Samson's Weblog » Ruby

Downgrade Rubygems

Samson Wu — Mon, 05 Dec 2011 13:09:53 +0000

First let’s list 2 truths here:

Rails 2.3.5 will fail with RubyGems 1.5.0 +
Rails 2.3.11 will fail with RubyGems 1.7.0 +

So what if you want to deploy or run an application which unfortunately still or initially written in rails 2, given the situation that latest RVM default install rubygems version 1.8.11?

It turns out to be not so painful, cause it’s as simple as just issue one command (take 1.4.2 for example):

gem update --system 1.4.2

Just like the China highway train, sometimes what you need to do is just to stop moving so fast.

ArchLinux, RVM, Ruby, Rails, Nginx, Passenger and You

Samson Wu — Wed, 30 Mar 2011 13:50:08 +0000

没看错，就是ArchLinux，怎么，又回来了？其实我一直未曾离开…… ⁱ

好了不矫情了，let’s do business.

[Overview]
本文介绍如何在archlinux上快速搭建rails开发环境，其中有很多可能包括我个人的preferences，各位完全可以根据自行需要取舍。

[ArchLinux]
参照Arch自己的 Official Install Guide ⁱⁱ 安装，其实根本不用参照，整个安装wizard做的已经非常非常user friendly了，我觉得。

[RVM]
RVM 的安装依赖 git 和 curl：

$ sudo pacman -S git curl

装之：

$ bash < <( curl http://rvm.beginrescueend.com/releases/rvm-install-head )

注意没有sudo，符合homebrew的philosophy，尽量不要root，何况我们还是作为development环境，rvm官网好像现在已经没有倾向性了，不过我印象中以前也是倾向于装在user的home目录。

同样是非常友好的安装过程，参照提示，在.bash_profile或者.bashrc的最后添加一行 Load 代码（如果你用的是bash的话）：

$ echo '[[ -s "$HOME/.rvm/scripts/rvm" ]] && . "$HOME/.rvm/scripts/rvm"' >> ~/.bashrc

我还喜欢shell补全，如果你也喜欢，再加上一句即可：

$ echo '[[ -r $rvm_path/scripts/completion ]] && . $rvm_path/scripts/completion' >> ~/.bashrc

最后查看一下notes，看看所在平台有什么注意事项：

$ rvm notes

[Ruby]
这里我们用rvm安装ruby，如果你喜欢也可以pacman -S之，我查了下，arch repo里的ruby是1.9.2，patch level也是最新的180，不过rvm的好处是可以安装好几个ruby版本，且能够非常方便的帮你维护不同的gemset，非常像python里面的virtualenv.

安装最新的ruby 1.9.2:

$ rvm install 1.9.2

如果需要也可以装上1.8.7的：

$ rvm install 1.8.7

下载编译安装完后我们就可以使用了，我喜欢把ruby 1.9.2，gemset rails3作为我的default：

$ rvm use 1.9.2@rails3 --create --default

verify一下我们是否还是 so far so good：

$ which ruby
/home/samson/.rvm/rubies/ruby-1.9.2-p180/bin/ruby
$ ruby -v
ruby 1.9.2p180 (2011-02-18 revision 30909) [x86_64-linux]

[Rails]
安装rails 3，最新的是3.0.5:

$ gem install rails

$ which rails
/home/samson/.rvm/gems/ruby-1.9.2-p180@rails3/bin/rails
$ rails -v
Rails 3.0.5

创建一个project做demo：

$ rails new demo

bundle一下，确保所有依赖的gem都已安装，这里会把sqlite3给补上:

$ cd demo
$ bundle

又一个milestone，测试一下：

$ rails s

[Nginx & Passenger]
不用apache，让我们换nginx玩玩；由于passenger的nginx模块安装的时候需要重新编译nginx，所以 pacman -S nginx 似乎是没有意义的，我们这里先skip掉，先安装passenger，然后在编译安装passenger的nginx模块的时候把nginx一并搞定。

安装passenger：

$ gem install passenger

安装passenger的nginx模块，同时安装nginx，默认的nginx安装地址是/opt/nginx（可以修改到不需要root的地址），需要root，我们可以用rvmsudo搞定：

