CyVerse_logo

Home_Icon Learning Center Home

Introducing the Shell

Questions:

  • What is a command shell and why would I use one?

Objectives:

  • Explain how the shell relates to the keyboard, the screen, the operating system, and users’ programs.

  • Explain when and why command-line interfaces should be used instead of graphical interfaces.

Keypoints:

  • Explain the steps in the shell’s read-run-print cycle.

  • Most commands take options (flags) which begin with a -.

  • Identify the actual command, options, and filenames in a command-line call.

  • Demonstrate the use of tab completion and explain its advantages.

  • A shell is a program whose primary purpose is to read commands and run other programs.

  • The shell’s main advantages are its high action-to-keystroke ratio, its support for automating repetitive tasks, and its capacity to access networked machines.

  • The shell’s main disadvantages are its primarily textual nature and how cryptic its commands and operation can be.

Background

Humans and computers commonly interact in many different ways, such as through a keyboard and mouse, touch screen interfaces, or using speech recognition systems. The most widely used way to interact with personal computers is called a graphical user interface (GUI). With a GUI, we give instructions by clicking a mouse and using menu-driven interactions.

While the visual aid of a GUI makes it intuitive to learn, this way of delivering instructions to a computer scales very poorly. Imagine the following task: for a literature search, you have to copy the third line of one thousand text files in one thousand different directories and paste it into a single file. Using a GUI, you would not only be clicking at your desk for several hours, but you could potentially also commit an error in the process of completing this repetitive task. This is where we take advantage of the Unix shell. The Unix shell is both a command-line interface (CLI) and a scripting language, allowing such repetitive tasks to be done automatically and fast. With the proper commands, the shell can repeat tasks with or without some modification as many times as we want. Using the shell, the task in the literature example can be accomplished in seconds.

The Shell:

The shell is a program where users can type commands. With the shell, it’s possible to invoke complicated programs like climate modeling software or simple commands that create an empty directory with only one line of code. The most popular Unix shell is Bash (the Bourne Again SHell — so-called because it’s derived from a shell written by Stephen Bourne). Bash is the default shell on most modern implementations of Unix and in most packages that provide Unix-like tools for Windows.

Using the shell will take some effort and some time to learn. While a GUI presents you with choices to select, CLI choices are not automatically presented to you, so you must learn a few commands like new vocabulary in a language you’re studying. However, unlike a spoken language, a small number of “words” (i.e. commands) gets you a long way, and we’ll cover those essential few today.

The grammar of a shell allows you to combine existing tools into powerful pipelines and handle large volumes of data automatically. Sequences of commands can be written into a script, improving the reproducibility of workflows.

In addition, the command line is often the easiest way to interact with remote machines and supercomputers. Familiarity with the shell is near essential to run a variety of specialized tools and resources including high-performance computing systems. As clusters and cloud computing systems become more popular for scientific data crunching, being able to interact with the shell is becoming a necessary skill. We can build on the command-line skills covered here to tackle a wide range of scientific questions and computational challenges.

Getting Started

Opening The Shell Via CyVerse

Follow along with Tuesday’s demo to start the RStudio environment with the input for this lesson.

For your RStudio instance, set the input folder to /iplant/home/shared/ag2pi_workshop

The login screen should look like this:

R Console

And we will be using the shell inside RStudio for these lessons.

R Shell

When the shell is first opened, you are presented with a prompt, indicating that the shell is waiting for input.

$

The shell typically uses $ as the prompt, but may use a different symbol. In the examples for this lesson, we’ll show the prompt as $. Most importantly: when typing commands, either from these lessons or from other sources, do not type the prompt, only the commands that follow it.

So let’s try our first command, ls which is short for listing. This command will list the contents of the current directory:

$ ls

input  kitematic

Command not found

If the shell can’t find a program whose name is the command you typed, it will print an error message such as:

$ ks

ks: command not found

This might happen if the command was mis-typed or if the program corresponding to that command is not installed.

Working With Files and Directories

Questions:

  • How can I create, copy, and delete files and directories?

  • How can I edit files?

Objectives:

  • Create a directory hierarchy that matches a given diagram.

  • Create files in that hierarchy using an editor or by copying and renaming existing files.

  • Delete, copy and move specified files and/or directories.

Keypoints:

  • cp [old] [new] copies a file.

  • mkdir [path] creates a new directory.

  • mv [old] [new] moves (renames) a file or directory.

  • rm [path] removes (deletes) a file.

  • * matches zero or more characters in a filename, so *.txt matches all files ending in .txt.

  • ? matches any single character in a filename, so ?.txt matches a.txt but not any.txt.

  • Use of the Control key may be described in many ways, including Ctrl-X, Control-X, and ^X.

  • The shell does not have a trash bin: once something is deleted, it’s really gone.

  • Most files’ names are something.extension. The extension isn’t required, and doesn’t guarantee anything, but is normally used to indicate the type of data in the file.

  • Depending on the type of work you do, you may need a more powerful text editor than Nano.

Creating Directories

We now know how to explore files and directories, but how do we create them in the first place?

Step one: see where we are and what we already have

Let’s go back to our ag2pi_workshop directory in the input directory and use ls -F to see what it contains:

$ pwd

/home/rstudio/input/ag2pi_workshop

$ ls -F

ag-data/  creatures/  data/  north-pacific-gyre/  notes.txt  pizza.cfg  solar.pdf  writing/

Step two: Create a directory

Let’s create a new directory called thesis using the command mkdir thesis (which has no output):

$ mkdir thesis

As you might guess from its name, mkdir means ‘make directory’. Since thesis is a relative path (i.e., does not have a leading slash, like /what/ever/thesis), the new directory is created in the current working directory:

$ ls -F

creatures/  data/  molecules/  north-pacific-gyre/  notes.txt  pizza.cfg  solar.pdf  thesis/  writing/

Since we’ve just created the thesis directory, there’s nothing in it yet:

$ ls -F thesis

Note that mkdir is not limited to creating single directories one at a time. The -p option allows mkdir to create a directory with any number of nested subdirectories in a single operation:

$ mkdir -p thesis/chapter_1/section_1/subsection_1

The -R option to the ls command will list all nested subdirectories wtihin a directory. Let’s use ls -FR to recursively list the new directory hierarchy we just created beneath the thesis directory:

$ ls -FR thesis
chapter_1/

thesis/chapter_1:
section_1/

thesis/chapter_1/section_1:
subsection_1/

thesis/chapter_1/section_1/subsection_1:

Two ways of doing the same thing

Using the shell to create a directory is no different than using a file explorer. If you open the current directory using your operating system’s graphical file explorer, the thesis directory will appear there too. While the shell and the file explorer are two different ways of interacting with the files, the files and directories themselves are the same.

Good names for files and directories

Complicated names of files and directories can make your life painful when working on the command line. Here we provide a few useful tips for the names of your files.

