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A Boulder startup improving the way developers work.

Archive for the ‘Development’ Category

Using Ruby to Send Update Emails to Our Mentors

At Devver.net, we send out weekly email updates to an awesome set of mentors. We do this for a number of reasons. First and foremost, we get valuable feedback and advice from our mentors on a variety of issues. But it’s also an easy and effective way to keep us on track and even maximize our chances of success. As Paul Graham says in How Not To Die (he was talking directly to YC teams, but you’ll get the idea):

“For us the main indication of impending doom is when we don’t hear from you. When we haven’t heard from, or about, a startup for a couple months, that’s a bad sign.

Maybe if you can arrange that we keep hearing from you, you won’t die.

That may not be so naive as it sounds. … [The] mere constraint of staying in regular contact with us will push you to make things happen, because otherwise you’ll be embarrassed to tell us that you haven’t done anything new since the last time we talked.”

Foodzie started emailing their mentors early in the summer. We actually borrowed (stole) their email format and best practices.

One thing we’ve tried to not do is send out a completely generic email to all our mentors. Depending on the content and the interaction we’ve had with a specific mentor, we’ll adjust his email accordingly. We begin each email with their name and send it directly to them (in other words, we don’t put a huge list of addresses in the To, CC, or BCC fields). We do this because we can tailor it and it helps elicit individual responses from each mentor (it’s easier to ignore a question if it’s sent to a group).

But, of course, sometimes the emails to a few mentors can be identical. In this case, my not-so-well-kept secret is that I just use a simple Ruby script to send out a duplicate email that appears to be hand-crafted (or at least copied and pasted).

I’ve been told that Outlook can perform this functionality easily, but I don’t know of any way to do this within Gmail. If there is, let me know so I can feel a little silly (in any case, the Ruby code was fun to write).

To run this code, you’ll need to install the highline gem. You’ll also need to add your Gmail account, recipients, subject message, etc. Finally, you’ll want to put your message inside a separate file within project directory. That way, you can easily modify, spellcheck, and format to your heart’s content before sending.

You can get the entire gmailr source code (all two files!) at Github. Please use this script for good, not evil – no one likes a spammer. Enjoy!

Written by Ben

January 20, 2009 at 3:46 pm

Installing and running git-svn on Mac OSX 10.4 Tiger

I am shocked at how much time it took me to get git-svn working on my mac. I use MacPorts, which works well most of the time. Sometimes it has problems which makes me really wish for apt-get on OS X. apt-get normally has worked much nicer for me, but can have its issues too. I even occasionally wish for Windows and a simple install.exe which works 95% of the time out of the box. Really I wish Apple would throw some engineer support to MacPorts and make the service rock solid.

I have had git installed and working for awhile, but preparing to switch our main project from Subversion (svn) to git, I thought I should start using git-svn. It seemed smart to use git-svn for awhile to get used to git, before a full switch so I could fall back on svn in a crunch. I decided to start using git-svn, but the first run of the git-svn command caused this error, and I had no idea how much of my night was about to be wasted…

Can't locate SVN/Core.pm in @INC

Searching led to a couple of webpages, but the most useful was getting git to work on OS X Tiger. It had a quick fix that might work or the long route fix. For some lucky people it is just a path problem. I checked if that was the case for me, by the following command

PATH=/opt/local/bin:$PATH; git svn

unfortunately for me I got the same error, OK I need to reinstall SVN with additional bindings…

> sudo port uninstall -f subversion-perlbindings
> sudo port install -f subversion-perlbindings

leading to this error:

--->  Building serf with target all
Error: Target org.macports.build returned: shell command " cd "/opt/local/var/macports/build/_opt_local_var_macports_sources_rsync.macports.org_release_ports_www_serf/work/serf-0.2.0" && make all " returned error 2
Command output: /opt/local/share/apr-1/build/libtool --silent --mode=compile /usr/bin/gcc-4.0 -O2 -I/opt/local/include -DDARWIN -DSIGPROCMASK_SETS_THREAD_MASK -no-cpp-precomp -I. -I/opt/local/include/apr-1 -I/opt/local/include/apr-1  -c -o buckets/aggregate_buckets.lo buckets/aggregate_buckets.c && touch buckets/aggregate_buckets.lo
libtool: compile: unable to infer tagged configuration
libtool: compile: specify a tag with `--tag'
make: *** [buckets/aggregate_buckets.lo] Error 1

I spent some time searching and eventually I find the solution to the serf error. I couldn’t read the blog because it wasn’t in English, but I could read enough to solve my MacPorts serf install problem. I followed these few lines from the blog

cd /opt/local/var/macports/build/_opt_local_var_macports_sources_rsync.macports.org_release_ports_www_serf/work/serf-0.2.0
$ sudo ./configure --prefix=/opt/local --with-apr=/opt/local --with-apr-util=/opt/local
$ sudo make all
$ sudo port install serf

Awesome, I have serf. Now what is next? Back to building svn with perl bindings, that works. Now, let’s build git again since svn with perl bindings is finally installed.

sudo port install git-core +svn

Which fails because of p5-svn-simple

dyld: lazy symbol binding failed: Symbol not found: _Perl_Gthr_key_ptr
Referenced from: /usr/local/lib/libsvn_swig_perl-1.0.dylib
Expected in: flat namespace
dyld: Symbol not found: _Perl_Gthr_key_ptr
Referenced from: /usr/local/lib/libsvn_swig_perl-1.0.dylib
Expected in: flat namespace
Error: Status 1 encountered during processing.

OK, I need to get p5-svn-simple working. Searching leads to this thread MacPort errors related to git. Here you will find the amazingly useful comment by Orestis:

“As mentioned move your libsvn_swig_perl* out of /usr/local/lib AND out of /usr/lib into temporary folders.

Uninstall and reinstall subversion-perlbindings

Install p5-svn-simple (and git-core +svn which is what lead me here)

Move the libsvn_swig_perl files back in /usr/lib and /usr/local/lib (or else git svn won’t work).

> cd /usr/local
> mv ./lib/libsvn_swig_perl* ./bak/
> sudo port install p5-svn-simple

Sweet that works now

> sudo port install git-core +svn
> cd /usr/local
> mv ./bak/libsvn_swig_perl* ./lib/

Finally I try to run git-svn, only to see the same ERROR I had from the very beginning! I am about to lose it but decide that I should try the quick fix again to see if it is the path issue…

PATH=/opt/local/bin:$PATH; git svn

It works! Alright now it is just a path problem. So I open up my .bash_profile, and notice I already have that path included

# Setting the path for MacPorts.
export PATH=/opt/local/bin:/opt/local/sbin:/Applications/MzScheme\ v352/bin:$PATH

But I also have an additional path added from when I originally built git from source, and it looks like I was running my old broken version of git-svn. So I just had to remove this one line from my .bash_profile

export PATH=~/projects/git-1.5.6.1:$PATH

and hours later and with a ton of frustration I have a fully functioning git-svn.

Now that it is working, you can move on to learning git-svn in 5 minutes.

Written by DanM

December 9, 2008 at 11:16 am

Revisiting additional Ruby Tools

I have heard about new Ruby tools since I did my Ruby Tools Roundup. I am always interested in tools that can help improve our code, so I had to check some of them out. Similar to my last tools post, I will be trying out a tool and writing my general impressions along with the basic usage.

reek


I have to start with reek, since it has been the most requested and searched on our site since I originally wrote about tools. reek will help identify code smells, allowing you to fix up your code. Instead of looking at cyclomatic complexity or other metrics, reek looks at patterns to warn you about bad code. Reek currently detects a few code smells (Long Method, Large Class, Feature Envy, Uncommunicative Name, Long Parameter List, Utility Function, Nested Iterators, Control Couple, Duplication) but more are on the way.