$ rvmsudo passenger-install-nginx-module

again，友好至极，装完连配置文件都帮你改好了，不过检查一下总不会错：

$ grep "passenger" nginx.conf
passenger_root /home/samson/.rvm/gems/ruby-1.9.2-p180@rails3/gems/passenger-3.0.5;
passenger_ruby /home/samson/.rvm/wrappers/ruby-1.9.2-p180@rails3/ruby;

配置一下，来跑一下之前创建的demo project：

server {¬
listen 80;¬
server_name demo.local;¬
root /home/samson/code/demo/public;¬
passenger_enabled on;¬
rails_env development;¬
}¬

$ sudo /opt/nginx/sbin/nginx

我取的server name时demo.local，所以在hosts里面加上这条entry后，我们就可以用browser访问 http://demo.local 了.

如果遇到403 forbidden，在nginx.conf里面改下user即可：

user samson users;

reload, welcome aboard!

$ sudo /opt/nginx/sbin/nginx -s reload

[Footnotes]

我有一个arch的liveusb，各种机子上一直保存着至少2+个arch的vm，虽然后来由于太占空间被转移到了移动硬盘，可就是一直舍不得删
最近老是official, official的… 你懂的

RubyGems 1.5.2 Manual Upgrade

Samson Wu — Wed, 16 Feb 2011 07:02:04 +0000

今天想更新RubyGems，突然发现 gem update ––system 貌似不work了：

$ gem -v
1.5.0

$ gem update --system
Updating RubyGems
ERROR: While executing gem ... (NoMethodError)
undefined method `version' for nil:NilClass

turns out 这是 RubyGems 1.5.0 和 1.5.1 的一个bug，1.5.2 fix了这个issue。

Manual的Upgrade可以绕过 reinstall 的麻烦和繁琐，且更低碳环保：

$ gem install rubygems-update
Fetching: rubygems-update-1.5.2.gem (100%)
Successfully installed rubygems-update-1.5.2
1 gem installed

$ update_rubygems
RubyGems 1.5.2 installed

=== 1.5.2 / 2011-02-10

NOTE: RubyGems 1.5.0 and 1.5.1 have a broken <tt>gem update --systemtt>.

To upgrade you'll need to use the manual upgrade recipe. Using sudo/su as
appropriate:

$ gem install rubygems-update
$ update_rubygems

Bug Fixes:

* Fixed gem update --system. RubyGems can now update itself again.

---------------------------------------------------------------------------

RubyGems installed the following executables:
/Users/samson/.rvm/rubies/ruby-1.9.2-p136/bin/gem

Ruby gem geoip and Rack::GeoIPCountry

Samson Wu — Thu, 25 Feb 2010 08:51:44 +0000

wikipedia上对于geolocation的解释是这样的：

Geolocation is the identification of the real-world geographic location of an Internet-connected computer, mobile device, website visitor or other.

检测的方法貌似也有很多：

Geolocation can be performed by associating a geographic location with the Internet Protocol (IP) address, MAC address, RFID, hardware embedded article/production number, embedded software number (such as UUID, Exif/IPTC/XMP or modern steganography), invoice, Wi-Fi connection location, or device GPS coordinates, or other, perhaps self-disclosed information.

（班门弄斧一下先，呵呵呵呵）

ruby里面取到geo信息的一个相对方便的办法是使用rubygem geoip，虽然本质上还是使用maxmind的data，但是免去了编译和安装其c library的麻烦。

安装gem并下载其depend到的geoip database：

$ sudo gem install geoip

$ wget http://geolite.maxmind.com/download/geoip/database/GeoLiteCountry/GeoIP.dat.gz && gunzip GeoIP.dat.gz

如果想要城市信息，还可以下载稍微大一点的带city info的free database：

$ wget http://geolite.maxmind.com/download/geoip/database/GeoLiteCity.dat.gz && gunzip GeoLiteCity.dat.gz

简单的测试一下：

require 'rubygems'
require 'geoip'

p GeoIP.new('GeoIP.dat').country("google.com")
p GeoIP.new('GeoLiteCity.dat').city("baidu.com")

alright, looks good:

["google.com", "66.249.91.104", 225, "US", "USA", "United States", "NA"]
["baidu.com", "220.181.6.81", "CN", "CHN", "China", "AS", "22", "Beijing", "", 39.9289, 116.3883]

由于geo的普遍性，把其做成可以plug&play的Rack middleware绝对是个好主意，这就是接下来要介绍的Rack::GeoIPCountry，CodeRack Contest的first place。

其原理就是调用geoip gem获得访问IP的geo信息并写入request header，这样后面的app或者middleware就能读到并处理了。

同样写个简单的middleware测试一下：

require 'geo_ip_country'

class GeoTest
def initialize(app)
@app = app
end

def call(env)
puts "Remote Address: #{env['REMOTE_ADDR']}"
puts "GeoIP Country ID: #{env['X_GEOIP_COUNTRY_ID']}"
puts "GeoIP Country Code: #{env['X_GEOIP_COUNTRY_CODE']}"
puts "GeoIP Country Code3: #{env['X_GEOIP_COUNTRY_CODE3']}"
puts "GeoIP Country: #{env['X_GEOIP_COUNTRY']}"
puts "GeoIP Continent: #{env['X_GEOIP_CONTINENT']}"
@app.call(env)
end
end

use Rack::ContentLength
use Rack::GeoIPCountry
use GeoTest

run Proc.new { |env| [200, { 'Content-Type' => 'text/html' }, 'OK'] }

rackup起来后，访问http://localhost:9292，确认console下输出了我们想要的geo信息：

Remote Address: 127.0.0.1
GeoIP Country ID: 0
GeoIP Country Code: --
GeoIP Country Code3: --
GeoIP Country: N/A
GeoIP Continent: --
127.0.0.1 - - [25/Feb/2010 16:36:11] "GET / HTTP/1.1" 200 2 0.0016

当然上面的127.0.0.1是不会有任何信息的，local network也是不会在database里面找到对应的，只有当真正的外网ip hit到我们的server时，我们才能看到有意义的geo信息。

List performance: ruby 1.8 and 1.9 (Part 2)

Samson Wu — Mon, 22 Feb 2010 05:54:36 +0000

接上篇： List performance: ruby 1.8 and 1.9 (Part 1)

有了之前的准备和热身，真正跑起步来似乎轻松不少，先贴上我们用来benchmark的code：

require 'benchmark'

n = ARGV.empty? ? 10 ** 6 : 10 ** ARGV[0].to_i
puts "n=#{n}"
Benchmark.bmbm do |x|
x.report do
list = []
n.times do
list << 0
end
end
end

和之前用来benchmark loop performance的code结构上基本没有区别，这里不再赘述，具体的解释亦可参照前文。

下面分别是ruby 1.8和ruby 1.9的一次完整运行（ n=10~10^8 ）的数据结果（也是我唯一运行的一次…）

ruby 1.8:

n=10
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000014)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000012)
==============================================

n=100
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000118)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000061)
==============================================

n=1000
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000375)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000314)
==============================================

n=10000
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.002900)
--------------------------- total: 0.000000sec

user system total real
0.010000 0.000000 0.010000 ( 0.002790)
==============================================

n=100000
Rehearsal ------------------------------------
0.030000 0.000000 0.030000 ( 0.027712)
--------------------------- total: 0.030000sec

user system total real
0.020000 0.000000 0.020000 ( 0.027713)
==============================================

n=1000000
Rehearsal ------------------------------------
0.280000 0.010000 0.290000 ( 0.323298)
--------------------------- total: 0.290000sec

user system total real
0.280000 0.010000 0.290000 ( 0.283621)
==============================================

n=10000000
Rehearsal ------------------------------------
2.740000 0.050000 2.790000 ( 2.809917)
--------------------------- total: 2.790000sec

user system total real
2.760000 0.040000 2.800000 ( 2.810491)
==============================================

n=100000000
Rehearsal ------------------------------------
27.410000 0.490000 27.900000 ( 28.164103)
-------------------------- total: 27.900000sec

user system total real
27.620000 0.480000 28.100000 ( 28.230073)
==============================================

ruby 1.9:

n=10
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000068)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000012)
==============================================

n=100
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000038)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000032)
==============================================

n=1000
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.000297)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.000209)
==============================================