  1. Don’t use spaces.

    Spaces can make a name more meaningful, but since spaces are used to separate arguments on the command line it is better to avoid them in names of files and directories. You can use - or _ instead (e.g. north-pacific-gyre/ rather than north pacific gyre/).

  2. Don’t begin the name with - (dash).

    Commands treat names starting with - as options.

  3. Stick with letters, numbers, . (period or ‘full stop’), - (dash) and _ (underscore).

    Many other characters have special meanings on the command line. We will learn about some of these during this lesson. There are special characters that can cause your command to not work as expected and can even result in data loss.

    If you need to refer to names of files or directories that have spaces or other special characters, you should surround the name in quotes ("").

Create a text file

Let’s change our working directory to thesis using cd, then run a text editor called Nano to create a file called draft.txt:

$ cd thesis
$ nano draft.txt

Which Editor?

When we say, ‘nano is a text editor’ we really do mean ‘text’: it can only work with plain character data, not tables, images, or any other human-friendly media. We use it in examples because it is one of the least complex text editors. However, because of this trait, it may not be powerful enough or flexible enough for the work you need to do after this workshop. On Unix systems (such as Linux and macOS), many programmers use Emacs or Vim (both of which require more time to learn), or a graphical editor such as Gedit. On Windows, you may wish to use Notepad++. Windows also has a built-in editor called notepad that can be run from the command line in the same way as nano for the purposes of this lesson.

No matter what editor you use, you will need to know where it searches for and saves files. If you start it from the shell, it will (probably) use your current working directory as its default location. If you use your computer’s start menu, it may want to save files in your desktop or documents directory instead. You can change this by navigating to another directory the first time you ‘Save As…’

Let’s type in a few lines of text. Once we’re happy with our text, we can press Ctrl+O (press the Control key and, while holding it down, press the O) to write our data to disk (we’ll be asked what file we want to save this to: press Return to accept the suggested default of draft.txt).

nano

Once our file is saved, we can use Ctrl+X to quit the editor and return to the shell.

Control, Ctrl, or ^ Key

The Control key is also called the ‘Ctrl’ key. There are various ways in which using the Control key may be described. For example, you may see an instruction to press the Control key and, while holding it down, press the X key, described as any of:

  • Control-X

  • Control+X

  • Ctrl-X

  • Ctrl+X

  • ^X

  • C-x

In nano, along the bottom of the screen you’ll see ^G Get Help ^O WriteOut. This means that you can use Control-G to get help and Control-O to save your file.

nano doesn’t leave any output on the screen after it exits, but ls now shows that we have created a file called draft.txt:

$ ls

draft.txt

Creating Files a Different Way

We have seen how to create text files using the nano editor. Now, try the following command:

$ touch my_file.txt

  1. What did the touch command do? When you look at your current directory using the GUI file explorer, does the file show up?

  2. Use ls -l to inspect the files. How large is my_file.txt?

  3. When might you want to create a file this way?

Solution

  1. The touch command generates a new file called my_file.txt in your current directory. You can observe this newly generated file by typing ls at the command line prompt. my_file.txt can also be viewed in your GUI file explorer.

  2. When you inspect the file with ls -l, note that the size of my_file.txt is 0 bytes. In other words, it contains no data. If you open my_file.txt using your text editor it is blank.

  3. Some programs do not generate output files themselves, but instead require that empty files have already been generated. When the program is run, it searches for an existing file to populate with its output. The touch command allows you to efficiently generate a blank text file to be used by such programs.



What’s In A Name?

You may have noticed that all of Nelle’s files are named ‘something dot something’, and in this part of the lesson, we always used the extension .txt. This is just a convention: we can call a file mythesis or almost anything else we want. However, most people use two-part names most of the time to help them (and their programs) tell different kinds of files apart. The second part of such a name is called the filename extension, and indicates what type of data the file holds: .txt signals a plain text file, .pdf indicates a PDF document, .cfg is a configuration file full of parameters for some program or other, .png is a PNG image, and so on.

This is just a convention, albeit an important one. Files contain bytes: it’s up to us and our programs to interpret those bytes according to the rules for plain text files, PDF documents, configuration files, images, and so on.

Naming a PNG image of a whale as whale.mp3 doesn’t somehow magically turn it into a recording of whalesong, though it might cause the operating system to try to open it with a music player when someone double-clicks it.

Moving files and directories

Returning to the ag2pi_workshop directory,

cd ~/input/ag2pi_workshop

In our thesis directory we have a file draft.txt which isn’t a particularly informative name, so let’s change the file’s name using mv, which is short for ‘move’:

$ mv thesis/draft.txt thesis/quotes.txt

The first argument tells mv what we’re ‘moving’, while the second is where it’s to go. In this case, we’re moving thesis/draft.txt to thesis/quotes.txt, which has the same effect as renaming the file. Sure enough, ls shows us that thesis now contains one file called quotes.txt:

$ ls thesis

quotes.txt

One has to be careful when specifying the target file name, since mv will silently overwrite any existing file with the same name, which could lead to data loss. An additional option, mv -i (or mv --interactive), can be used to make mv ask you for confirmation before overwriting.

Note that mv also works on directories.

Let’s move quotes.txt into the current working directory. We use mv once again, but this time we’ll use just the name of a directory as the second argument to tell mv that we want to keep the filename, but put the file somewhere new. (This is why the command is called ‘move’.) In this case, the directory name we use is the special directory name . that we mentioned earlier.

$ mv thesis/quotes.txt .

The effect is to move the file from the directory it was in to the current working directory. ls now shows us that thesis is empty:

$ ls thesis

Further, ls with a filename or directory name as an argument only lists that file or directory. We can use this to see that quotes.txt is still in our current directory:

$ ls quotes.txt

quotes.txt

Moving Files to a new folder

After running the following commands, Jamie realizes that she put the files sucrose.dat and maltose.dat into the wrong folder. The files should have been placed in the raw folder.

$ ls -F
 analyzed/ raw/
$ ls -F analyzed
fructose.dat glucose.dat maltose.dat sucrose.dat
$ cd analyzed

Fill in the blanks to move these files to the raw/ folder (i.e. the one she forgot to put them in)

$ mv sucrose.dat maltose.dat ____/____
Solution
$ mv sucrose.dat maltose.dat ../raw

Recall that .. refers to the parent directory (i.e. one above the current directory) and that . refers to the current directory.



Copying files and directories

The cp command works very much like mv, except it copies a file instead of moving it. We can check that it did the right thing using ls with two paths as arguments — like most Unix commands, ls can be given multiple paths at once:

$ cp quotes.txt thesis/quotations.txt
$ ls quotes.txt thesis/quotations.txt

quotes.txt   thesis/quotations.txt

We can also copy a directory and all its contents by using the recursive option -r, e.g. to back up a directory:

$ cp -r thesis thesis_backup

We can check the result by listing the contents of both the thesis and thesis_backup directory:

$ ls thesis thesis_backup

thesis:
quotations.txt

thesis_backup:
quotations.txt

Renaming Files

Suppose that you created a plain-text file in your current directory to contain a list of the statistical tests you will need to do to analyze your data, and named it: statstics.txt

After creating and saving this file you realize you misspelled the filename! You want to correct the mistake, which of the following commands could you use to do so?