I think this project is useful but would need to be more customized before a nightly run would yield very useful results. The biggest problem I have is the signal to noise ratio seemed pretty high. Reek was warning me about “long methods” that were only 7 statements long, which just isn’t something I am concerned about. The warnings on duplicate methods calls can be useful, after running reek on a few files I found a couple places where duplicate method calls were wasting time. Many of the other smells are interesting like ‘Feature Envy’, and ‘Utility Function’. I will need to use reek more before I know if these smells are good indicators or often false positives.

Below reek finds a utility function next_tick which is definitely a helper function that actually exists in two of our files, which probably should be moved into a helper mixin.

def next_tick
    if(EM.reactor_running?)
      EM.next_tick do
        yield
      end
    else
      yield
    end
end

I am really looking forward to see how the tool progresses. If the project allows for a simple config customization to change the thresholds as well as ignore some files/smells, this could become a very useful tool to help keep a team maintain a high expectation of code quality. It would be useful to get nightly reports about any code that might not meet expectations, so a quick group code review could decide if it is an exception (which can be quickly added to the config) or if the code should be refactored and cleaned up.

dmayer$ sudo gem install reek
dmayer$ reek ./lib/client/client.rb
[Utility Function] Client#next_tick doesn't depend on instance state
[Long Method] Client#process_done has approx 7 statements
[Duplication] Client#process_ready calls @buffer.create_reload_msg more than once
[Long Method] Client#process_ready has approx 10 statements
[Duplication] Client#report_system_message calls result.msg more than once
[Feature Envy] Client#report_system_message refers to result more than self
[Duplication] Client#send_tests calls Time.now more than once
[Long Method] Client#send_tests has approx 24 statements
[Feature Envy] Client#send_tests refers to tests more than self
#check a whole directory
dmayer$ reek ./lib/client/*

Towelie


Towelie helps discover duplication in Ruby code, it will help keep your code DRY. It doesn’t have a nice interface at the moment and it is pretty young code. That being said, it can still be a really useful tool to help guide refactoring and code cleanup.

~/projects dmayer$ git clone git://github.com/gilesbowkett/towelie.git
dmayer$ cd ~/projects/devver/
dmayer$ irb -r ~/projects/towelie/lib/towelie.rb
irb(main):001:0> @t = Towelie.new
=> #, @model=#>
irb(main):002:0> @t.parse "lib/client"
(string):24: warning: useless use of a variable in void context
=> nil
irb(main):003:0> puts @t.duplicates
found in:
lib/client/test_unit_reporter.rb
lib/client/rspec_reporter.rb

def nl
report_nl
end

... 2 more dupes in the reporters ...

found in:
lib/client/test_unit_reporter.rb
lib/client/rspec_reporter.rb

def report(str)
print(str.to_s)
end

found in:
lib/client/sync_client.rb
lib/client/rev_sync_client.rb
lib/client/rev_client.rb
lib/client/client.rb

def quit
send(@buffer.create_quit_msg)
end

found in:
lib/client/sync_client.rb
lib/client/rev_sync_client.rb
lib/client/rev_client.rb
lib/client/client.rb

def send_quit
send(@buffer.create_quit_msg)
end

=> nil
irb(main):004:0>

There are currently many duplications because we are maintaining two clients while deciding what route to eventually take. We have also moved a lot of our shared client code into a mixin, and Towelie finds some methods that really should be moved there as well such as the methods “quit” and “send_quit”, which is currently duped in 4 files. Towelie also points to the fact that we should refactor our reporters because they both duplicate code.

I have always been annoyed with copied and pasted functions accidentally working its way in code, this could be a useful nightly run to keep a team DRY. Sometimes two team members implement the same functionality without even knowing a solution already exists in the code base. If you want to go a bit more in depth, check out Giles Bowkett’s (creator of Towelie) How to use Towelie

Flay


Flay is another great tool by Ryan Davis who also works on Heckle and Flog which I covered in the past. Flay, like Towelie, helps keep your code DRY, it detects exact and similar code throughout a project. It seems to be more powerful than Towelie, as seen in this Towelie and Flay comparison. My biggest complaint is the current release has some pretty basic output that you see below. The output I got from Towelie was immediately more recognizable and useful, while Flay currently requires you to dig in a bit deeper on your own into its suggestions. An improvement is already being worked on and a verbose output mode should be in the release soon. Once better output is included I think Flay will be immediately useful out of the box even with small amounts of developer effort.

I like that Flay has weight system, which should make it easy to set some threshold to ignore, high level weights are more likely to be worth your time and attention. One piece of code Flay tagged with a low weight was code that rescued and logged different errors thrown, which while similar actually served a purpose.

rescue Errno::EISDIR => ed
      @stderr.puts "Error: #{ed.message}" if @stderr
      @stderr.puts "You can't pass a directory to devver only test files. Quitting." if @stderr
      send_quit
    rescue LoadError => le
      @stderr.puts "Error: #{le.message}" if @stderr
      @stderr.puts "Not all of the files can be found. Quitting." if @stderr
      send_quit
    rescue SyntaxError, NameError => se
      @stderr.puts "Error: #{se.message}" if @stderr
      @stderr.puts "This file doesn't appear to be a valid Ruby file. Quitting." if @stderr
      send_quit
end

Digging into the Flay results turned up some duplicate code that Towelie had missed. Since Towelie also caught a method that was duped in 4 client files that Flay missed (I was expecting Towelie’s results to be a subset of what Flay found), perhaps there is room for both of the tools and learning to work with both a little bit is worth the time. After a little bit of work perhaps one of the projects will become a clearly better option. Until then I will be following both of these projects.

sudo gem install flay
dmayer$ flay lib/client/*.rb
Processing lib/client/client.rb...
Processing lib/client/mod_client.rb...
...
Processing lib/client/syncer.rb...

Matches found in :defn (mass = 84)
lib/client/mod_client.rb:86
lib/client/mod_rev_client.rb:124

Matches found in :block (mass = 57)
lib/client/client.rb:201
lib/client/client.rb:205
lib/client/client.rb:209

... 6 more results ...

Matches found in :if (mass = 34)
lib/client/mod_client.rb:63
lib/client/mod_rev_client.rb:111

Matches found in :defn (mass = 32)
lib/client/mod_rev_client.rb:36
lib/client/mod_rev_client.rb:50

Conclusions


That should cover it for this Ruby tools post, but I am really enjoying checking out the tools showing up in the Ruby scene. So as always let me know if I missed something, or if there is a tool you would like to see a full write up on. After some of the tools mature a little bit I will have to revisit a few of the tools which are currently in the early stages. I hope the Ruby tools scene keeps as active as it has been lately because there are some interesting projects being worked on.

honorable mentions (things I didn’t think really needed a full write up)


  • metric-fu a great gem to give quick access to a bunch of tools and metrics about your code (RCov, Saikuro, Flog, SCM Churn, and Rails Stats)
  • CruiseControl.rb when you start using all of these tools, continuous integration starts to become more important (or doing nightly runs). CruiseControl.rb is dead simple continuous integration.
  • Simian another code duplication tool, which is mentioned in 3 tools for drying your Ruby code (free for OSS, $99 for a license)
  • Ruby Tidy a tool for cleaning up HTML (I haven’t used this in Ruby, but loved the Java version in my Java days)
  • Watir is an open-source library for automating web browsers. It allows you to write tests that are easy to read and maintain. It is simple and flexible.
  • Autotest, if you haven’t heard of autotest, check it out, continuously run your tests every time you save a file in your project.
  • Rufus a tool that checks if code you are about to load is safe. Allows you to look for custom patterns that you don’t want to run.
  • I wrote about a couple benchmarking tools last time and here is a great article / tutorial on Ruby benchmarking

Written by DanM

December 3, 2008 at 10:01 am

Ruby Beanstalkd distributed worker intermediate lessons

This post is a follow up to Ruby beanstalkd basics, I will try to make the example code little more interesting and useful. I am calling this is a Ruby beanstalkd intermediate write up, it sets up a few workers and distributes and receives results simultaneously. In this example the code resembles real code a bit more (using a queue cache and block passing). If there is enough interest in the Ruby/beanstalkd community, I will follow up with beanstalkd advanced lessons, and go into how we deal with failure cases such as worker dying during jobs, random jobs failing, processing multiple ‘projects’ at one time, using job priority settings, and using TTR/timeouts.