n=10000
Rehearsal ------------------------------------
0.000000 0.000000 0.000000 ( 0.002164)
--------------------------- total: 0.000000sec

user system total real
0.000000 0.000000 0.000000 ( 0.002025)
==============================================

n=100000
Rehearsal ------------------------------------
0.020000 0.000000 0.020000 ( 0.020366)
--------------------------- total: 0.020000sec

user system total real
0.020000 0.000000 0.020000 ( 0.020873)
==============================================

n=1000000
Rehearsal ------------------------------------
0.190000 0.010000 0.200000 ( 0.208302)
--------------------------- total: 0.200000sec

user system total real
0.190000 0.000000 0.190000 ( 0.208822)
==============================================

n=10000000
Rehearsal ------------------------------------
1.920000 0.050000 1.970000 ( 2.050276)
--------------------------- total: 1.970000sec

user system total real
1.920000 0.050000 1.970000 ( 2.054335)
==============================================

n=100000000
Rehearsal ------------------------------------
19.220000 0.460000 19.680000 ( 20.466960)
-------------------------- total: 19.680000sec

user system total real
19.220000 0.460000 19.680000 ( 20.546417)
==============================================

就这次运行的结果而言，ruby 1.9的performance平均都有25%～35%的提升，加之Part 1测试过的循环性能的倒退，则更可以确定list append操作的performance确实在1.9里面较1.8有了很大的提高。

List performance: ruby 1.8 and 1.9 (Part 1)

Samson Wu — Mon, 22 Feb 2010 02:47:02 +0000

（本文数据较多，在rss reader里面可能可读性不是很好，可考虑直接在线阅读）

昨天看到pipitu的这篇blog，觉得蛮有意思，文章比较了python和java的list performance，只可惜没有include ruby 1.8和ruby 1.9，不然结论会更有悬念一点，呵呵.

由于无法营造一致的软硬件环境，也不愿意重复pipitu关于python和java部分的工作，这里就只好先简单benchmark（如果可以算是的话）一下ruby 1.8和1.9里的list (array) performance了，也许pipitu以后有空更新include ruby也说不定：）

先看一下我们用的ruby的版本：

$ ruby -v
ruby 1.8.7 (2009-06-12 patchlevel 174) [i686-darwin9]

$ ruby1.9 -v
ruby 1.9.1p376 (2009-12-07 revision 26041) [i386-darwin9]

还有os：

$ uname -a
Darwin macbook.local 9.8.0 Darwin Kernel Version 9.8.0: Wed Jul 15 16:55:01 PDT 2009; root:xnu-1228.15.4~1/RELEASE_I386 i386

benchmark的方法和pipitu的python sample类似，就是往空的list里面循环n次append，由于循环也被引入，其performance也值得考虑，因为众所周知ruby里面做一件事犹如孔乙己的茴字写法一样有n种办法，其performance也各不一样，说不定pipitu以后会和python, java进行横向，咱还是挑相对快一点的好～不过话说回来，再怎么的精挑细选，java那边还是基本没有悬念，真正有悬念的，我们都心知肚明，呵呵。

所以真正运动之前先来点热身运动，看看哪个循环在我这相对要快：

require 'benchmark'

n = ARGV.empty? ? 10 ** 6 : 10 ** ARGV[0].to_i
puts "n=#{n}"
Benchmark.bmbm do |b|
b.report("for:") { for i in 1..n ; a = "0"; end }
b.report("times:") { n.times do ; a = "0"; end }
b.report("upto:") { 1.upto(n) do ; a = "0"; end }
b.report("downto:") { n.downto(1) do ; a = "0"; end }
end

以上是我所想到的比较常见的4种茴字写法，程序默认取n=10^6进行循环，也可以接受一个作为幂指数的命令行参数，Benchmark的bmbm方法会先dry run一遍所有test作为rehearsal，等memory和garbage collection的状态相对stable了以后才进行真正的benchmark，这样先运行和后运行的report会相对公平一点。