  1. cp statstics.txt statistics.txt

  2. mv statstics.txt statistics.txt

  3. mv statstics.txt .

  4. cp statstics.txt .

Solution

  1. No. While this would create a file with the correct name, the incorrectly named file still exists in the directory and would need to be deleted.

  2. Yes, this would work to rename the file.

  3. No, the period(.) indicates where to move the file, but does not provide a new file name; identical file names cannot be created.

  4. No, the period(.) indicates where to copy the file, but does not provide a new file name; identical file names cannot be created.



Moving and Copying

What is the output of the closing ls command in the sequence shown below?

$ pwd

/Users/jamie/data

$ ls

proteins.dat

$ mkdir recombined
$ mv proteins.dat recombined/
$ cp recombined/proteins.dat ../proteins-saved.dat
$ ls

  1. proteins-saved.dat recombined

  2. recombined

  3. proteins.dat recombined

  4. proteins-saved.dat

Solution

We start in the /Users/jamie/data directory, and create a new folder called recombined. The second line moves (mv) the file proteins.dat to the new folder (recombined). The third line makes a copy of the file we just moved. The tricky part here is where the file was copied to. Recall that .. means ‘go up a level’, so the copied file is now in /Users/jamie. Notice that .. is interpreted with respect to the current working directory, not with respect to the location of the file being copied. So, the only thing that will show using ls (in /Users/jamie/data) is the recombined folder.

  1. No, see explanation above. proteins-saved.dat is located at /Users/jamie

  2. Yes

  3. No, see explanation above. proteins.dat is located at /Users/jamie/data/recombined

  4. No, see explanation above. proteins-saved.dat is located at /Users/jamie



Removing files and directories

Returning to the ag2pi_workshop directory, let’s tidy up this directory by removing the quotes.txt file we created. The Unix command we’ll use for this is rm (short for ‘remove’):

$ rm quotes.txt

We can confirm the file has gone using ls:

$ ls quotes.txt

ls: cannot access 'quotes.txt': No such file or directory

Deleting Is Forever

`rm` is a powerful command.

The Unix shell doesn’t have a trash bin that we can recover deleted files from (though most graphical interfaces to Unix do). Instead, when we delete files, they are unlinked from the file system so that their storage space on disk can be recycled. Tools for finding and recovering deleted files do exist, but there’s no guarantee they’ll work in any particular situation, since the computer may recycle the file’s disk space right away.

Using rm Safely

What happens when we execute rm -i thesis_backup/quotations.txt? Why would we want this protection when using rm?

$ rm: remove regular file 'thesis_backup/quotations.txt'? y

The -i option will prompt before (every) removal (use Y to confirm deletion or N to keep the file). The Unix shell doesn’t have a trash bin, so all the files removed will disappear forever. By using the -i option, we have the chance to check that we are deleting only the files that we want to remove.

If we try to remove the thesis directory using rm thesis, we get an error message:

$ rm thesis

rm: cannot remove `thesis': Is a directory

This happens because rm by default only works on files, not directories.

rm can remove a directory and all its contents if we use the recursive option -r, and it will do so without any confirmation prompts:

$ rm -r thesis

Given that there is no way to retrieve files deleted using the shell, rm -r should be used with great caution (you might consider adding the interactive option rm -r -i).



Operations with multiple files and directories

Oftentimes one needs to copy or move several files at once. This can be done by providing a list of individual filenames, or specifying a naming pattern using wildcards.

Copy with Multiple Filenames

For this exercise, you can test the commands in the ag2pi_workshop/data directory.

In the example below, what does cp do when given several filenames and a directory name?

$ mkdir backup
$ cp amino-acids.txt animals.txt backup/

In the example below, what does cp do when given three or more file names?

$ ls -F

amino-acids.txt  animals.txt  backup/  elements/  morse.txt  pdb/  planets.txt  salmon.txt  sunspot.txt

$ cp amino-acids.txt animals.txt morse.txt
Solution

If given more than one file name followed by a directory name (i.e. the destination directory must be the last argument), cp copies the files to the named directory.

If given three file names, cp throws an error such as the one below, because it is expecting a directory name as the last argument.

cp: target ‘morse.txt’ is not a directory


Using wildcards for accessing multiple files at once

Wildcards

* is a wildcard, which matches zero or more characters. Let’s consider the ag2pi_workshop/molecules directory: *.pdb matches ethane.pdb, propane.pdb, and every file that ends with ‘.pdb’. On the other hand, p*.pdb only matches pentane.pdb and propane.pdb, because the ‘p’ at the front only matches filenames that begin with the letter ‘p’.

? is also a wildcard, but it matches exactly one character. So ?ethane.pdb would match methane.pdb whereas *ethane.pdb matches both ethane.pdb, and methane.pdb.

Wildcards can be used in combination with each other e.g. ???ane.pdb matches three characters followed by ane.pdb, giving cubane.pdb  ethane.pdb  octane.pdb.

When the shell sees a wildcard, it expands the wildcard to create a list of matching filenames before running the command that was asked for. As an exception, if a wildcard expression does not match any file, Bash will pass the expression as an argument to the command as it is. For example typing ls *.pdf in the molecules directory (which contains only files with names ending with .pdb) results in an error message that there is no file called *.pdf. However, generally commands like wc and ls see the lists of file names matching these expressions, but not the wildcards themselves. It is the shell, not the other programs, that deals with expanding wildcards, and this is another example of orthogonal design.

List filenames matching a pattern

When run in the molecules directory, which ls command(s) will produce this output?

ethane.pdb   methane.pdb

  1. ls *t*ane.pdb

  2. ls *t?ne.*

  3. ls *t??ne.pdb

  4. ls ethane.*

Solution

The solution is 3.

  1. shows all files whose names contain zero or more characters (*) followed by the letter t, then zero or more characters (*) followed by ane.pdb. This gives ethane.pdb  methane.pdb  octane.pdb  pentane.pdb.

  2. shows all files whose names start with zero or more characters (*) followed by the letter t, then a single character (?), then ne. followed by zero or more characters (*). This will give us octane.pdb and pentane.pdb but doesn’t match anything which ends in thane.pdb.

  3. fixes the problems of option 2 by matching two characters (??) between t and ne. This is the solution.

  4. only shows files starting with ethane..



