Linux-快捷命令整理

发表于 2023-07-30 分类于 Learn ， Alias 阅读次数：本文字数： 18k 阅读时长 ≈ 16 分钟

Introduction

快捷命令整理

方便自己，快捷他人

更是对自己学习技能的实战检验。

注意： <abspath> 指代的是需要提供对应执行脚本/命令的绝对路径；当然可以使用相对路径，或者当前执行环境中含有该命令，前提是需要提前配置好相关环境。

Getting Started


## 1. sizeg, sizem, sizek
alias sizeg='sizeg(){ echo `echo "scale=4; $1/(1024^3)" | bc` Gb;};sizeg'
alias sizem='sizem(){ echo `echo "scale=4; $1/(1024^2)" | bc` Mb;};sizem'
alias sizek='sizek(){ echo `echo "scale=4; $1/1024" | bc` Kb;};sizek'
## 2. headget
alias headget='headget(){ awk -vFS="\t" -vOFS="\t" -v name=$1 '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i; print "num","col="head[name]";"name""}NR>1{print NR,$head[name]}'\'' $2; };headget'
alias headgetcol='headgetcol(){ awk -vFS="\t" -vOFS="\t" -v name=$1 '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i; print head[name]}'\'' $2; };headgetcol' ## 获取列d
## 3. qxml
alias qxml='echo -e "job-ID\tprior\tname\tuser\tstate\tsubmit/start\tat\tqueue\tslots ja-task-ID" && printf %.s"-" {1..100};echo "" && qstat -xml| tr "\n" " " | sed "s#<job_list[^>]*>#\n#g"| sed "s#<[^>]*>##g" | column -t | sed "s/\([0-9]\{4\}-[0-9]\{2\}-[0-9]\{2\}\)T\([0-9]\{2\}:[0-9]\{2\}:[0-9]\{2\}\)/\1 \2/g"'
## 4. dfcol
alias dfcol='dfcol(){ diff -B <(headget $1 $2 | cut -f2 | sort) <(headget $1 $3 | cut -f2 | sort);};dfcol'
## 5. gsed
alias gsed='gsed(){ re_num=0;for num in `grep -n -w "$1" $2 | cut -d ":" -f1`; do sed -n "`echo "${num}-$re_num"|bc`p" $2;printf "\033[34;1mAre You Sure? [Y/n] \033[0m" && read -r input;if [[ -z $input ]];then echo -e "\033[31m???\033[0m"; elif [[ $input == "y" || $input == "Y" ]];then echo -e "sed -i \"${num}d\" $2"; sed -i "`echo "${num}-$re_num"|bc`d" $2; re_num=`echo "$re_num+1"|bc`;elif [[ $input == "n" || $input == "N" ]];then echo -e "\033[31;43mbreak off\033[0m";fi ;done;}; gsed'
## 6. mutalyzer
alias mutalyzer='mutalyzer(){ curl -X "GET" "https://v3.mutalyzer.nl/api/normalize/$1?only_variants=false" -H "accept: application/json" | jq '\''"Input Description\n\(.input_description)\nCorrected Description\n\(.corrected_description)\nProtein Description\n\(.protein.description)\nProtein Reference\n\(.protein.reference)\nProtein Predicted\n\(.protein.predicted)"'\'' | xargs echo -e | xargs -L 2 sh -c "ref=\"Protein Reference\";alt=\"Protein Predicted\";printf %.s"-" {1..79};echo -e \"\n\$0 \$1\";if [[ \"\$0 \$1\" == \$ref || \"\$0 \$1\" == \$alt ]];then echo \"\$2\"| tr \"\n\" \" \" |sed \"s/.\{10\}/& /g\" | xargs -d \" \" -n 6 echo -e;else echo -e \"\$2\"; fi";}; mutalyzer'
## 7. csed
alias csed='csed(){ sed "s/$1/\\\\\\\033[1;31m$1\\\\\\\\033[0m/g" | xargs -L 1 sh -c "echo -e \"\$@\"|tr \" \" \"\t\"" sh;};csed'
## 8. colm
alias colm='colm() { (head -n1 $1 && grep "$2" $1) | awk -vFS="\t" -v name="$3" '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i;}NR>1{print $head[name]}'\''; };colm'
## 9. format
alias format='format() { num=$(<abspath>/column -s$'\''\t'\'' -t -o "|" -x $1| wc -L); (<abspath>/column -s$'\''\t'\'' -t -o "|" -x $1|sed "s/$/\n`eval $(echo "printf %.s"-" {1..$num}")`/g")|le; };format'
## 10. wcl
alias wcl='wcl() { echo "$1" | wc -L; };wcl'
## 11. ublat
alias ublat='ublat() { (<abspath>/ucscBlat.sh $1 | sh) | sed ":a;N;s/\n/ /g;ta" | sed "s#<PRE>#\n<PRE>#;s#</PRE>#</PRE>\n#" | grep "<PRE>" | sed "s#<A[^>]*>##g;s#<[^>]*>##g;s/SPAN /SPAN\n/g;s/ browser/\nbrowser/g"; };ublat'
## 12. xfm
alias xfm='xfm() { awk -F'\''\t'\'' '\''{for(i=1;i<=NF;i++){cmd="cut -f "i" "FILENAME"|wc -L";cmd|getline len;colnum[i]=len;cmdl="printf %.s\"-\" {1.."colnum[i]+2"}";cmdl|getline line;lines[i]=line;printf "+%-"colnum[i]"s",lines[i];close(cmd);close(cmdl)}; printf "+%s\n",""}{for(i=1;i<=NF;i++){printf "| %-"colnum[i]"s ",$i};printf "|%s\n",""}END{for(i=1;i<=NF;i++){printf "+%-"colnum[i]"s",lines[i]};printf "+%s\n",""}'\'' $1 | le; };xfm'
## 13 xfm 升级版
alias xfm='xfm() { awk -F'\''\t'\'' '\''{ for(i=1;i<=NF;i++){cmd="cut -f "i" "FILENAME"|wc -L";cmd|getline len;colnum[i]=len;cmdl="printf %.s\"-\" {1.."colnum[i]+2"}";cmdl|getline line;lines[i]=line;close(cmd);close(cmdl)};}{if(FNR==1){printf ">> %-"title"s ",FILENAME;printf "<<%s\n","";close(cmdt);for(i=1;i<=NF;i++){printf "+%-"colnum[i]"s",lines[i]};printf "+%s\n","";}{for(i=1;i<=NF;i++){printf "| %-"colnum[i]"s ",$i};printf "|%s\n",""}{for(i=1;i<=NF;i++){printf "+%-"colnum[i]"s",lines[i];}printf "+%s\n","";}}'\'' $* | le; };xfm'
## 14 gcrev
alias gcrev='gcrev() { for i in `echo "$1" | rev | sed "s/\([ATGCatgcnN]\)\([ATGCatgcnN]\)/\1 \2 /g"`; do case $i in A|a) printf "%s" T ;; T|t) printf "%s" A;; G|g) printf "%s" C;; C|c) printf "%s" G;; N|n) printf "%s" N;; esac; done; echo ""; }; gcrev'