So in this example we are making an estimate of PI. Yes I know that there are far better approximations out there than my simple results, but this was what I came up with for an incredibly simple distributed computing problem. I based my example on the PI Calculation problem from an Introduction to Parallel Computing. The basic idea is that you can calculate pi by guessing random points in a square and then seeing how many points are inside a circle that fits inside the square (PI= 4 * points_in_circle/total_points).

I made a bunch of comments in the code that should help you follow but there are a few key sections worth pointing out.

In the Ruby beanstalkd Basics, both the Server and the Clients only used one queue at a time. Now since we are sending on one queue while also listening on another we need access to both queues at once. We simply have a helper function with a queue_cache to make getting and reusing multiple queues incredibly easy.

def get_queue(queue_name)
    @queue_cache ||= {}
    if @queue_cache.has_key?(queue_name)
      return @queue_cache[queue_name]
    else
      queue = Beanstalk::Pool.new(["#{SERVER_IP}:#{DEFAULT_PORT}"])
      queue.watch(queue_name)
      queue.use(queue_name)
      queue.ignore('default')
      @queue_cache[queue_name] = queue
      return queue
    end
  end

In the basic example each class had a function that got a job and did some work and deleted the job. It is easy to imagine workers that might have many different kinds of work to do on jobs. In every case they are going to grab a job, work on the job, and delete the job. We decided to break that up and make it easy to just pass a work block when workers get a job.

def take_msg(queue)
    msg = queue.reserve
    #by calling ybody we get the content of the message and convert it from yml
    body = msg.ybody
    if block_given?
      yield(body)
    end
    msg.delete
  end

#call take_msg like so
take_msg(queue) do |body|
  #work on body
end

One other thing you should keep a look out for in the code below is checking if a queue has any jobs. Many times workers will check if jobs exist and take them, and if there aren’t any jobs the process is free to do something else. I do this in this example, the server continually checks incoming results to immediately display. If no results have arrived yet, the server continues sending out job requests as fast as it can. This is useful since taking jobs from beanstalkd is a blocking call. They did add support for non-blocking calls in beanstalkd 1.1, but I haven’t started using the newest version yet. I think everything else should be pretty self explanatory, feel free to ask me any questions. To run the code it is the same as before: download beanstalk_intermediate.rb, start beanstalkd, and run the example with ruby.

$ beanstalkd &
$ ruby beanstalk_intermediate.rb
starting distributor
starting client(s)
distributor sending out  jobs
.......................................................
.............................................
received all the results our estimate for pi is: 3.142776
# of workers time to complete
1 real 0m7.282s
user 0m4.114s
sys 0m0.978s
2 real 0m5.667s
user 0m2.736s
sys 0m0.670s
3 real 0m4.999s
user 0m2.014s
sys 0m0.515s
4 real 0m4.612s
user 0m1.608s
sys 0m0.442s
5 real 0m4.517s
user 0m1.474s
sys 0m0.416s
require 'beanstalk-client.rb'

DEFAULT_PORT = 11300
SERVER_IP = '127.0.0.1'
#beanstalk will order the queues based on priority, with the same priority
#it acts FIFO, in a later example we will use the priority
#(higher numbers are higher priority)
DEFAULT_PRIORITY = 65536
#TTR is time for the job to reappear on the queue.
#Assuming a worker died before completing work and never called job.delete
#the same job would return back on the queue (in TTR seconds)
TTR = 3

class BeanBase

  #To work with multiple queues you must tell beanstalk which queues
  #you plan on writing to (use), and which queues you will reserve jobs from
  #(watch). In this case we also want to ignore the default queue
  #you need a different queue object for each tube you plan on using or
  #you can switch what the tub is watching and using a bunch, we just keep a few
  #queues open on the tubes we want.
  def get_queue(queue_name)
    @queue_cache ||= {}
    if @queue_cache.has_key?(queue_name)
      return @queue_cache[queue_name]
    else
      queue = Beanstalk::Pool.new(["#{SERVER_IP}:#{DEFAULT_PORT}"])
      queue.watch(queue_name)
      queue.use(queue_name)
      queue.ignore('default')
      @queue_cache[queue_name] = queue
      return queue
    end
  end

  #this will take a message off the queue, and process it with the block
  def take_msg(queue)
    msg = queue.reserve
    #by calling ybody we get the content of the message and convert it from yml
    body = msg.ybody
    if block_given?
      yield(body)
    end
    msg.delete
  end

  def results_ready?(queue)
    queue.peek_ready!=nil
  end

end

class BeanDistributor < BeanBase

  def initialize(chunks,points_per_chunk)
    @chunks = chunks
    @points_per_chunk = points_per_chunk
    @messages_out = 0
    @circle_count = 0
  end

  def get_incoming_results(queue)
    if(results_ready?(queue))
      result = nil
      take_msg(queue) do |body|
        result = body.count
      end
      @messages_out -= 1
      print "." #display that we received another result
      @circle_count += result
    else
      #do nothing
    end
  end

  def start_distributor
    request_queue = get_queue('requests')
    results_queue = get_queue('results')
    #put all the work on the request queue
    puts "distributor sending out #{@messages} jobs"
    @chunks.times do |num|
      msg = BeanRequest.new(1,@points_per_chunk)
      #Take our ruby object and convert it to yml and put it on the queue
      request_queue.yput(msg,pri=DEFAULT_PRIORITY, delay=0, ttr=TTR)
      @messages_out += 1
      #if there are results get them if not continue sending out work
      get_incoming_results(results_queue)
    end

    while @messages_out > 0
      get_incoming_results(results_queue)
    end
    npoints = @chunks * @points_per_chunk
    pi = 4.0*@circle_count/(npoints)
    puts "\nreceived all the results our estimate for pi is: #{pi}"
  end

end

class BeanWorker < BeanBase

  def initialize()
  end

  def write_result(queue, result)
    msg = BeanResult.new(1,result)
    queue.yput(msg,pri=DEFAULT_PRIORITY, delay=0, ttr=TTR)
  end

  def in_circle
    #generate 2 random numbers see if they are in the circle
    range = 1000000.0
    radius = range / 2
    xcord = rand(range) - radius
    ycord = rand(range) - radius
    if( (xcord**2) + (ycord**2) <= (radius**2) )
      return 1
    else
      return 0
    end
  end

  def start_worker
    request_queue = get_queue('requests')
    results_queue = get_queue('results')
    #get requests and do the work until the worker is killed
    while(true)
      result = 0
      take_msg(request_queue) do |body|
        chunks = body.count
        chunks.times { result += in_circle}
      end
      write_result(results_queue,result)
    end

  end

end

############
# These are just simple message classes that we pass using beanstalks
# to yml and from yml functions.
############
class BeanRequest
  attr_accessor :project_id, :count
  def initialize(project_id, count=0)
    @project_id = project_id
    @count = count
  end
end

class BeanResult
  attr_accessor :project_id, :count
  def initialize(project_id, count=0)
    @project_id = project_id
    @count = count
  end
end

#how many different jobs we should do
chunks = 100
#how many points to calculate per chunk
points_per_chunk = 10000
#how many workers should we have
#(normally different machines, in our example fork them off)
workers = 5

# Most of the time you will have two entirely separate classes
# but to make it easy to run this example we will just fork and start our server
# and client separately. We will wait for them to complete and check
# if we received all the messages we expected.
puts "starting distributor"
server_pid = fork {
  BeanDistributor.new(chunks,points_per_chunk).start_distributor
}

puts "starting client(s)"
client_pids = []
workers.times do |num|
  client_pid = fork {
    BeanWorker.new.start_worker
  }
  client_pids << client_pid
end

Process.wait(server_pid)
#take down the clients
client_pids.each do |pid|
  Process.kill("HUP",pid)
end

Written by DanM

November 19, 2008 at 3:19 pm

Posted in Development, Hacking, Ruby

Someone please build an awesome embeddable code widget

One awesome thing about working at a startup is that you get to focus very deeply on the problem you’re trying to solve. On the other hand, if you’ve taken the leap and founded a startup, it’s probably because you tend to see solutions and opportunities everywhere. It can be really hard to focus on one thing when you often have ideas for services that you’d like to use, or better yet, build.