More on Wildcards

Sam has a directory containing calibration data, datasets, and descriptions of the datasets:

.
├── 2015-10-23-calibration.txt
├── 2015-10-23-dataset1.txt
├── 2015-10-23-dataset2.txt
├── 2015-10-23-dataset_overview.txt
├── 2015-10-26-calibration.txt
├── 2015-10-26-dataset1.txt
├── 2015-10-26-dataset2.txt
├── 2015-10-26-dataset_overview.txt
├── 2015-11-23-calibration.txt
├── 2015-11-23-dataset1.txt
├── 2015-11-23-dataset2.txt
├── 2015-11-23-dataset_overview.txt
├── backup
│   ├── calibration
│   └── datasets
└── send_to_bob
    ├── all_datasets_created_on_a_23rd
    └── all_november_files

Before heading off to another field trip, she wants to back up her data and send some datasets to her colleague Bob. Sam uses the following commands to get the job done:

$ cp *dataset* backup/datasets
$ cp ____calibration____ backup/calibration
$ cp 2015-____-____ send_to_bob/all_november_files/
$ cp ____ send_to_bob/all_datasets_created_on_a_23rd/

Help Sam by filling in the blanks.

The resulting directory structure should look like this

.
├── 2015-10-23-calibration.txt
├── 2015-10-23-dataset1.txt
├── 2015-10-23-dataset2.txt
├── 2015-10-23-dataset_overview.txt
├── 2015-10-26-calibration.txt
├── 2015-10-26-dataset1.txt
├── 2015-10-26-dataset2.txt
├── 2015-10-26-dataset_overview.txt
├── 2015-11-23-calibration.txt
├── 2015-11-23-dataset1.txt
├── 2015-11-23-dataset2.txt
├── 2015-11-23-dataset_overview.txt
├── backup
│   ├── calibration
│   │   ├── 2015-10-23-calibration.txt
│   │   ├── 2015-10-26-calibration.txt
│   │   └── 2015-11-23-calibration.txt
│   └── datasets
│       ├── 2015-10-23-dataset1.txt
│       ├── 2015-10-23-dataset2.txt
│       ├── 2015-10-23-dataset_overview.txt
│       ├── 2015-10-26-dataset1.txt
│       ├── 2015-10-26-dataset2.txt
│       ├── 2015-10-26-dataset_overview.txt
│       ├── 2015-11-23-dataset1.txt
│       ├── 2015-11-23-dataset2.txt
│       └── 2015-11-23-dataset_overview.txt
└── send_to_bob
    ├── all_datasets_created_on_a_23rd
    │   ├── 2015-10-23-dataset1.txt
    │   ├── 2015-10-23-dataset2.txt
    │   ├── 2015-10-23-dataset_overview.txt
    │   ├── 2015-11-23-dataset1.txt
    │   ├── 2015-11-23-dataset2.txt
    │   └── 2015-11-23-dataset_overview.txt
    └── all_november_files
        ├── 2015-11-23-calibration.txt
        ├── 2015-11-23-dataset1.txt
        ├── 2015-11-23-dataset2.txt
        └── 2015-11-23-dataset_overview.txt
Solution
$ cp *calibration.txt backup/calibration
$ cp 2015-11-* send_to_bob/all_november_files/
$ cp *-23-dataset* send_to_bob/all_datasets_created_on_a_23rd/


Organizing Directories and Files

Jamie is working on a project and she sees that her files aren’t very well organized:

$ ls -F

analyzed/  fructose.dat    raw/   sucrose.dat

The fructose.dat and sucrose.dat files contain output from her data analysis. What command(s) covered in this lesson does she need to run so that the commands below will produce the output shown?

$ ls -F

analyzed/   raw/

$ ls analyzed

fructose.dat    sucrose.dat
Solution
mv *.dat analyzed

Jamie needs to move her files fructose.dat and sucrose.dat to the analyzed directory. The shell will expand *.dat to match all .dat files in the current directory. The mv command then moves the list of .dat files to the ‘analyzed’ directory.

Reproduce a folder structure

You’re starting a new experiment, and would like to duplicate the directory structure from your previous experiment so you can add new data.

Assume that the previous experiment is in a folder called ‘2016-05-18’, which contains a data folder that in turn contains folders named raw and processed that contain data files. The goal is to copy the folder structure of the 2016-05-18-data folder into a folder called 2016-05-20 so that your final directory structure looks like this:

2016-05-20/
└── data
    ├── processed
    └── raw

Which of the following set of commands would achieve this objective? What would the other commands do?

$ mkdir 2016-05-20
$ mkdir 2016-05-20/data
$ mkdir 2016-05-20/data/processed
$ mkdir 2016-05-20/data/raw

$ mkdir 2016-05-20
$ cd 2016-05-20
$ mkdir data
$ cd data
$ mkdir raw processed

$ mkdir 2016-05-20/data/raw
$ mkdir 2016-05-20/data/processed

$ mkdir -p 2016-05-20/data/raw
$ mkdir -p 2016-05-20/data/processed

$ mkdir 2016-05-20
$ cd 2016-05-20
$ mkdir data
$ mkdir raw processed
Solution The first two sets of commands achieve this objective. The first set uses relative paths to create the top level directory before the subdirectories. The third set of commands will give an error because the default behavior of ``mkdir`` won't create a subdirectory of a non-existant directory: the intermediate level folders must be created first. The fourth set of commands achieve this objective. Remember, the ``-p`` option, followed by a path of one or more directories, will cause ``mkdir`` to create any intermediate subdirectories as required. The final set of commands generates the 'raw' and 'processed' directories at the same level as the 'data' directory.


Pipes and Filters

Questions:

  • “How can I combine existing commands to do new things?”

Objectives:

  • Redirect a command’s output to a file.

  • Process a file instead of keyboard input using redirection.

  • Construct command pipelines with two or more stages.

  • Explain what usually happens if a program or pipeline isn’t given any input to process.

  • Explain Unix’s ‘small pieces, loosely joined’ philosophy.

Keypoints:

  • cat displays the contents of its inputs.

  • head displays the first 10 lines of its input.

  • tail displays the last 10 lines of its input.

  • sort sorts its inputs.

  • wc counts lines, words, and characters in its inputs.

  • command [file] redirects a command’s output to a file (overwriting any existing content).

  • command >[file] appends a command’s output to a file.

  • [first] | [second] is a pipeline: the output of the first command is used as the input to the second.

  • The best way to use the shell is to use pipes to combine simple single-purpose programs (filters).

Now that we know a few basic commands, we can finally look at the shell’s most powerful feature: the ease with which it lets us combine existing programs in new ways. We’ll start with the directory called ag2pi_workshop/molecules that contains six files describing some simple organic molecules. The .pdb extension indicates that these files are in Protein Data Bank format, a simple text format that specifies the type and position of each atom in the molecule.

$ ls molecules

cubane.pdb    ethane.pdb    methane.pdb
octane.pdb    pentane.pdb   propane.pdb

Let’s go into that directory with cd and run an example command wc cubane.pdb:

$ cd molecules
$ wc cubane.pdb

20  156 1158 cubane.pdb

wc is the ‘word count’ command: it counts the number of lines, words, and characters in files (from left to right, in that order).