1. headget：文件列数80+；想要cut截取某一列，还得打印表头数一数哪一列？？？headget col_name file_name；可直接返回该列信息，并告知第几列

怎么用：$ headget col_name file_name

~/.bashrc 配置文件添加：

1
2

alias headget='headget(){ awk -vFS="\t" -vOFS="\t" -v name=$1 '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i; print "num","col="head[name]";"name""}NR>1{print NR,$head[name]}'\'' $2; };headget'
alias headgetcol='headgetcol(){ awk -vFS="\t" -vOFS="\t" -v name=$1 '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i; print "num","col="head[name]";"name""}NR>1{print NR,$head[name]}'\'' $2 | head -n1; };headgetcol'

用法：headget/headgetcol $col_name $file

headgetcol 可返回查询列的列数而不打印该列信息；headget 打印所查询列的整列信息

2. dfcol: 当我们只需要比较两个文件中某一列的差异时（必须是两个文件的共有列），还在cut出来另存文件来diff？？？这里搭配前面提到的 headget 快捷命令使用，提取对应的列，再diff

怎么用：$ dfcol col_name file1 file2

~/.bashrc 配置文件添加：

1	alias dfcol='dfcol(){ diff -B <(headget $1 $2 \| cut -f2 \| sort) <(headget $1 $3 \| cut -f2 \| sort);};dfcol'

