Shell Scripts

Learning Objectives

  • Write a shell script that runs a command or series of commands for a fixed set of files.

  • Run a shell script from the command line.

  • Write a shell script that operates on a set of files defined by the user on the command line.

  • Create pipelines that include shell scripts you, and others, have written.

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 creating a new file, which will become our shell script:

$ cd molecules
$ nano

The command nano opens the file 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 (Ctrl-O in nano), and exit the text editor (Ctrl-X in nano). Check that the directory molecules now contains a file called

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
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.

Text vs. Whatever

We usually call programs like Microsoft Word or LibreOffice Writer “text editors”, but we need to be a bit more careful when it comes to programming. By default, Microsoft Word uses .docx files to store not only text, but also formatting information about fonts, headings, and so on. This extra information isn’t stored as characters, and doesn’t mean anything to tools like head: they expect input files to contain nothing but the letters, digits, and punctuation on a standard computer keyboard. When editing programs, therefore, you must either use a plain text editor, or be careful to save files as plain text.

What if we want to select lines from an arbitrary file? We could edit each time to change the filename, but that would probably take longer than just retyping the command. Instead, let’s edit and make it more versatile:

$ nano

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 argument) on the command line”. We can now run our script like this:

$ bash 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 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

Double-Quotes Around Arguments

For the same reason that we put the loop variable inside double-quotes, in case the filename happens to contain any spaces, we surround $1 with double-quotes.

We still need to edit each time we want to adjust the range of lines, though. Let’s fix that by using the special variables $2 and $3 for the number of lines to be passed to head and tail respectively:

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

We can now run:

$ bash pentane.pdb 15 5
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

By changing the arguments to our command we can change our script’s behaviour:

$ bash 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 a moment to figure out what it does. We can improve our script by adding some comments at the top:

$ nano
# Select lines from the middle of a file.
# Usage: bash 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 (including your future self) understand and use scripts. 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.

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 arguments to the shell script.” We also should put $@ inside double-quotes to handle the case of arguments containing spaces ("$@" is equivalent to "$1" "$2" …) Here’s an example:

$ nano
# Sort filenames by their length.
# Usage: bash one_or_more_filenames
wc -l "$@" | sort -n
$ bash *.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

Why Isn’t It Doing Anything?

What happens if a script is supposed to process a bunch of files, but we don’t give it any filenames? For example, what if we type:

$ bash

but don’t say *.dat (or anything else)? In this case, $@ expands to nothing at all, so the pipeline inside the script is effectively:

$ wc -l | sort -n

Since it doesn’t have any filenames, wc assumes it is supposed to process standard input, so it just sits there and waits for us to give it some data interactively. From the outside, though, all we see is it sitting there: the script doesn’t appear to do anything.

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 5 >

The file now contains:

297 bash goostats 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
301 history | tail -n 5 >

(goostats is a shell script which calculates some complicated statistics from a protein sample file – the first argument – and writes them to a file – the second argument. goodiffis a shell script for comparing statistics between two files, provides as arguments. Nelle’s supervisor provided them without too many explanations.)

After a moment’s work in an editor to remove the serial numbers on the commands, and to remove the final line where we called the history command, 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

Nelle’s supervisor insisted that all her analytics must be reproducible. The easiest way to capture all the steps is in a script. She runs the editor and writes the following:

# Calculate stats for data files.
for datafile in "$@"
    echo $datafile
    bash goostats $datafile stats-$datafile

She saves this in a file called so that she can now re-do the first stage of her analysis by typing:

$ bash *[AB].txt

She can also do this:

$ bash *[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 stats for Site A and Site B data files.
for datafile in *[AB].txt
    echo $datafile
    bash goostats $datafile stats-$datafile

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 arguments, and use *[AB].txt if none were provided. Of course, this introduces another tradeoff between flexibility and complexity.

Variables in Shell Scripts

In the molecules directory, imagine you have a shell script called containing the following commands:

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

While you are in the molecules directory, you type the following command:

bash '*.pdb' 1 1

Which of the following outputs would you expect to see?