Dan and I regulary talk about services that we wish existed but we simply can’t work on due to our commitment to Devver. The other day we were discussing one problem we wish someone would solve: why can’t we easily post nicely formatted code in our blog posts?

All I want is this: I copy/paste some code into a web site, choose the programming language, copy some widget code and paste that code into my blog. The code is indented and formatted, has syntax coloration, wraps correctly (for any iPhone readers) and can be easy copied/pasted. Including line numbers (that don’t mess with copy/paste) is a bonus.

In other words, I just want Pastie in my blog posts.

Yes, I know there are a few really nice projects that you can install on your server that will do all this. But we could all host our own video as well, but it’s just easier to upload and embed a video on YouTube or Vimeo.

This wouldn’t just have to be for the good of humanity either. Such a service could make money off ads (each widget could have a link to the full-screen code on the main site, which could have ads for programming jobs, books, and conferences) or even sell off the data about which programming languages were most popular (in blogs and on the main site).

Maybe there is a solution for this (if there is, please let me know in the comments. I’m more than willing to publicly display my ignorance in order to learn about it), but if there is, I don’t see it widely being used and it’s not easy to find on Google. If there isn’t (yet), please go forth and build. I’ll be anxiously waiting.

Written by Ben

October 30, 2008 at 7:53 am

Posted in Development, Hacking

Ruby Beanstalkd distributed worker basics

At Devver we have a lot of jobs to do quickly, so we distribute our work out to a group of EC2 workers. We have tried and used a number of queuing solutions with Ruby, but in the end beanstalkd seemed to be the best solution for us at the time.

I have only seen a few posts about the basics of using beanstalkd with Ruby. I decided to make two posts evolving a simple Ruby beanstalkd example into a more complicated example. This way people new to beanstalkd could see how easy it can be to get up and running with distributed processing using Ruby and beanstalkd. Then people that are doing more advanced work with beanstalkd could see some examples of how we are working with it here at Devver. It would also be great for more experienced beanstalkd warriors to share their thoughts as there aren’t many examples out in the wild. The lack of examples makes it harder to learn and difficult to decide what the best practices are when working with beanstalkd queues.

I have also shared two scripts we have found useful while working with beanstalkd. beanstalk_monitor.rb, which lets you see all the queue statistics about current usage, or to monitor the information of a single queue you are interested in. Finally, beanstalk_killer.rb, which is useful if you want to work on how your code will react to beanstalkd getting backed up or stalling (in beanstalkd speak, “Putting on the brakes”). It was a little harder to pull everything out and make a simple example from our code than I thought, and obviously the example is a bit useless. It should still give a solid example of how to do the basics of distributing jobs with beanstalkd.

For those new to beanstalk, there are a few things you will need to know like how to get a queue object, how to put objects on the queue, how to take objects off the queue, and how to control which queue you are working with. For a higher level overview or more detailed information, I recommend checking out the beanstalkd FAQ. The full example code is below, but first taking a look at the basic snippets might help.

#to work with beanstalk you need to get a client connection
queue = Beanstalk::Pool.new(["#{SERVER_IP}:#{DEFAULT_PORT}"])
#by default you will be working on the 'default' tube or queue
#if we wanted to work on a different queue we could change tubes, like so
queue.watch('test_queue')
queue.use('test_queue')
queue.ignore('default')
#to put a simple string on a queue
queue.put('hello queue world')
#to receive a simple string
job = queue.reserve
puts job.body #prints 'hello queue world'
#if you don't delete the job when you're done, the queue assumes there is an error
#and the job will show back up on the queue again
job.delete

How to run this example (on OS X, with macports installed)

> sudo port install beanstalkd
> sudo gem install beanstalk-client
> beanstalkd
> ruby beanstalk_tester.rb

Download: beanstalk_tester.rb

require 'beanstalk-client.rb'

DEFAULT_PORT = 11300
SERVER_IP = '127.0.0.1'
#beanstalk will order the queues based on priority, with the same priority
#it acts FIFO, in a later example we will use the priority
#(higher numbers are higher priority)
DEFAULT_PRIORITY = 65536
#TTR is time for the job to reappear on the queue.
#Assuming a worker died before completing work and never called job.delete
#the same job would return back on the queue (in seconds)
TTR = 3

class BeanBase


  #To work with multiple queues you must tell beanstalk which queues
  #you plan on writing to (use), and which queues you will reserve jobs from
  #(watch). In this case we also want to ignore the default queue
  def get_queue(queue_name)
    queue = Beanstalk::Pool.new(["#{SERVER_IP}:#{DEFAULT_PORT}"])
    queue.watch(queue_name)
    queue.use(queue_name)
    queue.ignore('default')
    queue
  end

end

class BeanDistributor < BeanBase

  def initialize(amount)
    @messages = amount
  end

  def start_distributor
    #put all the work on the request queue
    bean_queue = get_queue('requests')
    @messages.times do |num|
      msg = BeanRequest.new(1,num)
      #Take our ruby object and convert it to yml and put it on the queue
      bean_queue.yput(msg,pri=DEFAULT_PRIORITY, delay=0, ttr=TTR)
    end

    puts "distributor now getting results"
    #get all the results from the results queue
    bean_queue = get_queue('results')
    @messages.times do |num|
      result = take_msg(bean_queue)
      puts "result: #{result}"
    end

  end

  #this will take a message off the queue, process it and return the result
  def take_msg(queue)
    msg = queue.reserve
    #by calling ybody we get the content of the message and convert it from yml
    count = msg.ybody.count
    msg.delete
    return count
  end

end

class BeanWorker < BeanBase

  def initialize(amount)
    @messages = amount
    @received_msgs = 0
  end

  def start_worker
    results = []
    #get and process all the requests, on the requests queue
    bean_queue = get_queue('requests')
    @messages.times do |num|
      result = take_msg(bean_queue)
      results << result
      @received_msgs += 1
    end

    #return all of the results, by placing them on the separate results queue
    bean_queue = get_queue('results')
    results.each do |result|
      msg = BeanResult.new(1,result)
      bean_queue.yput(msg,pri=DEFAULT_PRIORITY, delay=0, ttr=TTR)
    end

    #this is just to pass information out of the forked process
    #we return the number of messages we received as our exit status
    exit @received_msgs
  end

  #this will take a message off the queue, process it and return the result
  def take_msg(queue)
    msg = queue.reserve
    #by calling ybody we get the content of the message and convert it from yml
    count = msg.ybody.count
    result = count*count
    msg.delete
    return result
  end

end

############
# These are just simple message classes that we pass using beanstalks
# to yml and from yml functions.
############
class BeanRequest
  attr_accessor :project_id, :count
  def initialize(project_id, count=0)
    @project_id = project_id
    @count = count
  end
end

class BeanResult
  attr_accessor :project_id, :count
  def initialize(project_id, count=0)
    @project_id = project_id
    @count = count
  end
end

#write X messages on the queue
numb = 10

recv_count = 0

# Most of the time you will have two entirely seperate classes
# but to make it easy to run this example we will just fork and start our server
# and client seperately. We will wait for them to complete and check
# if we received all the messages we expected.
puts "starting distributor"
server_pid = fork {
  BeanDistributor.new(numb).start_distributor
}

puts "starting client"
client_pid = fork {
  BeanWorker.new(numb).start_worker
}

Process.wait(client_pid)
recv_count = $?.exitstatus
puts "client finished received #{recv_count} msgs"
if(numb==recv_count)
  puts "received the expected number of messages"
else
  puts "error didn't receive the correct number of messages"
end

Process.wait(server_pid)

Written by DanM

October 28, 2008 at 2:35 pm

Tracking down open files with lsof

The other day I was running in a weird error on Devver. After running around twenty test runs on the system, the component that actually runs individual unit tests was crashing due to “Too many open files – (Errno::EMFILE)”

Unfortunately, I didn’t know much more than that. Which files were being kept open? I knew that this component loaded quite a few files, and that by default, OS X only allows 256 open file descriptors (

ulimit -n

will tell you the default on your system). If this was a valid case of needing to load more files, I could just up the limit using

ulimit -n <bigger_number>

.