用法：dfcol $col_name $file1 $file2

3. qxml: 还在qstat查询SGE任务？？？name只能显示前10个字符，都不知道哪个任务是哪个样本的分析任务（当然，可以qstat -j job_id 可查询对应分析任务的详细信息，但当只需要确认某个样本是否分析，就可能需要每个qstat -j，不便捷）

怎么用：$ qxml

~/.bashrc 配置文件添加：

1
2

alias qxml='echo -e "job-ID\tprior\tname\tuser\tstate\tsubmit/start\tat\tqueue\tslots ja-task-ID" && printf %.s"-" {1..100};echo "" && qstat -xml| tr "\n" " " | sed "s#<job_list[^>]*>#\n#g"| sed "s#<[^>]*>##g" | column -t | sed "s/\([0-9]\{4\}-[0-9]    \{2\}-[0-9]\{2\}\)T\([0-9]\{2\}:[0-9]\{2\}:[0-9]\{2\}\)/\1 \2/g"'
alias qxmlp='echo -e "job-ID\tprior\tname\tuser\tstate\tsubmit/start\tat\tqueue\tslots ja-task-ID\tpath" && printf %.s"-" {3..100};echo "" && qstat -xml| tr "\n" " " | sed "s#<job_list[^>]*>#\n#g"| sed "s#<[^>]*>##g" | column -t | sed "s/\([0-9]\{4\}-[0-9]\{2\}-[0-9]\{2\}\)T\([0-9]\{2\}:[0-9]\{2\}:[0-9]\{2\}\)/\1 \2/g" | awk -vOFS="\t" '\''{cmd="qstat -j "$1" | grep cwd | awk '\''\'\'''\''{print $2}'\''\'\'''\''";cmd|getline path;print $0,path}'\'''

qxmlp 较 qxml 多了分析任务的分析路径；直接运行 qxml/qxmlp 将会返回当前账号的任务情况

4. sizeg|sizem|sizek：就简单的字节换算

怎么用：$ sizeg|sizem|sizek b_size ## 注意：输入的是字节数，返回的是Gb|Mb|Kb

~/.bashrc 配置文件添加：

alias sizeg='sizeg(){ echo `echo "scale=4; $1/(1024^3)" | bc` Gb;};sizeg'

alias sizem='sizem(){ echo `echo "scale=4; $1/(1024^2)" | bc` Mb;};sizem'

alias sizek='sizek(){ echo `echo "scale=4; $1/1024" | bc` Kb;};sizek'

记得source

用法：sizeg/sizem/sizek $bp

5. gsed: 交互确认是否删除所匹配的行

怎么用：$ gsed [匹配值] file ## 循环确认是否删除所打印出的行；Y/y删除，N/n保留，其他值跳过，空值亦跳过

~/.bashrc 配置文件添加：

alias gsed='gsed(){ re_num=0;for num in `grep -n -w "$1" $2 | cut -d ":" -f1`; do sed -n "`echo "${num}-$re_num"|bc`p" $2;printf "\033[34;1mAre You Sure? [Y/n] \033[0m" && read -r input;if [[ -z $input ]];then echo -e "\033[31m???\033[0m"; elif [[ $input == "y" || $input == "Y" ]];then echo -e "sed -i \"${num}d\" $2"; sed -i "`echo "${num}-$re_num"|bc`d" $2; re_num=`echo "$re_num+1"|bc`;elif [[ $input == "n" || $input == "N" ]];then echo -e "\033[31;43mbreak off\033[0m";fi ;done;}; gsed'

用法：gsed $match_str $file

6.mutalyzer: 返回 Mutalyzer3 数据库所查询到的信息，版本更新，提供了 API

怎么用：$ mutalyzer "trans:c_site"

~/.bashrc 配置文件添加：

alias mutalyzer='mutalyzer(){ curl -X "GET" "https://v3.mutalyzer.nl/api/normalize/$1?only_variants=false" -H "accept: application/json" | <abspath>/jq '\''"Input Description\n\(.input_description)\nCorrected Description\n\(.corrected_description)\nProtein Description\n\(.protein.description)\nProtein Reference\n\(.protein.reference)\nProtein Predicted\n\(.protein.predicted)"'\'' | xargs echo -e | xargs -L 2 sh -c "ref=\"Protein Reference\";alt=\"Protein Predicted\";printf %.s"-" {1..79};echo -e \"\n\$0 \$1\";if [[ \"\$0 \$1\" == \$ref || \"\$0 \$1\" == \$alt ]];then echo \"\$2\"| tr \"\n\" \" \" |sed \"s/.\{10\}/& /g\" | xargs -d \" \" -n 6 echo -e;else echo -e \"\$2\"; fi";}; mutalyzer'

