Akio Ohta Drunkar

## simple_mjpeg_streamer_http_server_2cam.py
#!/usr/bin/python
"""
    Original Author: Igor Maculan - n3wtron@gmail.com
    Modified by: Drunkar - drunkars.p@gmail.com
    A Simple mjpg stream http server
"""
import cv2
from PIL import Image
import threading
from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer

## sn_log_settings_simple
import logging
logger = logging.getLogger("")logger.setLevel(logging.DEBUG)
stream_handler = logging.StreamHandler()
stream_handler.setLevel(logging.DEBUG)
logger.addHandler(stream_handler)

## hubot-jidan_no_jouken.coffee
module.exports = (robot) ->

  ORACLE = "疲れからか、不幸にも黒塗りの高級車に追突してしまう。
後輩をかばいすべての責任を負った三浦に対し、車の主、暴力団員谷岡に言い渡された示談の条件とは…。"

  robot.hear /.+(。|!|！)$/i, (msg) ->
    msg.send "しかし" + ORACLE

  robot.hear /(けど(、)?|のに|、|すぎて)$/i, (msg) ->
    msg.send ORACLE

## sn_log_settings_module.py
from logging import getLogger
logger = getLogger(__name__)

## sn_log_settings_master.py
import os
import logging
import logging.handlers

root_logger = logging.getLogger("")
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
root_logger.setLevel(logging.DEBUG)

# stdout handler
stream_handler = logging.StreamHandler()

## hubot-battle_dome.coffee
module.exports = (robot) ->

  robot.hear /ボールを相手のゴールに$/i, (msg) ->
    msg.reply "シュゥゥゥーッ！！"

  robot.hear /超(！|!)$/i, (msg) ->
    msg.reply "エキサイティン！！"

## rpi_im920.py
#!/usr/bin/env python
# -*- coding: UTF-8 -*-

import os
import sys
from threading import Thread
import threading
import time
import serial

## speech_recognition_api_example.html

<!DOCTYPE html>
<html>
<head>
    <title>speech test</title>
    <meta charset="utf-8">
</head>
<body>
<script type="text/javascript">
    var recognition = new webkitSpeechRecognition();

## howto_test_python.md

      
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                Drunkar
                / howto_test_python.md
            
            
              Created
              May 13, 2016 03:25
            
          
    How to: Pythonでのテスト

例: nbviewerのテスト環境


travis ciを使用(.travis.ymlを実行)

.travis.ymlでinvokeを使用して環境のセットアップやtestコマンドを外部ファイル化(tasks.py)


invokeでtasks.pyを実行


tasks.pyの内部でnosetestsでテストを実行


## scikit_svm_example.py
# coding: utf-8
import argparse
import numpy as np
from sklearn import svm
from sklearn.multiclass import OneVsRestClassifier
from sklearn.externals import joblib

parser = argparse.ArgumentParser(description="svm")
parser.add_argument("-pretrained_model", default=None)
parser.add_argument("-train", default=None, help="data for train")
	#!/usr/bin/python
	"""
	Original Author: Igor Maculan - n3wtron@gmail.com
	Modified by: Drunkar - drunkars.p@gmail.com
	A Simple mjpg stream http server
	"""
	import cv2
	from PIL import Image
	import threading
	from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer
	import logging
	logger = logging.getLogger("")logger.setLevel(logging.DEBUG)
	stream_handler = logging.StreamHandler()
	stream_handler.setLevel(logging.DEBUG)
	logger.addHandler(stream_handler)
	module.exports = (robot) ->

	ORACLE = "疲れからか、不幸にも黒塗りの高級車に追突してしまう。
	後輩をかばいすべての責任を負った三浦に対し、車の主、暴力団員谷岡に言い渡された示談の条件とは…。"

	robot.hear /.+(。\|!\|！)$/i, (msg) ->
	msg.send "しかし" + ORACLE

	robot.hear /(けど(、)?\|のに\|、\|すぎて)$/i, (msg) ->
	msg.send ORACLE
	import os
	import logging
	import logging.handlers

	root_logger = logging.getLogger("")
	formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
	root_logger.setLevel(logging.DEBUG)

	# stdout handler
	stream_handler = logging.StreamHandler()
	module.exports = (robot) ->

	robot.hear /ボールを相手のゴールに$/i, (msg) ->
	msg.reply "シュゥゥゥーッ！！"

	robot.hear /超(！\|!)$/i, (msg) ->
	msg.reply "エキサイティン！！"
	#!/usr/bin/env python
	# -- coding: UTF-8 --

	import os
	import sys
	from threading import Thread
	import threading
	import time
	import serial

	<!DOCTYPE html>
	<html>
	<head>
	<title>speech test</title>
	<meta charset="utf-8">
	</head>
	<body>
	<script type="text/javascript">
	var recognition = new webkitSpeechRecognition();
	# coding: utf-8
	import argparse
	import numpy as np
	from sklearn import svm
	from sklearn.multiclass import OneVsRestClassifier
	from sklearn.externals import joblib

	parser = argparse.ArgumentParser(description="svm")
	parser.add_argument("-pretrained_model", default=None)
	parser.add_argument("-train", default=None, help="data for train")