Fortunately, a quick Google or two pointed the way to

lsof

. Unfortunately, my Unix-fu is never nearly as good as I wish and I didn’t know much about this handy utility. But I quickly discovered that it’s very useful for tracking down problems like this. I quickly used

ps

to find the PID of the Devver process and then a quick

lsof -p <PID>

displayed all the files that the process had open. So easy!

Sure enough, there were a ton of redundant file handles to the file that we use to store information about the Devver run. Armed with this information, it was easy to find the buggy code where we called File.open but failed to ever close the file.

Unfortunately, I still don’t know how to write a good unit test for this case. I guess I could do something ugly like call sytem(“lsof -p pid | wc -l”) before and after calling the code and make sure the number of descriptors stays constant, but that’s really ugly. Is there a way to test this within Ruby? I’m open to ideas.

Still, it’s always good to learn more about a powerful Unix tool. I’m constanly amazed by the power and depth of the Unit tool set.

Written by Ben

October 9, 2008 at 12:23 pm

Ruby Tools Roundup

Update: Devver now offers a hosted metrics service for Ruby developers which can give you useful feedback about your code. Check out Caliper, to get started with metrics for your project.

I collected all of the Ruby tools posts I made this week into a single roundup. You can quickly jump to any tool that interests you or read my reviews start to finish. If you just want to read a individual section here are the previous posts Ruby Code Quality Tools, Ruby Test Quality Tools, and Ruby Performance Tools.

There have been a bunch of interesting tools released for Ruby lately. I decided to write about a few of my favorite Ruby tools and give some of the new tools a shot as well. Simply put, better tools can help you be a better developer. I am ignoring the entire topic of IDEs as tools, as I have written about Ruby IDEs before, and it is basically a religious war. If you use any Ruby tools I don’t mention be sure to let me know as I am always interested in trying something new out.

Tool Name Description
Code Quality Tools
Roodi Roodi gives developers information about common mistakes in their Ruby code. It makes it easy to clean up your code before things start to get ugly.
Dust Dust is a new tool that will analyze your code, detect unsafe blocks and unused code. Dust is being created by the same mind behind Heckle
Flog Flog essentially scores an ABC metric, giving you a good understanding of the overall code complexity of any give file or method.
Saikuro When given Ruby source code, Saikuro will generate a report listing the cyclomatic complexity of each method found.
Test Quality Tools
Heckle Heckle helps test your Ruby tests (how cool is that?). Heckle is a mutation tester. It alters/breaks code and verifies that tests fail.
rcov rcov is the easiest way to get information about your current code coverage.
Ruby/Rails Performance Tools
ruby-prof ruby-prof is a fast and easy-to-use Ruby profiler. The first of four tools that can help you solve performance issues.
New Relic New Relic is one of the three Rails plugin performance debugging and monitoring tools recently released.
TuneUp TuneUp a Rails performance tool from FiveRuns. This tool has an interesting community built around it as well.
RubyRun Ruby Run is a Rails performance tool similar to New Relic and TuneUp

Lets get into it…

Roodi


Roodi gives you a bunch of interesting warnings about your Ruby code. We are about to release some code, so I took the opportunity to fix up anything Roodi complained about. It helped identify refactoring opportunities, both with long methods, and overly complex methods. The code and tests became cleaner and more granular after breaking some of the methods down. I even found and fixed one silly performance issue that was easy to see after refactoring, which improved the speed of our code. Spending some time with Roodi looks like it could easily improve the quality and readability of most Ruby projects with very little effort. I didn’t solve every problem because in one case I just didn’t think the method could be simplified anymore, but the majority of the suggestions were right on. Below is an example session with Roodi

dmayer$ sudo gem install roodi
dmayer$ roodi lib/client/syncer.rb
lib/client/syncer.rb:136 - Block cyclomatic complexity is 5.  It should be 4 or less.
lib/client/syncer.rb:61 - Method name "excluded" has a cyclomatic complexity is 10.  It should be 8 or less.
lib/client/syncer.rb:101 - Method name "should_be_excluded?" has a cyclomatic complexity is 9.  It should be 8 or less.
lib/client/syncer.rb:132 - Method name "find_changed_files" has a cyclomatic complexity is 10.  It should be 8 or less.
lib/client/syncer.rb:68 - Rescue block should not be empty.
lib/client/syncer.rb:61 - Method name "excluded" has 25 lines.  It should have 20 or less.
lib/client/syncer.rb:132 - Method name "find_changed_files" has 27 lines.  It should have 20 or less.
Found 7 errors.

After Refactoring:

~/projects/gridtest/trunk dmayer$ roodi lib/client/syncer.rb
lib/client/syncer.rb:148 - Block cyclomatic complexity is 5.  It should be 4 or less.
lib/client/syncer.rb:82 - Rescue block should not be empty.
Found 2 errors.

I did have one problem with Roodi – the errors about rescue blocks just seemed to be incorrect. For code like the little example below it kept throwing the error even though I obviously am doing some work in the rescue code.

Roodi output: lib/client/syncer.rb:68 - Rescue block should not be empty.
begin
  socket = TCPSocket.new(server_ip,server_port)
  socket.close
  return true
rescue Errno::ECONNREFUSED
  return false
end

Dust


Dust detects unused code like unused variables,branches, and blocks. I look forward to see how the project progresses. Right now there doesn’t seem to be much out there on the web, and the README is pretty bare bones. Once you can pass it some files to scan, I think this will be something really useful. For now I didn’t think there wasn’t much I could actually do besides check it out. Kevin, who also helped create the very cool Heckle, does claim that code scanning is coming soon, so I look forward to doing a more detailed write up eventually.

Flog


Flog gives feedback about the quality of your code by scoring code using the ABC metric. Using Flog to help guide refactoring, code cleanup, and testing efforts can be highly effective. It is a little easier to understand the reports after reading how Flog scores your code, and what is a good Flog score. Once you get used to working with Flog you will likely want to run it often against your whole project after making any significant changes. There are two easy ways to do this a handy Flog Rake task or MetricFu which works with both Flog and Saikuro.

Running Flog against any subset of a project is easy, here I am running it against our client libraries

find ./lib/client/ -name \*.rb | xargs flog -n -m &gt; flog.log

Here some example Flog output when run against our client code.