If we run the command wc *.pdb, the * in *.pdb matches zero or more characters, so the shell turns *.pdb into a list of all .pdb files in the current directory:

$ wc *.pdb

 20  156  1158  cubane.pdb
 12  84   622   ethane.pdb
  9  57   422   methane.pdb
 30  246  1828  octane.pdb
 21  165  1226  pentane.pdb
 15  111  825   propane.pdb
107  819  6081  total

Note that wc *.pdb also shows the total number of all lines in the last line of the output.

If we run wc -l instead of just wc, the output shows only the number of lines per file:

$ wc -l *.pdb

 20  cubane.pdb
 12  ethane.pdb
  9  methane.pdb
 30  octane.pdb
 21  pentane.pdb
 15  propane.pdb
107  total

The -m and -w options can also be used with the wc command, to show only the number of characters or the number of words in the files.

What happens if a command is supposed to process a file, but we don’t give it a filename? For example, what if we type:

$ wc -l

but don’t type *.pdb (or anything else) after the command? Since it doesn’t have any filenames, wc assumes it is supposed to process input given at the command prompt, 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 command doesn’t appear to do anything.

If you make this kind of mistake, you can escape out of this state by holding down the control key Ctrl and typing the letter C``once and letting go of the ``Ctrl key. Ctrl + C

Which of these files contains the fewest lines? It’s an easy question to answer when there are only six files, but what if there were 6000? Our first step toward a solution is to run the command:

$ wc -l *.pdb > lengths.txt

The greater than symbol, >, tells the shell to redirect the command’s output to a file instead of printing it to the screen. (This is why there is no screen output: everything that wc would have printed has gone into the file lengths.txt instead.) The shell will create the file if it doesn’t exist. If the file exists, it will be silently overwritten, which may lead to data loss and thus requires some caution. ls lengths.txt confirms that the file exists:

$ ls lengths.txt

lengths.txt

We can now send the content of lengths.txt to the screen using cat lengths.txt. The cat command gets its name from ‘concatenate’ i.e. join together, and it prints the contents of files one after another. There’s only one file in this case, so cat just shows us what it contains:

$ cat lengths.txt

 20  cubane.pdb
 12  ethane.pdb
  9  methane.pdb
 30  octane.pdb
 21  pentane.pdb
 15  propane.pdb
107  total

We’ll continue to use cat in this lesson, for convenience and consistency, but it has the disadvantage that it always dumps the whole file onto your screen. More useful in practice is the command less, which you use with less lengths.txt. This displays a screenful of the file, and then stops. You can go forward one screenful by pressing the spacebar, or back one by pressing b. Press q to quit.

Now let’s use the sort command to sort its contents.

If we run sort on a file containing the following lines:

10
2
19
22
6

the output is:

10
19
2
22
6

If we run sort -n on the same input, we get this instead:

2
6
10
19
22

Explain why -n has this effect.

Solution

The -n option specifies a numerical rather than an alphanumerical sort.



We will also use the -n option to specify that the sort is numerical instead of alphanumerical. This does not change the file; instead, it sends the sorted result to the screen:

$ sort -n lengths.txt

  9  methane.pdb
 12  ethane.pdb
 15  propane.pdb
 20  cubane.pdb
 21  pentane.pdb
 30  octane.pdb
107  total

We can put the sorted list of lines in another temporary file called sorted-lengths.txt by putting sorted-lengths.txt after the command, just as we used lengths.txt to put the output of wc into lengths.txt. Once we’ve done that, we can run another command called head to get the first few lines in sorted-lengths.txt:

$ sort -n lengths.txt > sorted-lengths.txt
$ head -n 1 sorted-lengths.txt

9  methane.pdb

Using -n 1 with head tells it that we only want the first line of the file; -n 20 would get the first 20, and so on. Since sorted-lengths.txt contains the lengths of our files ordered from least to greatest, the output of head must be the file with the fewest lines.

It’s a very bad idea to try redirecting the output of a command that operates on a file to the same file. For example:

$ sort -n lengths.txt > lengths.txt

Doing something like this may give you incorrect results and/or delete the contents of lengths.txt.

We have seen the use of >, but there is a similar operator >> which works slightly differently. We’ll learn about the differences between these two operators by printing some strings. We can use the echo command to print strings of text e.g.

$ echo The echo command prints text

The echo command prints text

Now test the commands below to reveal the difference between the two operators:

$ echo hello > testfile01.txt

and:

$ echo hello >> testfile02.txt

Hint: Try executing each command twice in a row and then examining the output files.

In the first example with >, the string ‘hello’ is written to testfile01.txt, but the file gets overwritten each time we run the command.

We see from the second example that the >> operator also writes ‘hello’ to a file (in this case testfile02.txt), but appends the string to the file if it already exists (i.e. when we run it for the second time).

We have already met the head command, which prints lines from the start of a file. tail is similar, but prints lines from the end of a file instead.

Consider the file ag2pi_workshop/data/animals.txt. After these commands, select the answer that corresponds to the file animals-subset.txt:

$ head -n 3 animals.txt > animals-subset.txt
$ tail -n 2 animals.txt > animals-subset.txt

  1. The first three lines of animals.txt

  2. The last two lines of animals.txt

  3. The first three lines and the last two lines of animals.txt

  4. The second and third lines of animals.txt

Option 3 is correct. For option 1 to be correct we would only run the ``head`` command. For option 2 to be correct we would only run the ``tail`` command. For option 4 to be correct we would have to pipe the output of ``head`` into ``tail -n 2`` by doing ``head -n 3 animals.txt | tail -n 2 animals-subset.txt``

If you think this is confusing, you’re in good company: even once you understand what wc, sort, and head do, all those intermediate files make it hard to follow what’s going on. We can make it easier to understand by running sort and head together:

$ sort -n lengths.txt | head -n 1

9  methane.pdb

The vertical bar, |, between the two commands is called a pipe. It tells the shell that we want to use the output of the command on the left as the input to the command on the right.

Nothing prevents us from chaining pipes consecutively. That is, we can for example send the output of wc directly to sort, and then the resulting output to head. Thus we first use a pipe to send the output of wc to sort:

$ wc -l *.pdb | sort -n

  9 methane.pdb
 12 ethane.pdb
 15 propane.pdb
 20 cubane.pdb
 21 pentane.pdb
 30 octane.pdb
107 total

And now we send the output of this pipe, through another pipe, to head, so that the full pipeline becomes:

$ wc -l *.pdb | sort -n | head -n 1

9  methane.pdb

This is exactly like a mathematician nesting functions like log(3x) and saying ‘the log of three times x’. In our case, the calculation is ‘head of sort of line count of *.pdb’.

The redirection and pipes used in the last few commands are illustrated below:

Redirects and Pipes

In our current directory, we want to find the 3 files which have the least number of lines. Which command listed below would work?