默认运行（ n=10^6 ）的结果如下：

n=1000000
Rehearsal -------------------------------------------
for: 0.310000 0.000000 0.310000 ( 0.313392)
times: 0.290000 0.000000 0.290000 ( 0.297268)
upto: 0.300000 0.000000 0.300000 ( 0.300311)
downto: 0.310000 0.000000 0.310000 ( 0.304146)
---------------------------------- total: 1.210000sec

user system total real
for: 0.310000 0.000000 0.310000 ( 0.313129)
times: 0.290000 0.000000 0.290000 ( 0.297470)
upto: 0.300000 0.000000 0.300000 ( 0.302154)
downto: 0.310000 0.000000 0.310000 ( 0.305562)

一次完整运行（ n=10~10^8 ）的数据结果如下：

n=10
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000018)
times: 0.000000 0.000000 0.000000 ( 0.000011)
upto: 0.000000 0.000000 0.000000 ( 0.000047)
downto: 0.000000 0.000000 0.000000 ( 0.000053)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000014)
times: 0.000000 0.000000 0.000000 ( 0.000011)
upto: 0.000000 0.000000 0.000000 ( 0.000011)
downto: 0.000000 0.000000 0.000000 ( 0.000011)
=====================================================

n=100
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000041)
times: 0.000000 0.000000 0.000000 ( 0.000031)
upto: 0.000000 0.000000 0.000000 ( 0.000033)
downto: 0.000000 0.000000 0.000000 ( 0.000040)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000035)
times: 0.000000 0.000000 0.000000 ( 0.000030)
upto: 0.000000 0.000000 0.000000 ( 0.000031)
downto: 0.000000 0.000000 0.000000 ( 0.000031)
=====================================================

n=1000
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000367)
times: 0.000000 0.000000 0.000000 ( 0.000315)
upto: 0.000000 0.000000 0.000000 ( 0.000319)
downto: 0.000000 0.000000 0.000000 ( 0.000854)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000273)
times: 0.000000 0.000000 0.000000 ( 0.000250)
upto: 0.000000 0.000000 0.000000 ( 0.000254)
downto: 0.000000 0.000000 0.000000 ( 0.000258)
=====================================================

n=10000
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.003388)
times: 0.010000 0.000000 0.010000 ( 0.003056)
upto: 0.000000 0.000000 0.000000 ( 0.003006)
downto: 0.000000 0.000000 0.000000 ( 0.003084)
---------------------------------- total: 0.010000sec

user system total real
for: 0.010000 0.000000 0.010000 ( 0.003114)
times: 0.000000 0.000000 0.000000 ( 0.002955)
upto: 0.000000 0.000000 0.000000 ( 0.003047)
downto: 0.010000 0.000000 0.010000 ( 0.004650)
=====================================================

n=100000
Rehearsal -------------------------------------------
for: 0.030000 0.000000 0.030000 ( 0.032892)
times: 0.030000 0.000000 0.030000 ( 0.029808)
upto: 0.030000 0.000000 0.030000 ( 0.031190)
downto: 0.030000 0.000000 0.030000 ( 0.030379)
---------------------------------- total: 0.120000sec

user system total real
for: 0.030000 0.000000 0.030000 ( 0.033382)
times: 0.030000 0.000000 0.030000 ( 0.029139)
upto: 0.030000 0.000000 0.030000 ( 0.031608)
downto: 0.030000 0.000000 0.030000 ( 0.030498)
=====================================================

n=1000000
Rehearsal -------------------------------------------
for: 0.310000 0.000000 0.310000 ( 0.313392)
times: 0.290000 0.000000 0.290000 ( 0.297268)
upto: 0.300000 0.000000 0.300000 ( 0.300311)
downto: 0.310000 0.000000 0.310000 ( 0.304146)
---------------------------------- total: 1.210000sec

user system total real
for: 0.310000 0.000000 0.310000 ( 0.313129)
times: 0.290000 0.000000 0.290000 ( 0.297470)
upto: 0.300000 0.000000 0.300000 ( 0.302154)
downto: 0.310000 0.000000 0.310000 ( 0.305562)
=====================================================

n=10000000
Rehearsal -------------------------------------------
for: 3.090000 0.000000 3.090000 ( 3.109693)
times: 2.940000 0.010000 2.950000 ( 2.946662)
upto: 2.990000 0.010000 3.000000 ( 3.003812)
downto: 3.010000 0.000000 3.010000 ( 3.021900)
--------------------------------- total: 12.050000sec