用法：mutalyzer "$trans:$c_site"

7. colm：获取匹配行的某一列信息

1	$ alias colm='colm() { (head -n1 $1 && grep "$2" $1) \| awk -vFS="\t" -v name="$3" '\''NR==1{for(i=1;i<=NF;i++) head[$i]=i;}NR>1{print $head[name]}'\''; };colm'

第一个参数：文件名第二个参数：匹配存在该字符串的行第三个参数：返回匹配行的某一列信息

用法：colm $file $match_str $col

8. format：对文本文件进行格式化输出

alias format='format() { num=$(<abspath>/column -s$'\''\t'\'' -t -o "|" -x $1| wc -L); (<abspath>/column -s$'\''\t'\'' -t -o "|" -x $1|sed "s/$/\n`eval $(echo "printf %.s"-" {1..$num}")`/g")|le; };format'

用法：format $file

9. wcl: 判断字符串长度

1
2
3

alias wcl='wcl() { echo "$1" | wc -L; };wcl'
## usage:
$ wcl "str"

10. Glow：终端上的markdown查看器

1	$ conda create -n Glow -c dnachun glow-md -y

11. ublat

ucsc blat 本地化

alias ublat='ublat() { (<abspath>/ucscBlat.sh $1 | sh) | sed ":a;N;s/\n/ /g;ta" | sed "s#<PRE>#\n<PRE>#;s#</PRE>#</PRE>\n#" | grep "<PRE>" | sed "s#<A[^>]*>##g;s#<[^>]*>##g;s/SPAN /SPAN\n/g;s/ browser/\nbrowser/g"; };ublat'
$ ublat GCACAAGCAGTGCTATGAGTGGCAGTCATCAGGACCTCAGTGTGATACAGCCAATTGTAAAAGACTGCAAAGAGGAACCAACCGGTGAGCCCTCTCCTAA
## output
   ACTIONS      QUERY   SCORE START   END QSIZE IDENTITY  CHROM  STRAND  START       END   SPAN
-----------------------------------------------------------------------------------------------
browser details YourSeq    75     1    75   100   100.0%  chr12  +    70189051  70189125     75
browser details YourSeq    28    73   100   100   100.0%  chr12  +    66221779  66221806     28

## ucscBlat.sh
seq=$1
echo 'curl '\''https://genome.ucsc.edu/cgi-bin/hgBlat'\'' \
  -H '\''Accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7'\'' \
  -H '\''Accept-Language: zh-CN,zh;q=0.9,en;q=0.8'\'' \
  -H '\''Cache-Control: max-age=0'\'' \
  -H '\''Connection: keep-alive'\'' \
  -H '\''Content-Type: multipart/form-data; boundary=----WebKitFormBoundaryN2EGAypLqBwsLg9v'\'' \
  -H '\''Cookie: hguid.genome-japan=723668884_OY1HNADbTpsXcALt7NvYvTdG79Qp; _ga=GA1.2.471529949.1663819139; _ga_PWFD1NPDNM=GS1.1.1664180680.2.1.1664181280.0.0.0; hguid=1400796865_VQ96g5e3qnvra4gymb0CdJgpTiDf; _gid=GA1.2.2126454113.1676274745; _gat=1'\'' \
  -H '\''Origin: https://genome.ucsc.edu'\'' \
  -H '\''Referer: https://genome.ucsc.edu/cgi-bin/hgBlat'\'' \
  -H '\''Sec-Fetch-Dest: document'\'' \
  -H '\''Sec-Fetch-Mode: navigate'\'' \
  -H '\''Sec-Fetch-Site: same-origin'\'' \
  -H '\''Sec-Fetch-User: ?1'\'' \
  -H '\''Upgrade-Insecure-Requests: 1'\'' \
  -H '\''User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36'\'' \
  -H '\''sec-ch-ua: "Chromium";v="110", "Not A(Brand";v="24", "Google Chrome";v="110"'\'' \
  -H '\''sec-ch-ua-mobile: ?0'\'' \
  -H '\''sec-ch-ua-platform: "Windows"'\'' \
  --data $'\''------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="hgsid"\r\n\r\n1569233731_63ApO5jAfET6mwe2b4l7U8yamDV1\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="changeInfo"\r\n\r\n\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="org"\r\n\r\nHuman\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="db"\r\n\r\nhg19\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="type"\r\n\r\nBLATs guess\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="sort"\r\n\r\nquery,score\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="output"\r\n\r\nhyperlink\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="userSeq"\r\n\r\n'$seq'\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="boolshad.allResults"\r\n\r\n0\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="Submit"\r\n\r\nSubmit\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v\r\nContent-Disposition: form-data; name="seqFile"; filename=""\r\nContent-Type: application/octet-stream\r\n\r\n\r\n------WebKitFormBoundaryN2EGAypLqBwsLg9v--\r\n'\'' \
  --compressed' #| sed ":a;N;s/\n/ /g;ta" | sed "s#<PRE>#\n<PRE>#;s#</PRE>#</PRE>\n#" | grep "<PRE>" | sed "s#<A[^>]*>##g;s#<[^>]*>##g;s/SPAN /SPAN\n/g;s/ browser/\nbrowser/g"

