Tag: command line

Moving Left and Right in zsh (in macOS)

I use the command line a lot on my Macs, in particular, I use iTerm2.

When moving left and right in a command the shortcuts I knew about so far were:

Key (combination)Moves Cursor…
Right Arrow ‘→’One character right
Left Arrow ‘←’One character left
CTRL + aBeginning of the line
CTRL+ eEnd of the line

After adding the following lines to ~/.zshrc, I now can also move left and right per word using ALT-← and ALT-→ respectively:

bindkey "[D" backward-word # ALT-left-arrow  ⌥ + ←
bindkey "[C" forward-word  # ALT-right-arrow ⌥ + →

Especially when moving around in long command lines, this is really convenient & saves a lot of time.

Do you have keyboard shortcuts that you use regularly on the command line (or elsewhere)? I’d love to hear about them!

Seeing And Saying On The Command Line

Occasionally I like command line tools to also say the output, in addition to ‘printing’ it (to STDOUT).

A current context is starting a server locally with updated information. The start up takes time, so I tend to not wait at the command line for it to fully boot.

I wanted a noticeable signal when the thing is up – and also a confirmation that the version of the information source *is* actually updated. The commands tee and (the macOS) say do this for me:

tee >(say&)

tee copies the output of its input to STDOUT (usually the terminal) and the given file. The construction >(other command&) causes tee to send the input not to a file but to othercommand and the & causes that command to return immediately (instead of returning only after the command to finish).

Overall, I do something like this. The system returns a lengthy JSON string, so I use jq to get to the version information I’m looking for:

curl -s -u <username:thepassword> “<url_to_locally_running_service>” | jq “<path_to_version_info_in_json>” | tee >(say&)

The GitHub page explains that

jq is a lightweight and flexible command-line JSON processor.

https://stedolan.github.io/jq/

It’s well worth trying, if you’re dealing with JSON input on the command line.

Tools for Testing — 2

Just like the first tool for testing ‘GraphViz’ I briefly described earlier, today’s tool is not limited to be used in testing.

In most of my projects, I use the command line a lot. My colleague Marcus Franke pointed me to autojump, which allows you to quickly navigate directory structures, as well as open folders in a GUI tool like the Finder (or Pathfinder) on a Mac (and I’m sure it works similarly on Windows & Linux).

As the project page says:

autojump is a faster way to navigate your filesystem. It works by maintaining a database of the directories you use the most from the command line.

I use a Mac (most of the time) as well as Homebrew, so the installation of autojump was simple:

brew install autojump

After using cd to navigate to my most visited directories to ‘train’ auto jump, I can use ‘j d’ to jump into my dev folder, which is where I keep all my project directories:

$ j d
/Users/stephan/dev
~/dev $

Yes, it’s just three key strokes: ‘j’, space and ‘d’. I like this quick way to jump between directories, because it’s a lot less typing (compared to entering the real path names) and moving back and forth in the directory structure is pretty easy and fast.

A Surprising Use of an Interface

This post relates to my short talk at the Agile Testing Days in Potsdam, Germany 2012.

Earlier this year I tweeted this (there’s another blog post about this as well):

Automating tests/checks, seems more valuable than having automated tests—like planning being more valuable than having the plan.

In my case the automating certainly led to other interesting results — and that’s the topic of this post.

Some context

Let’s assume we’re using Cucumber to automate tests for some application and follow the typical Cucumber setup: A folder features containing the feature files and inside of that another folder (step_definitions) containing, well, the step definitions. A support folder inside the feature directory keeps supporting files, such as environment configuration(s) etc.

Keeping it clean

The way I started to work is to start simple: At first I put everything inside the step definitions. Pretty soon though, I extract code chunks into methods of their own. And then move those method definitions into their own class (or module) – an in fact a file of their own.

That way, I end up with two more levels of abstraction below the feature descriptions and the step definitions: Classes (or modules) containing method definitions (see picture).

feature files, step defs, classes/modules, methods

Here I follow Uncle Bob Martin‘s advice of “Extract till you drop” (see his book ‘Clean Code‘, and episode 3 (Functions) of the video series at cleancoders.com): Extract methods until there’s nothing left to extract (and extract that code into the right place).

A first result: A high level interface to the system

One of the results of doing this, is a really high level and clean API to the system at hand. In addition to that I find that step definitions are much easier to understand, since they (mostly) contain a business level description of how the system is used and accompanying assertions to check whether the system behaves as it should.

Enter Pry

Pry is a command line tool for Ruby, like the interactive ruby shell irb that comes with Ruby. However, Pry is a lot more powerful and offers to display method definitions (even those defined in the C sources of internal Ruby classes) and a whole lot more. For a good introduction see the Pry Screencast by Josh Cheek on vimeo.

A trivial and contrived example

Let’s assume we’re trying to find stuff on the web (I’m on a Mac; there are hints about how to achieve this on Windows in the code comments):

require 'safariwatir' # Windows: require 'watir'

class GoogleSearch
 def initialize
 @browser = Watir::Safari.new # Win: Watir::Browser.new
 end

 def search_for search_term
 @browser.goto 'http://wellknown-search-engine.example.com/'
 @browser.text_field( :name, 'q' ).set search_term
 @browser.button( :id, 'gbqfb' ).click
 @browser.ol( :id, 'rso' ).links.map(&amp;amp;amp;:text)
 end
end

Given that interface and Ppy, the creation of a console app borders on being trivial (yet, it took me a long while to get to this point):

require_relative 'google_search'
require 'pry'

GoogleSearch.new.pry

Think about this for a moment: Take Pry and your API and in 3 lines of code you get a console app for your system. The console can be used like this:

[10] stephan@nibur … #ruby google_search_console.rb
[1] pry(#&lt;GoogleSearch&gt;):1&gt; search_for 'pry video josh'
=&gt; ['Pry Screencast on Vimeo',
# ...

As mentioned above, you can even display the method definition (including lines of code, file name etc.)

[8] pry(&lt;GoogleSearch&gt;)&gt; show-method search_for

From: /Users/stephan/…/google_search.rb @ line 8:
Number of lines: 6
Owner: GoogleSearch
Visibility: public

def search_for search_term
 @browser.goto 'http://google.de/'
 @browser.text_field( :name, 'q' ).set search_term
 @browser.button( :id, 'gbqfb' ).click
 @browser.ol( :id, 'rso' ).links.map(&amp;amp;amp;:text)
end
[9] pry(#&amp;amp;lt;GoogleSearch&amp;amp;gt;)&amp;amp;gt;…

Leaving thoughts

It seems that doing something can be more valuable that having the result. Notwithstanding, we still need to produce something of value for our business.

I came to realise that clean code matters more than ‘only’ providing a code base that’s easy to understand and change: Without the high level API, I might not even have noticed the possibility to create a ‘business level console’.

Having a console app like this allows to prepare starting points for exploratory testing (that might be ‘automation assisted exploring). Or short: I think a clean and high-level interface plus Pry is a cool tool for exploration.

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