  1. wc -l * sort -n head -n 3

  2. wc -l * | sort -n | head -n 1-3

  3. wc -l * | head -n 3 | sort -n

  4. wc -l * | sort -n | head -n 3

Option 4 is the solution. The pipe character ``|`` is used to connect the output from one command to the input of another. ``>`` is used to redirect standard output to a file. Try it in the ``ag2pi_workshop/molecules`` directory!

This idea of linking programs together is why Unix has been so successful. Instead of creating enormous programs that try to do many different things, Unix programmers focus on creating lots of simple tools that each do one job well, and that work well with each other. This programming model is called ‘pipes and filters’. We’ve already seen pipes; a filter is a program like wc or sort that transforms a stream of input into a stream of output. Almost all of the standard Unix tools can work this way: unless told to do otherwise, they read from standard input, do something with what they’ve read, and write to standard output.

The key is that any program that reads lines of text from standard input and writes lines of text to standard output can be combined with every other program that behaves this way as well. You can and should write your programs this way so that you and other people can put those programs into pipes to multiply their power.

A file called animals.txt (in the ag2pi_workshop/data folder) contains the following data:

2012-11-05,deer
2012-11-05,rabbit
2012-11-05,raccoon
2012-11-06,rabbit
2012-11-06,deer
2012-11-06,fox
2012-11-07,rabbit
2012-11-07,bear

What text passes through each of the pipes and the final redirect in the pipeline below?

$ cat animals.txt | head -n 5 | tail -n 3 | sort -r > final.txt

Hint: build the pipeline up one command at a time to test your understanding

The head command extracts the first 5 lines from animals.txt. Then, the last 3 lines are extracted from the previous 5 by using the tail command. With the sort -r command those 3 lines are sorted in reverse order and finally, the output is redirected to a file final.txt. The content of this file can be checked by executing cat final.txt. The file should contain the following lines:

2012-11-06,rabbit
2012-11-06,deer
2012-11-05,raccoon

For the file animals.txt from the previous exercise, consider the following command:

$ cut -d , -f 2 animals.txt

The cut command is used to remove or ‘cut out’ certain sections of each line in the file, and cut expects the lines to be separated into columns by a Tab character. A character used in this way is a called a delimiter. In the example above we use the -d option to specify the comma as our delimiter character. We have also used the -f option to specify that we want to extract the second field (column). This gives the following output:

deer
rabbit
raccoon
rabbit
deer
fox
rabbit
bear

The uniq command filters out adjacent matching lines in a file. How could you extend this pipeline (using uniq and another command) to find out what animals the file contains (without any duplicates in their names)?

$ cut -d , -f 2 animals.txt | sort | uniq

The file animals.txt contains 8 lines of data formatted as follows:

2012-11-05,deer
2012-11-05,rabbit
2012-11-05,raccoon
2012-11-06,rabbit
...

The uniq command has a -c option which gives a count of the number of times a line occurs in its input. Assuming your current directory is ag2pi_workshop/data/, what command would you use to produce a table that shows the total count of each type of animal in the file?

  1. sort animals.txt | uniq -c

  2. sort -t, -k2,2 animals.txt | uniq -c

  3. cut -d, -f 2 animals.txt | uniq -c

  4. cut -d, -f 2 animals.txt | sort | uniq -c

  5. cut -d, -f 2 animals.txt | sort | uniq -c | wc -l

Option 4. is the correct answer. If you have difficulty understanding why, try running the commands, or sub-sections of the pipelines (make sure you are in the ag2pi_workshop/data directory).

Nelle has run her samples through the assay machines and created 17 files in the north-pacific-gyre/2012-07-03 directory described earlier. As a quick check, starting from her home directory, Nelle types:

$ cd north-pacific-gyre/2012-07-03
$ wc -l *.txt

The output is 18 lines that look like this:

300 NENE01729A.txt
300 NENE01729B.txt
300 NENE01736A.txt
300 NENE01751A.txt
300 NENE01751B.txt
300 NENE01812A.txt
... ...

Now she types this:

$ wc -l *.txt | sort -n | head -n 5

240 NENE02018B.txt
300 NENE01729A.txt
300 NENE01729B.txt
300 NENE01736A.txt
300 NENE01751A.txt

Whoops: one of the files is 60 lines shorter than the others. When she goes back and checks it, she sees that she did that assay at 8:00 on a Monday morning — someone was probably in using the machine on the weekend, and she forgot to reset it. Before re-running that sample, she checks to see if any files have too much data:

$ wc -l *.txt | sort -n | tail -n 5

 300 NENE02040B.txt
 300 NENE02040Z.txt
 300 NENE02043A.txt
 300 NENE02043B.txt
5040 total

Those numbers look good — but what’s that ‘Z’ doing there in the third-to-last line? All of her samples should be marked ‘A’ or ‘B’; by convention, her lab uses ‘Z’ to indicate samples with missing information. To find others like it, she does this:

$ ls *Z.txt

NENE01971Z.txt    NENE02040Z.txt

Sure enough, when she checks the log on her laptop, there’s no depth recorded for either of those samples. Since it’s too late to get the information any other way, she must exclude those two files from her analysis. She could delete them using rm, but there are actually some analyses she might do later where depth doesn’t matter, so instead, she’ll have to be careful later on to select files using the wildcard expression *[AB].txt. As always, the * matches any number of characters; the expression [AB] matches either an ‘A’ or a ‘B’, so this matches all the valid data files she has.

Wildcard expressions can be very complex, but you can sometimes write them in ways that only use simple syntax, at the expense of being a bit more verbose. Consider the directory ag2pi_workshop/north-pacific-gyre/2012-07-03 : the wildcard expression *[AB].txt matches all files ending in A.txt or B.txt. Imagine you forgot about this.

  1. Can you match the same set of files with basic wildcard expressions that do not use the [] syntax? Hint: You may need more than one command, or two arguments to the ls command.

  2. If you used two commands, the files in your output will match the same set of files in this example. What is the small difference between the outputs?

  3. If you used two commands, under what circumstances would your new expression produce an error message where the original one would not?

  1. A solution using two wildcard commands:

    $ ls *A.txt
$ ls *B.txt

A solution using one command but with two arguments:

$ ls *A.txt *B.txt

  1. The output from the two new commands is separated because there are two commands.

  2. When there are no files ending in A.txt, or there are no files ending in B.txt, then one of the two commands will fail.

Suppose you want to delete your processed data files, and only keep your raw files and processing script to save storage. The raw files end in .dat and the processed files end in .txt. Which of the following would remove all the processed data files, and only the processed data files?

  1. rm ?.txt

  2. rm *.txt

  3. rm * .txt

  4. rm *.*

  1. This would remove .txt files with one-character names

  2. This is correct answer

  3. The shell would expand * to match everything in the current directory, so the command would try to remove all matched files and an additional file called .txt

  4. The shell would expand *.* to match all files with any extension, so this command would delete all files

Finding Things

Questions:

  • How can I find files?

