nyango

object Main extends App {

  def possibleSeq(baseSeq: Seq[Option[Boolean]]): Seq[Seq[Boolean]] =
    baseSeq.foldLeft(Seq(Seq.empty[Boolean])) { (acc, ele) =>
      ele match {
        case Some(b) => acc.map(_ ++ Seq(b))
        case None => acc.flatMap(s => Seq(s ++ Seq(true), s ++ Seq(false)))
      }
    }

nyango

import javax.inject.{Inject, Singleton}

import akka.stream.Materializer
import play.api.Configuration
import play.filters.cors.CORSConfig.Origins.Matching
import play.filters.cors.{CORSConfig, CORSFilter}

import scala.concurrent.ExecutionContext
import scala.util.matching.Regex

nyango

#!/bin/bash -eu

if [[ $# != 1 ]];
then
  echo "第一引数にアカウント名を指定してください。"
  echo ""
  echo "e.g."
  echo "$ ./list_policies.sh your_account_name"
  exit 1
fi

nyango

import math
NUMBER = 100000000

def get_prime_list(limit):
    limit_sqrt = int(math.ceil(math.sqrt(limit)))
    prime_bool_list = [False] * 2 + [True] * (limit - 2)
    for prime_cand in xrange(2,limit_sqrt):
        if prime_bool_list[prime_cand]:
            for composite in range(prime_cand ** 2, limit, prime_cand):
                prime_bool_list[composite] = False

nyango

#!/bin/bash
set -eu
pngFile=$1
headPtr=0
if [ "89504E470D0A1A0A" != $(xxd -ps -u -s $headPtr -l 8 $pngFile) ]
then
  echo "pngファイルではありません"
  exit 1
fi
headPtr=$((headPtr+8))

nyango

#!/bin/bash
# this script removes duplicated files 
# using md5sum.
#
# $1 : target directory
#
tmptable=$(mktemp temp.XXXXX)

\ls -t ${1%/}/* | while read line
do

nyango

brew install aalib
brew install libcaca
brew install mplayer --with-libcaca

nyango

sudo git clone git://github.com/yyuu/pyenv.git /usr/local/pyenv
sudo git clone git://github.com/yyuu/pyenv-virtualenv.git /usr/local/pyenv/plugins/pyenv-virtualenv

nyango

sudo git clone git://github.com/yyuu/pyenv-virtualenv.git /usr/local/pyenv
sudo git clone git://github.com/yyuu/pyenv-virtualenv.git /usr/local/pyenv/plugins/pyenv-virtualenv

nyango

import csv
trainReader = csv.reader(open('traindata.csv', 'rb'))
nya = []
for row in trainReader:
    nya.append(row)
# train data
noarr = filter(lambda row: row[-1] == 'No', nya)
yesarr = filter(lambda row: row[-1] == 'Yes', nya)