user system total real
for: 3.110000 0.010000 3.120000 ( 3.119928)
times: 2.950000 0.010000 2.960000 ( 2.992141)
upto: 3.000000 0.010000 3.010000 ( 3.044853)
downto: 3.020000 0.000000 3.020000 ( 3.036987)
=====================================================

n=100000000
Rehearsal -------------------------------------------
for: 30.950000 0.070000 31.020000 ( 31.139756)
times: 29.360000 0.060000 29.420000 ( 29.543839)
upto: 29.890000 0.070000 29.960000 ( 30.102346)
downto: 30.080000 0.070000 30.150000 ( 30.271642)
-------------------------------- total: 120.550000sec

user system total real
for: 31.130000 0.080000 31.210000 ( 31.359814)
times: 29.420000 0.050000 29.470000 ( 29.630556)
upto: 30.050000 0.060000 30.110000 ( 30.197589)
downto: 30.180000 0.050000 30.230000 ( 30.361343)
=====================================================

由于精力有限，就不做多次运行取平均值这种相对无聊的事情了，结果虽然不严谨也无法真正判断出究竟谁最快（times和upto，downto是在伯仲之间），但至少可以看出for in range是相对最慢的。

换ruby1.9后的运行结果与上基本一致，详细数据如下：

n=10
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000029)
times: 0.000000 0.000000 0.000000 ( 0.000050)
upto: 0.000000 0.000000 0.000000 ( 0.000014)
downto: 0.000000 0.000000 0.000000 ( 0.000013)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000014)
times: 0.000000 0.000000 0.000000 ( 0.000011)
upto: 0.000000 0.000000 0.000000 ( 0.000012)
downto: 0.000000 0.000000 0.000000 ( 0.000012)
=====================================================

n=100
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000061)
times: 0.000000 0.000000 0.000000 ( 0.000103)
upto: 0.000000 0.000000 0.000000 ( 0.000078)
downto: 0.000000 0.000000 0.000000 ( 0.000060)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000066)
times: 0.000000 0.000000 0.000000 ( 0.000061)
upto: 0.000000 0.000000 0.000000 ( 0.000061)
downto: 0.000000 0.000000 0.000000 ( 0.000061)
=====================================================

n=1000
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.000465)
times: 0.000000 0.000000 0.000000 ( 0.000461)
upto: 0.000000 0.000000 0.000000 ( 0.000477)
downto: 0.000000 0.000000 0.000000 ( 0.000428)
---------------------------------- total: 0.000000sec

user system total real
for: 0.000000 0.000000 0.000000 ( 0.000388)
times: 0.000000 0.000000 0.000000 ( 0.000339)
upto: 0.000000 0.000000 0.000000 ( 0.000341)
downto: 0.000000 0.000000 0.000000 ( 0.000339)
=====================================================

n=10000
Rehearsal -------------------------------------------
for: 0.000000 0.000000 0.000000 ( 0.004486)
times: 0.010000 0.000000 0.010000 ( 0.003675)
upto: 0.000000 0.000000 0.000000 ( 0.004407)
downto: 0.000000 0.000000 0.000000 ( 0.004121)
---------------------------------- total: 0.010000sec

user system total real
for: 0.010000 0.000000 0.010000 ( 0.003961)
times: 0.000000 0.000000 0.000000 ( 0.005113)
upto: 0.010000 0.000000 0.010000 ( 0.003592)
downto: 0.000000 0.000000 0.000000 ( 0.003592)
=====================================================

n=100000
Rehearsal -------------------------------------------
for: 0.040000 0.000000 0.040000 ( 0.042573)
times: 0.030000 0.000000 0.030000 ( 0.039094)
upto: 0.030000 0.000000 0.030000 ( 0.041495)
downto: 0.040000 0.000000 0.040000 ( 0.049316)
---------------------------------- total: 0.140000sec

user system total real
for: 0.040000 0.000000 0.040000 ( 0.040422)
times: 0.040000 0.000000 0.040000 ( 0.037030)
upto: 0.040000 0.000000 0.040000 ( 0.041921)
downto: 0.040000 0.000000 0.040000 ( 0.039868)
=====================================================