  • How can I find things in files?

Objectives:

  • Use grep to select lines from text files that match simple patterns.

  • Use find to find files and directories whose names match simple patterns.

  • Use the output of one command as the command-line argument(s) to another command.

  • Explain what is meant by ‘text’ and ‘binary’ files, and why many common tools don’t handle the latter well.

Keypoints:

  • find finds files with specific properties that match patterns.

  • grep selects lines in files that match patterns.

  • --help is an option supported by many bash commands, and programs that can be run from within Bash, to display more information on how to use these commands or programs.

  • man [command] displays the manual page for a given command.

  • $([command]) inserts a command’s output in place.

In the same way that many of us now use ‘Google’ as a verb meaning ‘to find’, Unix programmers often use the word ‘grep’. ‘grep’ is a contraction of ‘global/regular expression/print’, a common sequence of operations in early Unix text editors. It is also the name of a very useful command-line program.

grep finds and prints lines in files that match a pattern. For our examples, we will use a file that contains three haikus taken from a 1998 competition in Salon magazine. For this set of examples, we’re going to be working in the writing subdirectory:

$ cd
$ cd input/ag2pi_workshop/writing
$ cat haiku.txt

The Tao that is seen
Is not the true Tao, until
You bring fresh toner.

With searching comes loss
and the presence of absence:
"My Thesis" not found.

Yesterday it worked
Today it is not working
Software is like that.

We haven’t linked to the original haikus because they don’t appear to be on Salon’s site any longer. As Jeff Rothenberg said, ‘Digital information lasts forever — or five years, whichever comes first.’ Luckily, popular content often has backups.

Let’s find lines that contain the word ‘not’:

$ grep not haiku.txt

Is not the true Tao, until
"My Thesis" not found
Today it is not working

Here, not is the pattern we’re searching for. The grep command searches through the file, looking for matches to the pattern specified. To use it type grep, then the pattern we’re searching for and finally the name of the file (or files) we’re searching in.

The output is the three lines in the file that contain the letters ‘not’.

By default, grep searches for a pattern in a case-sensitive way. In addition, the search pattern we have selected does not have to form a complete word, as we will see in the next example.

Let’s search for the pattern: ‘The’.

$ grep The haiku.txt

The Tao that is seen
"My Thesis" not found.

This time, two lines that include the letters ‘The’ are outputted, one of which contained our search pattern within a larger word, ‘Thesis’.

To restrict matches to lines containing the word ‘The’ on its own, we can give grep with the -w option. This will limit matches to word boundaries.

Later in this lesson, we will also see how we can change the search behavior of grep with respect to its case sensitivity.

$ grep -w The haiku.txt

The Tao that is seen

Note that a ‘word boundary’ includes the start and end of a line, so not just letters surrounded by spaces. Sometimes we don’t want to search for a single word, but a phrase. This is also easy to do with grep by putting the phrase in quotes.

$ grep -w "is not" haiku.txt

Today it is not working

We’ve now seen that you don’t have to have quotes around single words, but it is useful to use quotes when searching for multiple words. It also helps to make it easier to distinguish between the search term or phrase and the file being searched. We will use quotes in the remaining examples.

Another useful option is -n, which numbers the lines that match:

$ grep -n "it" haiku.txt

5:With searching comes loss
9:Yesterday it worked
10:Today it is not working

Here, we can see that lines 5, 9, and 10 contain the letters ‘it’.

We can combine options (i.e. flags) as we do with other Unix commands. For example, let’s find the lines that contain the word ‘the’. We can combine the option -w to find the lines that contain the word ‘the’ and -n to number the lines that match:

$ grep -n -w "the" haiku.txt

2:Is not the true Tao, until
6:and the presence of absence:

Now we want to use the option -i to make our search case-insensitive:

$ grep -n -w -i "the" haiku.txt

1:The Tao that is seen
2:Is not the true Tao, until
6:and the presence of absence:

Now, we want to use the option -v to invert our search, i.e., we want to output the lines that do not contain the word ‘the’.

$ grep -n -w -v "the" haiku.txt

1:The Tao that is seen
3:You bring fresh toner.
4:
5:With searching comes loss
7:"My Thesis" not found.
8:
9:Yesterday it worked
10:Today it is not working
11:Software is like that.

If we use the -r (recursive) option, grep can search for a pattern recursively through a set of files in subdirectories.

Let’s search recursively for Yesterday in the ag2pi_workshop/writing directory:

grep -r Yesterday .

data/LittleWomen.txt:"Yesterday, when Aunt was asleep and I was trying to be as still as a
data/LittleWomen.txt:Yesterday at dinner, when an Austrian officer stared at us and then
data/LittleWomen.txt:Yesterday was a quiet day spent in teaching, sewing, and writing in my
haiku.txt:Yesterday it worked

grep has lots of other options. To find out what they are, we can type:

$ grep --help

Usage: grep [OPTION]... PATTERN [FILE]...
Search for PATTERN in each FILE or standard input.
PATTERN is, by default, a basic regular expression (BRE).
Example: grep -i 'hello world' menu.h main.c

Regexp selection and interpretation:
  -E, --extended-regexp     PATTERN is an extended regular expression (ERE)
  -F, --fixed-strings       PATTERN is a set of newline-separated fixed strings
  -G, --basic-regexp        PATTERN is a basic regular expression (BRE)
  -P, --perl-regexp         PATTERN is a Perl regular expression
  -e, --regexp=PATTERN      use PATTERN for matching
  -f, --file=FILE           obtain PATTERN from FILE
  -i, --ignore-case         ignore case distinctions
  -w, --word-regexp         force PATTERN to match only whole words
  -x, --line-regexp         force PATTERN to match only whole lines
  -z, --null-data           a data line ends in 0 byte, not newline

Miscellaneous:
...        ...        ...

Which command would result in the following output:

and the presence of absence:

  1. grep "of" haiku.txt

  2. grep -E "of" haiku.txt

  3. grep -w "of" haiku.txt

  4. grep -i "of" haiku.txt

The correct answer is 3, because the -w option looks only for whole-word matches. The other options will also match ‘of’ when part of another word.

grep’s real power doesn’t come from its options, though; it comes from the fact that patterns can include wildcards. (The technical name for these is regular expressions, which is what the ‘re’ in ‘grep’ stands for.) Regular expressions are both complex and powerful; if you want to do complex searches, please look at the lesson on our website. As a taster, we can find lines that have an ‘o’ in the second position like this:

$ grep -E "^.o" haiku.txt

You bring fresh toner.
Today it is not working
Software is like that.

We use the -E option and put the pattern in quotes to prevent the shell from trying to interpret it. (If the pattern contained a *, for example, the shell would try to expand it before running grep.) The ^ in the pattern anchors the match to the start of the line. The . matches a single character (just like ? in the shell), while the o matches an actual ‘o’.