Total score = 1364.52395469781

Client#send_tests: (64.3)
    14.3: assignment
    13.9: puts
    10.7: branch
    10.5: send
     4.7: send_quit
     3.4: message
     3.4: now
     2.0: create_queue_test_msg
     1.9: create_run_msg
     1.9: test_files
     1.8: dump
     1.7: each
     1.7: report_start
     1.7: length
     1.7: get_tests
     1.7: -
     1.7: open
     1.7: load_file
     1.6: empty?
     1.6: nil?
     1.6: use_cache
     1.6: exists?
ModClient#send_file: (32.0)
    12.4: branch
     5.4: +
     4.3: assignment
     3.9: send
     3.1: puts
     2.9: ==
     2.9: exists?
     2.9: directory?
     1.9: strftime
     1.8: to_s
     1.5: read
     1.5: create_file_msg
     1.4: info
Syncer#sync: (30.8)
    13.2: assignment
     8.6: branch
     3.6: inspect
     3.2: info
     3.0: puts
     2.8: +
     2.6: empty?
     1.7: map
     1.5: now
     1.5: length
     1.4: send_files
     1.3: max
     1.3: >
     1.3: find_changed_files
     1.3: write_sync_time
Syncer#find_changed_files: (26.2)
    15.6: assignment
     8.7: branch
     3.5: <<
     1.8: to_s
     1.7: get_relative_path
     1.7: >
     1.7: mtime
     1.6: exists?
     1.6: ==
     1.5: prune
     1.4: should_be_excluded?
     1.3: get_removed_files
     1.3: find
... and so on ...

Saikuro


Saikuro is another code complexity tool. It seems to give a little less information than some of the others. It does generate nice HTML reports. Like other code complexity tools it can be helpful to discover the most complex parts of your projects for refactoring and to help focus your testing. I liked the way Flog broke things down for me into a bit more detail, but either is a useful tool and I am sure it is a matter of preference depending on what you are looking for.

saikuro screenshot
Saikuro Screenshot

Heckle


Heckle is an interesting tool to do mutation testing of your tests. Heckle currently supports Test:Unit and RSpec, but does have a number of issues. I had to run it on a few different files and methods before I got some useful output that helped me improve my testing. The first problem was it crashing when I passed it entire files (crashing the majority of the time). I then began passing it single methods I was curious about, which still occasionally caused Heckle to get into an infinite loop case. This is a noted problem in Heckle, but -T and providing a timeout should solve that issue. In my case it was actually not an infinite loop timing error, but an error when attempting to rewrite the code, which lead to a continual failure loop that wouldn’t time out. When I found a class and method that Heckle could test I got some good results. I found one badly written test case, and one case that was never tested. Lets run through a simple Heckle example.

#install heckle
dmayer$ sudo gem install heckle

#example of the infinite loop Error Heckle run
heckle Syncer should_be_excluded? --tests test/unit/client/syncer_test.rb -v

Setting timeout at 5 seconds.
Initial tests pass. Let's rumble.

**********************************************************************
*** Syncer#should_be_excluded? loaded with 13 possible mutations
**********************************************************************
...
2 mutations remaining...
Replacing Syncer#should_be_excluded? with:

2 mutations remaining...
Replacing Syncer#should_be_excluded? with:
... loops forever ...

#Heckle run against our Client class and the process method

dmayer$ heckle Client process --tests test/unit/client/client_test.rb

Initial tests pass. Let's rumble.

**********************************************************************
*** Client#process loaded with 9 possible mutations
**********************************************************************

9 mutations remaining...
8 mutations remaining...
7 mutations remaining...
6 mutations remaining...
5 mutations remaining...
4 mutations remaining...
3 mutations remaining...
2 mutations remaining...
1 mutations remaining...

The following mutations didn't cause test failures:

--- original
+++ mutation

def process(command)

case command
when @buffer.Ready then
process_ready
- when @buffer.SetID then
+ when nil then
process_set_id(command)
when @buffer.InitProject then
process_init_project
when @buffer.Result then
process_result(command)
when @buffer.Goodbye then
kill_event_loop
when @buffer.Done then
process_done
when @buffer.Error then
process_error(command)
else
@log.error("client ignoring invalid command #{command}") if @log
end
end

--- original
+++ mutation
def process(command)
case command
when @buffer.Ready then
process_ready
when @buffer.SetID then
process_set_id(command)
when @buffer.InitProject then
process_init_project
when @buffer.Result then
process_result(command)
when @buffer.Goodbye then
kill_event_loop
when @buffer.Done then
process_done
when @buffer.Error then
process_error(command)
else
- @log.error("client ignoring invalid command #{command}") if @log
+ nil if @log
end
end

Heckle Results:

Passed : 0
Failed : 1
Thick Skin: 0

Improve the tests and try again.

#Tests added / changed to improve Heckle results

def test_process_process_loop__random_result
    Client.any_instance.expects(:start_tls).returns(true)
    client = Client.new({})
    client.stubs(:send_data)
    client.log = stub_everything
    client.log.expects(:error).with("client ignoring invalid command this is random")
    client.process("this is random")
  end

  def test_process_process_loop__set_id
    Client.any_instance.expects(:start_tls).returns(true)
    client = Client.new({})
    client.stubs(:send_data)
    client.log = stub_everything
    cmd = DataBuffer.new.create_set_ids_msg("4")
    client.expects(:process_set_id).with(cmd)
    client.process(cmd)
  end

#A final Heckle run, showing successful results

dmayer$ heckle Client process --tests test/unit/client/client_test.rb

Initial tests pass. Let's rumble.

**********************************************************************
*** Client#process loaded with 9 possible mutations
**********************************************************************

9 mutations remaining...
8 mutations remaining...
7 mutations remaining...
6 mutations remaining...
5 mutations remaining...
4 mutations remaining...
3 mutations remaining...
2 mutations remaining...
1 mutations remaining...
No mutants survived. Cool!

Heckle Results:

Passed : 1
Failed : 0
Thick Skin: 0

All heckling was thwarted! YAY!!!

rcov


rcov is a code coverage tool for Ruby. If you are doing testing you should probably be monitoring your coverage with a code coverage tool. I don't know of a better tool for code coverage than rcov. It is simple to use and generates beautiful, easy-to-read HTML charts showing the current coverage broken down by file. An easy way to make you project more stable is to occasionally spend some time increasing the coverage you have on your project. I have always found it a great way to get back into a project if you have been off of it for awhile. You just need to find some weak coverage points and get to work.
Rcov Screenshot
rcov screenshot

ruby-prof


ruby-prof does what every other profiler does, but it is much faster than the one built in to Ruby. It also makes it easy to output the information you are seeking to HTML pages, such as call graphs. If you are just looking for a simple write up to get started with ruby-prof I recommend the previous link. I will talk a little more about the kinds of problems I find and how I have solved them with ruby-prof.

I have used ruby-prof a number of times to isolate the ways to speed up my code. I haven't used it to identify why an entire Rails application is slow (there are better tools I discuss later for that), but if you have a small but highly important piece of code ruby-prof is often the best way to isolate the problem. I used ruby-prof to identified the two slowest lines of code of a spellchecker, which was rewritten to become twice as fast.

Most recently I used it to identify where the code was spending all of its time in a loop for a file syncer. It turns out that for thousands of files each time through the loop we were continually calling Pathname.new(path).relative_path_from(@dir_path) over and over. Putting a small cache around that call essentially eliminated all delays in our file synchronization. Below is a simple example of how a few lines of code can make all the difference in performance and how easily ruby-prof can help you isolate the problem areas and where to spend your time. I think seeing the code that ruby-prof helped isolate, and the changes made to the code might be useful if you are new to profiling and performance work.

changes in our spellchecker / recommender

#OLD Way
 alteration = []
    n.times {|i| LETTERS.each_byte {
        |l| alteration << word[0...i].strip+l.chr+word[i+1..-1].strip } }
 insertion = []
     (n+1).times {|i| LETTERS.each_byte {
        |l| insertion << word[0...i].strip+l.chr+word[i..-1].strip } }
 #NEW Way
    #pre-calculate the word breakups
    word_starts = []
    word_missing_ends = []
    word_ends = []
    (n+1).times do |i|
      word_starts << word[0...i]
      word_missing_ends << word[i+1..-1]
      word_ends << word[i..-1]
    end

 alteration = []
    n.times {|i|
      alteration = alteration.concat LETTERS.collect { |l|
        word_starts[i]+l+word_missing_ends[i] } }
 insertion = []
    (n+1).times {|i|
      insertion = insertion.concat LETTERS.collect { |l|

        word_starts[i]+l+word_ends[i] } }

Changes in our file syncer

#OLD
 path_name = Pathname.new(path).relative_path_from(@dir_path).to_s
 #NEW
 path_name = get_relative_path(path)

  def get_relative_path(path)
    return @path_cache[path] if @path_cache.member?(path)
    retval = Pathname.new(path).relative_path_from(@dir_path).to_s
    @path_cache[path] = retval
    return retval
  end

