The Unix Shell

Shell Scripts

We are finally ready to see what makes the shell such a powerful programming environment. We are going to take the commands we repeat frequently and save them in files so that we can re-run all those operations again later by typing a single command. For historical reasons, a bunch of commands saved in a file is usually called a shell script, but make no mistake: these are actually small programs.

Let’s start by going back to molecules/ and putting the following line in the file middle.sh:

$ cd molecules
$ nano middle.sh

The command nano middle.sh opens the file middle.sh within the text editor “nano” (which runs within the shell). If the file does not exist, it will be created. We can use the text editor to directly edit the file. We’ll simply insert the following line:

head -n 15 octane.pdb | tail -n 5

This is a variation on the pipe we constructed earlier: it selects lines 11-15 of the file octane.pdb. Remember, we are not running it as a command just yet: we are putting the commands in a file.

Then we save the file (using CTRL-O), and exit the text editor (using CTRL-X). Check that the directory molecules now contains a file called middle.sh.

Once we have saved the file, we can ask the shell to execute the commands it contains. Our shell is called bash, so we run the following command:

$ bash middle.sh

ATOM      9  H           1      -4.502   0.681   0.785  1.00  0.00
ATOM     10  H           1      -5.254  -0.243  -0.537  1.00  0.00
ATOM     11  H           1      -4.357   1.252  -0.895  1.00  0.00
ATOM     12  H           1      -3.009  -0.741  -1.467  1.00  0.00
ATOM     13  H           1      -3.172  -1.337   0.206  1.00  0.00

Sure enough, our script’s output is exactly what we would get if we ran that pipeline directly.

What if we want to select lines from an arbitrary file? We could edit middle.sh each time to change the filename, but that would probably take longer than just retyping the command. Instead, let’s edit middle.sh and replace octane.pdb with a special variable called $1:

$ nano middle.sh

Now, within “nano”, replace the text octane.pdb with the special variable called $1:

head -n 15 "$1" | tail -n 5

Inside a shell script, $1 means “the first filename (or other parameter) on the command line”. We can now run our script like this:

$ bash middle.sh octane.pdb

ATOM      9  H           1      -4.502   0.681   0.785  1.00  0.00
ATOM     10  H           1      -5.254  -0.243  -0.537  1.00  0.00
ATOM     11  H           1      -4.357   1.252  -0.895  1.00  0.00
ATOM     12  H           1      -3.009  -0.741  -1.467  1.00  0.00
ATOM     13  H           1      -3.172  -1.337   0.206  1.00  0.00

or on a different file like this:

$ bash middle.sh pentane.pdb

ATOM      9  H           1       1.324   0.350  -1.332  1.00  0.00
ATOM     10  H           1       1.271   1.378   0.122  1.00  0.00
ATOM     11  H           1      -0.074  -0.384   1.288  1.00  0.00
ATOM     12  H           1      -0.048  -1.362  -0.205  1.00  0.00
ATOM     13  H           1      -1.183   0.500  -1.412  1.00  0.00

We still need to edit middle.sh each time we want to adjust the range of lines, though. Let’s fix that by using the special variables $2 and $3:

$ nano middle.sh

head -n "$2" "$1" | tail -n "$3"

$ bash middle.sh pentane.pdb 20 5

ATOM     14  H           1      -1.259   1.420   0.112  1.00  0.00
ATOM     15  H           1      -2.608  -0.407   1.130  1.00  0.00
ATOM     16  H           1      -2.540  -1.303  -0.404  1.00  0.00
ATOM     17  H           1      -3.393   0.254  -0.321  1.00  0.00
TER      18              1

This works, but it may take the next person who reads middle.sh a moment to figure out what it does. We can improve our script by adding some comments at the top:

$ nano middle.sh

# Select lines from the middle of a file.
# Usage: middle.sh filename end_line num_lines
head -n "$2" "$1" | tail -n "$3"

A comment starts with a # character and runs to the end of the line. The computer ignores comments, but they’re invaluable for helping people understand and use scripts.