Leah has several hundred data files saved in one directory, each of which is formatted like this:

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

She wants to write a shell script that takes a species as the first command-line argument and a directory as the second argument. The script should return one file called species.txt containing a list of dates and the number of that species seen on each date. For example using the data shown above, rabbit.txt would contain:

2013-11-05,22
2013-11-06,19

Put these commands and pipes in the right order to achieve this:

cut -d : -f 2

|
grep -w $1 -r $2
|
$1.txt
cut -d , -f 1,3

Hint: use man grep to look for how to grep text recursively in a directory and man cut to select more than one field in a line.

An example of such a file is provided in ag2pi_workshop/data/animal-counts/animals.txt

   grep -w $1 -r $2 | cut -d : -f 2 | cut -d , -f 1,3  $1.txt

You would call the script above like this:

$ bash count-species.sh bear .

While grep finds lines in files, the find command finds files themselves. Again, it has a lot of options; to show how the simplest ones work, we’ll use the directory tree shown below.

Find File Tree

Nelle’s writing directory contains one file called haiku.txt and three subdirectories: thesis (which contains a sadly empty file, empty-draft.md); data (which contains three files LittleWomen.txt, one.txt and two.txt); and a tools directory that contains the programs format and stats, and a subdirectory called old, with a file oldtool.

For our first command, let’s run find . (remember to run this command from the ag2pi_workshop/writing folder).

$ find .

.
./data
./data/one.txt
./data/LittleWomen.txt
./data/two.txt
./tools
./tools/format
./tools/old
./tools/old/oldtool
./tools/stats
./haiku.txt
./thesis
./thesis/empty-draft.md

As always, the . on its own means the current working directory, which is where we want our search to start. find’s output is the names of every file and directory under the current working directory. This can seem useless at first but find has many options to filter the output and in this lesson we will discover some of them.

The first option in our list is -type d that means ‘things that are directories’. Sure enough, find’s output is the names of the five directories in our little tree (including .):

$ find . -type d

./
./data
./thesis
./tools
./tools/old

Notice that the objects find finds are not listed in any particular order. If we change -type d to -type f, we get a listing of all the files instead:

$ find . -type f

./haiku.txt
./tools/stats
./tools/old/oldtool
./tools/format
./thesis/empty-draft.md
./data/one.txt
./data/LittleWomen.txt
./data/two.txt

Now let’s try matching by name:

$ find . -name *.txt

./haiku.txt

We expected it to find all the text files, but it only prints out ./haiku.txt. The problem is that the shell expands wildcard characters like * before commands run. Since *.txt in the current directory expands to haiku.txt, the command we actually ran was:

$ find . -name haiku.txt

find did what we asked; we just asked for the wrong thing.

To get what we want, let’s do what we did with grep: put *.txt in quotes to prevent the shell from expanding the * wildcard. This way, find actually gets the pattern *.txt, not the expanded filename haiku.txt:

$ find . -name "*.txt"

./data/one.txt
./data/LittleWomen.txt
./data/two.txt
./haiku.txt

ls and find can be made to do similar things given the right options, but under normal circumstances, ls lists everything it can, while find searches for things with certain properties and shows them.

As we said earlier, the command line’s power lies in combining tools. We’ve seen how to do that with pipes; let’s look at another technique. As we just saw, find . -name "*.txt" gives us a list of all text files in or below the current directory. How can we combine that with wc -l to count the lines in all those files?

The simplest way is to put the find command inside $():

$ wc -l $(find . -name "*.txt")

11 ./haiku.txt
300 ./data/two.txt
21022 ./data/LittleWomen.txt
70 ./data/one.txt
21403 total

When the shell executes this command, the first thing it does is run whatever is inside the $(). It then replaces the $() expression with that command’s output. Since the output of find is the four filenames ./data/one.txt, ./data/LittleWomen.txt, ./data/two.txt, and ./haiku.txt, the shell constructs the command:

$ wc -l ./data/one.txt ./data/LittleWomen.txt ./data/two.txt ./haiku.txt

which is what we wanted. This expansion is exactly what the shell does when it expands wildcards like * and ?, but lets us use any command we want as our own ‘wildcard’.

It’s very common to use find and grep together. The first finds files that match a pattern; the second looks for lines inside those files that match another pattern. Here, for example, we can find PDB files that contain iron atoms by looking for the string ‘FE’ in all the .pdb files above the current directory:

$ grep "FE" $(find .. -name "*.pdb")

../data/pdb/heme.pdb:ATOM     25 FE           1      -0.924   0.535  -0.518

The -v option to grep inverts pattern matching, so that only lines which do not match the pattern are printed. Given that, which of the following commands will find all files in /data whose names end in s.txt but whose names also do not contain the string net? (For example, animals.txt or amino-acids.txt but not planets.txt.) Once you have thought about your answer, you can test the commands in the ag2pi_workshop directory.

  1. find data -name "*s.txt" | grep -v net

  2. find data -name *s.txt | grep -v net

  3. grep -v "net" $(find data -name "*s.txt")

  4. None of the above.

The correct answer is 1. Putting the match expression in quotes prevents the shell expanding it, so it gets passed to the find command.

Option 2 is incorrect because the shell expands *s.txt instead of passing the wildcard expression to find.

Option 3 is incorrect because it searches the contents of the files for lines which do not match ‘net’, rather than searching the file names.

We have focused exclusively on finding patterns in text files. What if your data is stored as images, in databases, or in some other format?

A handful of tools extend grep to handle a few non text formats. But a more generalizable approach is to convert the data to text, or extract the text-like elements from the data. On the one hand, it makes simple things easy to do. On the other hand, complex things are usually impossible. For example, it’s easy enough to write a program that will extract X and Y dimensions from image files for grep to play with, but how would you write something to find values in a spreadsheet whose cells contained formulas?

A last option is to recognize that the shell and text processing have their limits, and to use another programming language. When the time comes to do this, don’t be too hard on the shell: many modern programming languages have borrowed a lot of ideas from it, and imitation is also the sincerest form of praise.

The Unix shell is older than most of the people who use it. It has survived so long because it is one of the most productive programming environments ever created — maybe even the most productive. Its syntax may be cryptic, but people who have mastered it can experiment with different commands interactively, then use what they have learned to automate their work. Graphical user interfaces may be better at the first, but the shell is still unbeaten at the second. And as Alfred North Whitehead wrote in 1911, ‘Civilization advances by extending the number of important operations which we can perform without thinking about them.’

Write a short explanatory comment for the following shell script:

wc -l $(find . -name "*.dat") | sort -n

  1. Find all files with a .dat extension recursively from the current directory

  2. Count the number of lines each of these files contains

  3. Sort the output from step 2. numerically

Lesson content modified from The Carpentries: The Unix Shell

The Carpentries Tutorial Link

Under The Carpentries License:

The Unix Shell: Licenses

Fix or improve this documentation