$ easy_install zope.insterface
$ easy_install twisted

from twisted.internet import reactor, protocol
 
class ReverseEcho(protocol.Protocol):
  def dataReceived(self, data):
    self.transport.write(data.strip()[::-1] + "\n")
 
if __name__ == '__main__':
  server = protocol.ServerFactory()
  server.protocol = ReverseEcho
  reactor.listenTCP(10000, server)
  reactor.run()

$ python rev_echo.py &
$ telnet 127.0.0.1 10000
hello twisted world
dlrow detsiwt olleh

from twisted.web import static, server
from twisted.internet import reactor
 
DOC_ROOT = '/tmp/www/html'
PORT = 10001
 
res  = static.File(DOC_ROOT)
site = server.Site(res)
reactor.listenTCP(PORT, site)
reactor.run()

$ mkdir -p /tmp/www/html
$ echo "hello twisted world" > /tmp/www/html/index.html
$ python static_web.py &
$ w3m http://localhost:10001

$ wget http://sourceforge.net/projects/opencvlibrary/files/opencv-linux/1.1pre1/opencv-1.1pre1.tar.gz/download
$ tar zxvf opencv-1.1pre1.tar.gz
$ cd opencv-1.1pre1
$ ./make && make install

#include < stdio .h >
#include < cv .h >
#include < highgui .h >
 
IplImage* createHistgram(IplImage* srcImg, CvSize& imageSize);
 
int main(int argc, char** argv) {
    // 画像読み込み(グレースケールで読み込み)
    char* imageFilename = "sample.jpg";
    if (argc == 2) {
    	imageFilename = argv[1];
    }
    IplImage* img = cvLoadImage(imageFilename, CV_LOAD_IMAGE_GRAYSCALE);
    if (!img) {
    	printf("@E failed to load image %s @\n", imageFilename);
    	exit(-1);
    }
 
    // Window作成
    char* windowTitle      = "Original Image";
    char* histWindowTitle  = "Histgram";
    cvNamedWindow(windowTitle, CV_WINDOW_AUTOSIZE);
    cvNamedWindow(histWindowTitle, CV_WINDOW_AUTOSIZE);
 
    // 元画像とヒストグラム表示
    CvSize size = cvSize(256, 256);
    IplImage* histImg = createHistgram(img, size);
    cvShowImage(histWindowTitle, histImg);
    cvShowImage(windowTitle, img);
 
    // キー入力待ち
    cvWaitKey(0);
 
    // 破棄
    cvReleaseImage(&img);
    cvReleaseImage(&histImg);
    cvDestroyAllWindows();
 
    return 0;
}
 
IplImage* createHistgram(IplImage* srcImg, CvSize& imageSize) {
	// ヒストグラム作成
	int    channelSize[] = { 256 };
	float  levelRange[]  = { 0, 256 };
	float* range[]       = { levelRange };
	CvHistogram* hist    = cvCreateHist(1, channelSize, CV_HIST_ARRAY, range, 1);
	cvCalcHist(&srcImg, hist);
 
	// ヒストグラム出力用画像作成
	IplImage* dstImg = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
	cvSet(dstImg, cvScalarAll(255), 0);
 
	// ヒストグラムのスケール変換
	float max = 0;
	cvGetMinMaxHistValue(hist, 0, &max, 0, 0);
	cvScale(hist->bins, hist->bins, ((double)dstImg->height) / max, 0);
 
	// 画像に出力
	int binWidth = cvRound((double)imageSize.width / channelSize[0]);
	for (int i = 0; i < channelSize[0]; i++) {
	    int     histValue  = cvRound(cvQueryHistValue_1D(hist, i));
	    CvPoint bottomLeft = cvPoint(i * binWidth, dstImg->height);
	    CvPoint topRight   = cvPoint((i+1) * binWidth, dstImg->height - histValue);
	    cvRectangle(dstImg, bottomLeft, topRight, cvScalarAll(0), CV_FILLED, 8, 0);
	}
 
	// ヒストグラム破棄
	cvReleaseHist(&hist);
 
	return dstImg;
}

TARGET = helloworld
SRCS   = helloworld.cpp
INC    = /usr/local/include/opencv
LIB    = -lcxcore -lcv -lhighgui
 
all:$(TARGET)
$(TARGET):$(SRCS)
	g++ $(SRCS) -o $(TARGET) -I$(INC) $(LIB)
run:all
	./$(TARGET)
clean:
	rm $(TARGET)