  1. All of the lines between the first and the last lines of each file ending in .pdb in the molecules directory

  2. The first and the last line of each file ending in .pdb in the molecules directory

  3. The first and the last line of each file in the molecules directory

  4. An error because of the quotes around *.pdb

Variables in Shell Scripts

The correct answer is 2.

The special variables $1, $2 and $3 represent the command line arguments given to the script, such that the commands run are:

$ head -n 1 cubane.pdb ethane.pdb octane.pdb pentane.pdb propane.pdb
$ tail -n 1 cubane.pdb ethane.pdb octane.pdb pentane.pdb propane.pdb

The shell does not expand '*.pdb' because it is enclosed by quote marks. As such, the first argument to the script is '*.pdb' which gets expanded within the script by head and tail.

List Unique Species

Leah has several hundred data files, each of which is formatted like this:


An example of this type of file is given in data-shell/data/animal-counts/animals.txt.

Write a shell script called that takes any number of filenames as command-line arguments, and uses cut, sort, and uniq to print a list of the unique species appearing in each of those files separately.


# Script to find unique species in csv files where species is the second data field
# This script accepts any number of file names as command line arguments

# Loop over all files
for file in $@
	echo "Unique species in $file:"
	# Extract species names
	cut -d , -f 2 $file | sort | uniq

Find the Longest File With a Given Extension

Write a shell script called that takes the name of a directory and a filename extension as its arguments, and prints out the name of the file with the most lines in that directory with that extension. For example:

$ bash /tmp/data pdb

would print the name of the .pdb file in /tmp/data that has the most lines.


# Shell script which takes two arguments:
#    1. a directory name
#    2. a file extension
# and prints the name of the file in that directory
# with the most lines which matches the file extension.

wc -l $1/*.$2 | sort -n | tail -n 2 | head -n 1

Why Record Commands in the History Before Running Them?

If you run the command:

$ history | tail -n 5 >

the last command in the file is the history command itself, i.e., the shell has added history to the command log before actually running it. In fact, the shell always adds commands to the log before running them. Why do you think it does this?


If a command causes something to crash or hang, it might be useful to know what that command was, in order to investigate the problem. Were the command only be recorded after running it, we would not have a record of the last command run in the event of a crash.

Script Reading Comprehension

For this question, consider the data-shell/molecules directory once again. This contains a number of .pdb files in addition to any other files you may have created. Explain what a script called would do when run as bash *.pdb if it contained the following lines:

# Script 1
echo *.*
# Script 2
for filename in $1 $2 $3
    cat $filename
# Script 3
echo $@.pdb


Script 1 would print out a list of all files containing a dot in their name.

Script 2 would print the contents of the first 3 files matching the file extension. The shell expands the wildcard before passing the arguments to the script.

Script 3 would print all the arguments to the script (i.e. all the .pdb files), followed by .pdb. cubane.pdb ethane.pdb methane.pdb octane.pdb pentane.pdb propane.pdb.pdb

Debugging Scripts

Suppose you have saved the following script in a file called in Nelle’s north-pacific-gyre/2012-07-03 directory:

# Calculate stats for data files.
for datafile in "$@"
    echo $datfile
    bash goostats $datafile stats-$datafile

When you run it:

$ bash *[AB].txt

the output is blank. To figure out why, re-run the script using the -x option:

bash -x *[AB].txt

What is the output showing you? Which line is responsible for the error?


The -x flag causes bash to run in debug mode. This prints out each command as it is run, which will help you to locate errors. In this example, we can see that echo isn’t printing anything. We have made a typo in the loop variable name, and the variable datfile doesn’t exist, hence returning an empty string.

Key Points

  • Save commands in files (usually called shell scripts) for re-use.

  • bash filename runs the commands saved in a file.

  • $@ refers to all of a shell script’s command-line arguments.

  • $1, $2, etc., refer to the first command-line argument, the second command-line argument, etc.

  • Place variables in quotes if the values might have spaces in them.

  • Letting users decide what files to process is more flexible and more consistent with built-in Unix commands.

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