What if we want to process many files in a single pipeline? For example, if we want to sort our .pdb files by length, we would type:

$ wc -l *.pdb | sort -n

because wc -l lists the number of lines in the files (recall that wc stands for ‘word count’, adding the -l flag means ‘count lines’ instead) and sort -n sorts things numerically. We could put this in a file, but then it would only ever sort a list of .pdb files in the current directory. If we want to be able to get a sorted list of other kinds of files, we need a way to get all those names into the script. We can’t use $1, $2, and so on because we don’t know how many files there are. Instead, we use the special variable $@, which means, “All of the command-line parameters to the shell script.” We also should put $@ inside double-quotes to handle the case of parameters containing spaces ("$@" is equivalent to "$1" "$2" …) Here’s an example:

$ cat sorted.sh

wc -l "$@" | sort -n

$ bash sorted.sh *.pdb ../creatures/*.dat

9 methane.pdb
12 ethane.pdb
15 propane.pdb
20 cubane.pdb
21 pentane.pdb
30 octane.pdb
163 ../creatures/basilisk.dat
163 ../creatures/unicorn.dat

We have two more things to do before we’re finished with our simple shell scripts. If you look at a script like:

wc -l "$@" | sort -n

you can probably puzzle out what it does. On the other hand, if you look at this script:

# List files sorted by number of lines.
wc -l "$@" | sort -n

you don’t have to puzzle it out — the comment at the top tells you what it does. A line or two of documentation like this make it much easier for other people (including your future self) to re-use your work. The only caveat is that each time you modify the script, you should check that the comment is still accurate: an explanation that sends the reader in the wrong direction is worse than none at all.

Second, suppose we have just run a series of commands that did something useful — for example, that created a graph we’d like to use in a paper. We’d like to be able to re-create the graph later if we need to, so we want to save the commands in a file. Instead of typing them in again (and potentially getting them wrong) we can do this:

$ history | tail -n 4 > redo-figure-3.sh

The file redo-figure-3.sh now contains:

297 bash goostats -r NENE01729B.txt stats-NENE01729B.txt
298 bash goodiff stats-NENE01729B.txt /data/validated/01729.txt > 01729-differences.txt
299 cut -d ',' -f 2-3 01729-differences.txt > 01729-time-series.txt
300 ygraph --format scatter --color bw --borders none 01729-time-series.txt figure-3.png

After a moment’s work in an editor to remove the serial numbers on the commands, we have a completely accurate record of how we created that figure.

In practice, most people develop shell scripts by running commands at the shell prompt a few times to make sure they’re doing the right thing, then saving them in a file for re-use. This style of work allows people to recycle what they discover about their data and their workflow with one call to history and a bit of editing to clean up the output and save it as a shell script.

Nelle’s Pipeline: Creating a Script

An off-hand comment from her supervisor has made Nelle realize that she should have provided a couple of extra parameters to goostats when she processed her files. This might have been a disaster if she had done all the analysis by hand, but thanks to for loops, it will only take a couple of hours to re-do.

But experience has taught her that if something needs to be done twice, it will probably need to be done a third or fourth time as well. She runs the editor and writes the following:

# Calculate reduced stats for data files at J = 100 c/bp.
for datafile in "$@"
do
    echo $datafile
    bash goostats -J 100 -r $datafile stats-$datafile
done

(The parameters -J 100 and -r are the ones her supervisor said she should have used.) She saves this in a file called do-stats.sh so that she can now re-do the first stage of her analysis by typing:

$ bash do-stats.sh *[AB].txt

She can also do this:

$ bash do-stats.sh *[AB].txt | wc -l

so that the output is just the number of files processed rather than the names of the files that were processed.

One thing to note about Nelle’s script is that it lets the person running it decide what files to process. She could have written it as:

# Calculate reduced stats for  A and Site B data files at J = 100 c/bp.
for datafile in *[AB].txt
do
    echo $datafile
    bash goostats -J 100 -r $datafile stats-$datafile
done

The advantage is that this always selects the right files: she doesn’t have to remember to exclude the ‘Z’ files. The disadvantage is that it always selects just those files — she can’t run it on all files (including the ‘Z’ files), or on the ‘G’ or ‘H’ files her colleagues in Antarctica are producing, without editing the script. If she wanted to be more adventurous, she could modify her script to check for command-line parameters, and use *[AB].txt if none were provided. Of course, this introduces another tradeoff between flexibility and complexity.

head -n $2 $1
tail -n $3 $1

bash script.sh '*.pdb' 1 1

2013-11-05,deer,5
2013-11-05,rabbit,22
2013-11-05,raccoon,7
2013-11-06,rabbit,19
2013-11-06,deer,2
2013-11-06,fox,1
2013-11-07,rabbit,18
2013-11-07,bear,1

$ bash longest.sh /tmp/data pdb

history | tail -n 5 > recent.sh

# Script 1
echo *.*

# Script 2
for filename in $1 $2 $3
do
    cat $filename
done

# Script 3
echo $@.dat