n=1000000
Rehearsal -------------------------------------------
for: 0.390000 0.000000 0.390000 ( 0.401887)
times: 0.370000 0.000000 0.370000 ( 0.376656)
upto: 0.370000 0.010000 0.380000 ( 0.384750)
downto: 0.370000 0.000000 0.370000 ( 0.380184)
---------------------------------- total: 1.510000sec

user system total real
for: 0.400000 0.000000 0.400000 ( 0.411929)
times: 0.370000 0.000000 0.370000 ( 0.386443)
upto: 0.370000 0.010000 0.380000 ( 0.379820)
downto: 0.370000 0.000000 0.370000 ( 0.379068)
=====================================================

n=10000000
Rehearsal -------------------------------------------
for: 3.920000 0.020000 3.940000 ( 4.021434)
times: 3.690000 0.030000 3.720000 ( 3.844118)
upto: 3.710000 0.030000 3.740000 ( 3.844035)
downto: 3.700000 0.020000 3.720000 ( 3.795330)
--------------------------------- total: 15.120000sec

user system total real
for: 3.910000 0.020000 3.930000 ( 4.003016)
times: 3.670000 0.020000 3.690000 ( 3.749495)
upto: 3.700000 0.020000 3.720000 ( 3.919785)
downto: 3.690000 0.030000 3.720000 ( 3.789975)
=====================================================

n=100000000
Rehearsal -------------------------------------------
for: 39.260000 0.240000 39.500000 ( 40.293460)
times: 36.700000 0.210000 36.910000 ( 37.450910)
upto: 37.020000 0.260000 37.280000 ( 38.963391)
downto: 36.940000 0.230000 37.170000 ( 37.806189)
-------------------------------- total: 150.860000sec

user system total real
for: 39.230000 0.240000 39.470000 ( 40.471694)
times: 36.850000 0.240000 37.090000 ( 38.302817)
upto: 36.870000 0.230000 37.100000 ( 37.802815)
downto: 36.970000 0.220000 37.190000 ( 38.052300)
=====================================================

有趣的是ruby1.9的循环操作性能竟然普遍都是负增长，这倒为我们之后的list performance比较埋下了伏笔。

热身运动到此结束，似乎有喧宾夺主之嫌，所以赶紧搞个part 2…，下篇文章我们会用上面循环性能测试的疑似最佳表现者times来进行list append性能测试，敬请期待。

ruby’s “python -m SimpleHTTPServer”

Samson Wu — Sat, 20 Feb 2010 18:57:43 +0000

If I remembered right, the command below used to be the most voted one on commandlinefu.com:

$ python -m SimpleHTTPServer

the “SimpleHTTPServer” module is written in python and it maybe called “the python way”, but that’s not our topic today. what we really want to do here is just making a ruby equivalent for this popular command, using rack.

first, make sure you have rack gem installed on your system (if you’ve installed rails 2.x before, you may already have it):

$ sudo gem install rack

confirm installation (Rack 1.0 should also work for our example):

$ rackup --version
Rack 1.1

alright, preparation is done, let’s start cooking. only a rackup file will be sufficient, for consistency, let’s just call it simple_http_server.ru .

#!/usr/bin/env rackup
#\ -E deployment

use Rack::ContentLength

app = Rack::Directory.new Dir.pwd
run app

Rack::Directory is so awesome that we just simply rely on it… aren’t i cheating? hehe, maybe…

ok, we’re done. to test it, simply run:

$ rackup simple_http_server.ru

and then point your browser to http://locahost:9292/ .

to be useful for daily use, you may consider chmod +x it to make it executable and put it in your $PATH.

$ chmod +x simple_http_server.ru
$ export PATH=$PATH:`pwd`

to share a directory with your coworkers or friends, simply cd to that directory and execute the script:

$ cd /the/dir/i/want/to/share
$ simple_http_server.ru

since we’re actually using rackup to execute, all the rackup options are also available, which is good:

$ simple_http_server.ru -h

finally, let’s end up with emulating python SimpleHTTPServer’s default behavior:

$ simple_http_server.ru -p 8000

Samson's Weblog » Ruby

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