#!/usr/bin/perl
 
use strict;
use warnings;
use Perl6::Say;
use Benchmark qw(timethese cmpthese);
 
use LWP::Simple;
use Web::Scraper;
use YAML;
 
use Coro;
use Coro::AnyEvent;
use Coro::Handle;
use Coro::LWP;    # これが無いとLWP::Simple::getがそのまま同期処理になる
 
# 候補リンクを取得する
my $scraper = scraper {
    process '//a', 'links[]' => '@href';
};
my $res     = $scraper->scrape(URI->new('http://www.google.co.jp/'));
my @links   = @{ $res->{links} };
 
STDOUT->autoflush(1);
my $result = timethese(10, {
    Blocking    => 'get_by_blocking',
    NonBlocking => 'get_by_nonblocking',
});
cmpthese($result);
STDOUT->autoflush(0);
 
# 同期処理で取得する
sub get_by_blocking {
    say "@ BLOCKING @";
    my @content;
    foreach my $link (@links) {
        say "retrieving $link";
        push(@content, get($link));  # 本来はここでスクレイピング
        say "complete $link";
    }
    return @content;
}
 
# 非同期処理で取得する
sub get_by_nonblocking {
    say "@ NON BLOCKING @";
    my @cvs;
    my @content;
    foreach my $link (@links) {
        my $cv = AnyEvent->condvar;
        push(@cvs, $cv);
        async {
            say "retrieving $link";
            push(@content, get($link)); # 本来はここでスクレイピング
            say "complete $link";
            $cv->send;
        };
    }
    foreach my $cv (@cvs) {
        $cv->recv;
    }
    return @content;
}

Blocking:    59 wallclock secs ( 1.81 usr +  0.38 sys =  2.19 CPU) @  4.57/s (n=10)
NonBlocking: 14 wallclock secs ( 1.48 usr +  0.31 sys =  1.79 CPU) @  5.59/s (n=10)
 
              Rate    Blocking NonBlocking
Blocking    4.57/s          --        -18%
NonBlocking 5.59/s         22%          --

global:
  assets_path: /usr/local/share/plagger/assets
 
plugins:
  # 入力となるFeedの設定
  - module: Subscription::Config
    config:
      feed:
        - url:  http://feeds.feedburner.com/hatena/b/hotentry
 
  # ユーザ数を取得して、エントリを修正
  - module: Filter::HatenaBookmarkUsersCount
  - module: Widget::HatenaBookmarkUsersCount
 
  # 300件以下は削除
  - module: Filter::Rule
    rule:
      module: Expression
      expression: $args->{entry}->{meta}->{hatenabookmark_users} > 300
 
  # 500件以上は複製
  - module: SmartFeed
    rule:
      module: Expression
      expression: $args->{entry}->{meta}->{hatenabookmark_users} > 500
    config:
      id: copy
 
  # 出力先1
  - module: Publish::CSV
    config:
      dir: .
      encoding: utf-8
      filename: out.csv
      mode: create
      column:
       - title
       - permalink
    rule:
      expression: $args->{feed}->id ne 'copy'
 
  # 出力先2
  - module: Store::DBIC
    config:
      schema_class: Plagger::Schema::MySQL
      connect_info: ['dbi:mysql:plagger_db', 'plagger_user', 'plagger_pass']
    rule:
      expression: $args->{feed}->id eq 'copy'

#!/usr/bin/python
# -*- coding: utf-8 -*-
 
import Image
import ImageFilter
 
# ロードしてjpegへ
image = Image.open('lena.ppm')
print image.format, image.size
image.save('lena.jpg', 'JPEG')
 
# リサイズしてPNGへ
small = image.resize([128, 128])
small.save('thumbnail.png', 'PNG')
 
# 回転してBMPへ
rotate = image.rotate(45)
rotate.save('rotate45.bmp', 'BMP')
 
# 上下反転してGIFへ
upsideDown = image.transpose(Image.FLIP_TOP_BOTTOM)
upsideDown.save('upside_down.gif', 'GIF')
 
# フィルタ処理してTIFFへ
filtered = image.filter(ImageFilter.DETAIL)
filtered.save('filtered.tiff', 'TIFF')