New Relic


New Relic is a performance monitoring tool for Rails apps. It has a great development mode that will help you track down performance issues before they even become a problem, and live monitoring so that you can find any hiccups that are slowing down the production application. The entire performance monitoring space for Ruby/Rails seems to be heating up. I guess it is easy to see why, when scaling has been such an issue for some Rails apps. Just playing around with New Relic was exciting and fun. I could quickly track down the slowest pages, and our most problematic SQL calls, in this case I was testing New Relic on Seekler (an old project of ours) since I didn't think I would find much interesting on our current Devver site. Seekler had some glaring performance issues and I think if we had New Relic from the beginning we could have avoided many of them. Sounds like I might have a day project involving New Relic and giving Seekler as much of a performance boost as possible. New Relic turned out to be my favorite of the performance monitoring tools. For a much more detailed writeup check out RailsTips New Relic Review.

newrelic screenshot
New Relic screenshot

TuneUp


TuneUp another easy-to-install and use Rails performance monitoring solution. The problem I had with TuneUp was I couldn't get it working on test app for these sorts of things. I tried running Seekler with TuneUp, but had no luck. I found that many people on the message boards seemed to be having various compatibility issues. I looked at the TuneUp screencast and the kind of information that they give you and I feel like this would be equal to New Relic if it works for you. I am emailing back and forth with FiveRuns support who have been very attentive and helpful, so if I get it working I will update this section.

Update: FiveRuns is pretty amazing with their support. I haven't got TuneUp fully working yet, but have made some progress. Some good things to know are that some plugins like safe_erb and output_compression can cause problems with TuneUp. They are aware of the issues, and actively looking into it.

Ruby Run


RubyRun provides live performance monitoring and debugging tools. I hadn't ever heard of this product before I started doing some research while writing this blog article. I am sorry to say but this was the hardest to set up, and gave back less valuable information. I think they need a simple screencast on how to get set up and get useful information back. After getting setup and running I could only get ugly CSV reports that didn't tell me much more than the regular Rails log files. I started reading the RubyRun Manual but it was about as long as Moby Dick and all I wanted was how to view simple easy-to-read reports which is a snap in New Relic and TuneUp. Since the site didn't mention RubyRun providing better data than New Relic or TuneUp which were much more user friendly, I don't think I would recommend RubyRun.

UPDATE: After reading about my difficulties with RubyRun the great folks from Rubysophic got in touch with me. They offered to help me get the tool working and posted a RubyRun quick start guide to their site. I got it working in a snap thanks to an email from their dev and the amazingly simple quick start guide. I still didn't get the same depth of information that I got with New Relic, although RubyRun has a ton of settings so it is likely you can get more depth to the reports. Something worth pointing out is that RubyRun is working on Seekler, which I haven't been able to get TuneUp running on. So if you have been having problems with TuneUp or New Relic, definitely give RubyRun a look. In the end I think the other offerings are slightly more user friendly (less complex settings), and easier to explore the data (link in the feed to both reports, at least when in developer mode). That being said RubyRun offers some great information and options that the others don't and with a bit more UI tuning RubyRun would be at the top of the pack. Thanks to the helpful devs at Rubysophic for helping me to get the most out of RubyRun.

RubyRun screenshot
RubyRun screenshot
RubyRun second screen shot
screenshot of a different RubyRun report

That is it, hope you learned about a new Ruby tool. So get to work, try a new tool, and get to know your code a little better than you did before.

While I was writing this article, people pointed out to me two more tools worth pointing out. I didn't get a chance to try them out or review them, but thought I should point them out. Towlie, helps keep your code dry by finding redundant methods. and finally Source ANalysis (SAN), which is described as, "a Ruby gem for analyzing the contents of source code including comment to script ratios, todo items, declared functions, classes, and much more".

Written by DanM

October 3, 2008 at 10:25 am

Ruby Code Quality Tools

Update: Devver now offers a hosted metrics service for Ruby developers which can give you useful feedback about your code. Check out Caliper, to get started with metrics for your project.

This is the third post in my series of Ruby tools articles. This time I look at Ruby code quality tools. Rubyists like Ruby because the code can look so nice, simple, and sometimes beautiful. Unfortunately not all code is so great, in fact often the code I write doesn’t look good. Fortunately while a great language can help you to write great code, great tools can help as well. As code grows it is easy for code bloat, dead code, or confusing complexities to slip in. The tools I review below can help with all of these problems. I recommend finding the one or two code quality tools you like best and starting to integrate them more into your development process.

Roodi


Roodi gives you a bunch of interesting warnings about your Ruby code. We are about to release some code, so I took the opportunity to fix up anything Roodi complained about. It helped identify refactoring opportunities, both with long methods, and overly complex methods. The code and tests became cleaner and more granular after breaking some of the methods down. I even found and fixed one silly performance issue that was easy to see after refactoring, which improved the speed of our code. Spending some time with Roodi looks like it could easily improve the quality and readability of most Ruby projects with very little effort. I didn’t solve every problem because in one case I just didn’t think the method could be simplified anymore, but the majority of the suggestions were right on. Below is an example session with Roodi

dmayer$ sudo gem install roodi
dmayer$ roodi lib/client/syncer.rb
lib/client/syncer.rb:136 - Block cyclomatic complexity is 5.  It should be 4 or less.
lib/client/syncer.rb:61 - Method name "excluded" has a cyclomatic complexity is 10.  It should be 8 or less.
lib/client/syncer.rb:101 - Method name "should_be_excluded?" has a cyclomatic complexity is 9.  It should be 8 or less.
lib/client/syncer.rb:132 - Method name "find_changed_files" has a cyclomatic complexity is 10.  It should be 8 or less.
lib/client/syncer.rb:68 - Rescue block should not be empty.
lib/client/syncer.rb:61 - Method name "excluded" has 25 lines.  It should have 20 or less.
lib/client/syncer.rb:132 - Method name "find_changed_files" has 27 lines.  It should have 20 or less.
Found 7 errors.

After Refactoring:

~/projects/gridtest/trunk dmayer$ roodi lib/client/syncer.rb
lib/client/syncer.rb:148 - Block cyclomatic complexity is 5.  It should be 4 or less.
lib/client/syncer.rb:82 - Rescue block should not be empty.
Found 2 errors.

I did have one problem with Roodi – the errors about rescue blocks just seemed to be incorrect. For code like the little example below it kept throwing the error even though I obviously am doing some work in the rescue code.

Roodi output: lib/client/syncer.rb:68 - Rescue block should not be empty.
begin
  socket = TCPSocket.new(server_ip,server_port)
  socket.close
  return true
rescue Errno::ECONNREFUSED
  return false
end

Dust


Dust detects unused code like unused variables,branches, and blocks. I look forward to see how the project progresses. Right now there doesn’t seem to be much out there on the web, and the README is pretty bare bones. Once you can pass it some files to scan, I think this will be something really useful. For now I didn’t think there wasn’t much I could actually do besides check it out. Kevin, who also helped create the very cool Heckle, does claim that code scanning is coming soon, so I look forward to doing a more detailed write up eventually.

