
10.130.64.143 - - [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 0.205
10.130.64.143 - - [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 0.004
10.130.64.143 - - [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
#or
head -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 -c
8237 201703
15051 201704
16083 201705
18561 201706
22723 201707
19345 201708

其他实际案例 ip block

案例: db数据订正

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（就算支持，直接改也有风险的，还是先备份再修改留个“后悔药”）。

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:

  1. 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/%';
  1. 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'
# 直接替换原文件， 可以sed -i ".bak" 替换时保留原始备份文件
sed -i "" 's|https://www.tanglei.name/upload/photos/[0-9]\{1,\}/|http://www.tanglei.me|g' customers.csv
  1. 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

老方式: 需要启play环境，慢。新方式直接命令行解决。

sbt "project site" consoleQuick
import play.api.libs._
val sec = "secret...secret"
var uid = "10086"
Crypto.sign(s"uid=$uid"， sec.getBytes("UTF-8")) + s"-uid=$uid"

➜  Documents$  ~/stdcookie.sh 97522
918xxxxdf64abcfcxxxxc465xx7554dxxxx21e-uid=97522
➜  Documents$ cat ~/stdcookie.sh
#!/bin/bash ##  cannot remove this line
uid=$1
hash=`echo -n "uid=$uid" | openssl dgst -sha1 -hmac "secret...secret"`
echo "$hash-uid=$uid"

➜  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

➜  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=

➜  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
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