12. xfm

格式化输出表格型数据；即给文本文件添加类表格显示

alias xfm='xfm() { awk -F'\''\t'\'' '\''{for(i=1;i<=NF;i++){cmd="cut -f "i" "FILENAME"|wc -L";cmd|getline len;colnum[i]=len;cmdl="printf %.s\"-\" {1.."colnum[i]+2"}";cmdl|getline line;lines[i]=line;printf "+%-"colnum[i]"s",lines[i];close(cmd);close(cmdl)}; printf "+%s\n",""}{for(i=1;i<=NF;i++){printf "| %-"colnum[i]"s ",$i};printf "|%s\n",""}END{for(i=1;i<=NF;i++){printf "+%-"colnum[i]"s",lines[i]};printf "+%s\n",""}'\'' $1 | le; };xfm'
$ xfm test.xls
+----------+----------+-----------+-----------+-----------+------------+
| Chr_Left | Pos_Left | Gene_Left | Chr_Right | Pos_Right | Gene_Right |
+----------+----------+-----------+-----------+-----------+------------+
| chr2     | 42526812 | EML4      | chr2      | 29448241  | ALK        |
+----------+----------+-----------+-----------+-----------+------------+
$ cat test.xls
Chr_Left	Pos_Left	Gene_Left	Chr_Right	Pos_Right	Gene_Right
chr2	42526812	EML4	chr2	29448241	ALK

13. gcrev

返回序列的反向互补序列

1
2
3

$ alias gcrev='gcrev() { for i in `echo "$1" | rev | sed "s/\([ATGCatgcnN]\)\([ATGCatgcnN]\)/\1 \2 /g"`; do case $i in A|a) printf "%s" T ;; T|t) printf "%s" A;; G|g) printf "%s" C;; C|c) printf "%s" G;; N|n) printf "%s" N;; esac; done; echo ""; }; gcrev'
$ gcrev AGGCAGGAAAATCACTTGAACCCAGGAGGCAGAGATTGCAGTGAGCCGAGATCACACCACTGCACTCCAGCCAGGGCGACAGAGTGAGACTC
GAGTCTCACTCTGTCGCCCTGGCTGGAGTGCAGTGGTGTGATCTCGGCTCACTGCAATCTCTGCCTCCTGGGTTCAAGTGATTTTCCTGCCT

References

。。。。。。

Introduction

Getting Started

1. headget：文件列数80+；想要cut截取某一列，还得打印表头数一数哪一列？？？headget col_name file_name；可直接返回该列信息，并告知第几列

2. dfcol: 当我们只需要比较两个文件中某一列的差异时（必须是两个文件的共有列），还在cut出来另存文件来diff？？？这里搭配前面提到的 headget 快捷命令使用，提取对应的列，再diff

4. sizeg|sizem|sizek：就简单的字节换算

5. gsed: 交互确认是否删除所匹配的行

6.mutalyzer: 返回 Mutalyzer3 数据库所查询到的信息，版本更新，提供了 API

7. colm： 获取匹配行的某一列信息

8. format：对文本文件进行格式化输出

9. wcl: 判断字符串长度

10. Glow：终端上的markdown查看器

11. ublat

12. xfm

13. gcrev

References

7. colm：获取匹配行的某一列信息