Flog


Flog gives feedback about the quality of your code by scoring code using the ABC metric. Using Flog to help guide refactoring, code cleanup, and testing efforts can be highly effective. It is a little easier to understand the reports after reading how Flog scores your code, and what is a good Flog score. Once you get used to working with Flog you will likely want to run it often against your whole project after making any significant changes. There are two easy ways to do this a handy Flog Rake task or MetricFu which works with both Flog and Saikuro.

Running Flog against any subset of a project is easy, here I am running it against our client libraries

find ./lib/client/ -name \*.rb | xargs flog -n -m &gt; flog.log

Here some example Flog output when run against our client code.

Total score = 1364.52395469781

Client#send_tests: (64.3)
    14.3: assignment
    13.9: puts
    10.7: branch
    10.5: send
     4.7: send_quit
     3.4: message
     3.4: now
     2.0: create_queue_test_msg
     1.9: create_run_msg
     1.9: test_files
     1.8: dump
     1.7: each
     1.7: report_start
     1.7: length
     1.7: get_tests
     1.7: -
     1.7: open
     1.7: load_file
     1.6: empty?
     1.6: nil?
     1.6: use_cache
     1.6: exists?
ModClient#send_file: (32.0)
    12.4: branch
     5.4: +
     4.3: assignment
     3.9: send
     3.1: puts
     2.9: ==
     2.9: exists?
     2.9: directory?
     1.9: strftime
     1.8: to_s
     1.5: read
     1.5: create_file_msg
     1.4: info
Syncer#sync: (30.8)
    13.2: assignment
     8.6: branch
     3.6: inspect
     3.2: info
     3.0: puts
     2.8: +
     2.6: empty?
     1.7: map
     1.5: now
     1.5: length
     1.4: send_files
     1.3: max
     1.3: >
     1.3: find_changed_files
     1.3: write_sync_time
Syncer#find_changed_files: (26.2)
    15.6: assignment
     8.7: branch
     3.5: <<
     1.8: to_s
     1.7: get_relative_path
     1.7: >
     1.7: mtime
     1.6: exists?
     1.6: ==
     1.5: prune
     1.4: should_be_excluded?
     1.3: get_removed_files
     1.3: find
... and so on ...

Saikuro


Saikuro is another code complexity tool. It seems to give a little less information than some of the others. It does generate nice HTML reports. Like other code complexity tools it can be helpful to discover the most complex parts of your projects for refactoring and to help focus your testing. I liked the way Flog broke things down for me into a bit more detail, but either is a useful tool and I am sure it is a matter of preference depending on what you are looking for.

saikuro screenshot
Saikuro Screenshot

Written by DanM

October 1, 2008 at 10:04 pm

Posted in Development, Ruby, Testing

Ruby Test Quality Tools

Update: Devver now offers a hosted metrics service for Ruby developers which can give you useful feedback about your code. Check out Caliper, to get started with metrics for your project.

This is the second post in my series of Ruby tools articles. This time I am focused on Ruby test quality tools. Devver is always really interested in testing, and obviously the quality of a project’s tests is important. We are always looking at ways to add even more value to the investment teams put in with testing. Simply knowing that you are writing higher quality tests helps increase the value returned on the time invested in testing. I haven’t found many tools to help with test quality, but these tools are a great help to any Ruby tester.

Heckle


Heckle is an interesting tool to do mutation testing of your tests. Heckle currently supports Test:Unit and RSpec, but does have a number of issues. I had to run it on a few different files and methods before I got some useful output that helped me improve my testing. The first problem was it crashing when I passed it entire files (crashing the majority of the time). I then began passing it single methods I was curious about, which still occasionally caused Heckle to get into an infinite loop case. This is a noted problem in Heckle, but -T and providing a timeout should solve that issue. In my case it was actually not an infinite loop timing error, but an error when attempting to rewrite the code, which lead to a continual failure loop that wouldn’t time out. When I found a class and method that Heckle could test I got some good results. I found one badly written test case, and one case that was never tested. Lets run through a simple Heckle example.

#install heckle
dmayer$ sudo gem install heckle

#example of the infinite loop Error Heckle run
heckle Syncer should_be_excluded? --tests test/unit/client/syncer_test.rb -v
Setting timeout at 5 seconds.
Initial tests pass. Let's rumble.

**********************************************************************
***  Syncer#should_be_excluded? loaded with 13 possible mutations
**********************************************************************
...
2 mutations remaining...
Replacing Syncer#should_be_excluded? with:

2 mutations remaining...
Replacing Syncer#should_be_excluded? with:
... loops forever ...

#Heckle run against our Client class and the process method
dmayer$ heckle Client process --tests test/unit/client/client_test.rb
Initial tests pass. Let's rumble.

**********************************************************************
***  Client#process loaded with 9 possible mutations
**********************************************************************

9 mutations remaining...
8 mutations remaining...
7 mutations remaining...
6 mutations remaining...
5 mutations remaining...
4 mutations remaining...
3 mutations remaining...
2 mutations remaining...
1 mutations remaining...

The following mutations didn't cause test failures:

--- original
+++ mutation

 def process(command)

   case command
   when @buffer.Ready then
     process_ready
-  when @buffer.SetID then
+  when nil then
     process_set_id(command)
   when @buffer.InitProject then
     process_init_project
   when @buffer.Result then
     process_result(command)
   when @buffer.Goodbye then
     kill_event_loop
   when @buffer.Done then
     process_done
   when @buffer.Error then
     process_error(command)
   else
     @log.error("client ignoring invalid command #{command}") if @log
   end
 end

--- original
+++ mutation
 def process(command)
   case command
   when @buffer.Ready then
     process_ready
   when @buffer.SetID then
     process_set_id(command)
   when @buffer.InitProject then
     process_init_project
   when @buffer.Result then
     process_result(command)
   when @buffer.Goodbye then
     kill_event_loop
   when @buffer.Done then
     process_done
   when @buffer.Error then
     process_error(command)
   else
-    @log.error("client ignoring invalid command #{command}") if @log
+    nil if @log
   end
 end

Heckle Results:

Passed    :   0
Failed    :   1
Thick Skin:   0

Improve the tests and try again.

#Tests added / changed to improve Heckle results
  def test_process_process_loop__random_result
    Client.any_instance.expects(:start_tls).returns(true)
    client = Client.new({})
    client.stubs(:send_data)
    client.log = stub_everything
    client.log.expects(:error).with("client ignoring invalid command this is random")
    client.process("this is random")
  end

  def test_process_process_loop__set_id
    Client.any_instance.expects(:start_tls).returns(true)
    client = Client.new({})
    client.stubs(:send_data)
    client.log = stub_everything
    cmd = DataBuffer.new.create_set_ids_msg("4")
    client.expects(:process_set_id).with(cmd)
    client.process(cmd)
  end

#A final Heckle run, showing successful results
dmayer$ heckle Client process --tests test/unit/client/client_test.rb
Initial tests pass. Let's rumble.

**********************************************************************
*** Client#process loaded with 9 possible mutations
**********************************************************************

9 mutations remaining...
8 mutations remaining...
7 mutations remaining...
6 mutations remaining...
5 mutations remaining...
4 mutations remaining...
3 mutations remaining...
2 mutations remaining...
1 mutations remaining...
No mutants survived. Cool!

Heckle Results:

Passed : 1
Failed : 0
Thick Skin: 0

All heckling was thwarted! YAY!!!

rcov


rcov is a code coverage tool for Ruby. If you are doing testing you should probably be monitoring your coverage with a code coverage tool. I don't know of a better tool for code coverage than rcov. It is simple to use and generates beautiful, easy-to-read HTML charts showing the current coverage broken down by file. An easy way to make you project more stable is to occasionally spend some time increasing the coverage you have on your project. I have always found it a great way to get back into a project if you have been off of it for awhile. You just need to find some weak coverage points and get to work.
Rcov Screenshot
rcov screenshot

Written by DanM

September 30, 2008 at 9:57 am

Posted in Development, Ruby, Testing

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