tazjel’s gists

tazjel / bench.sh

Created August 6, 2013 05:40 — forked from davlgd/bench.sh

	#! /bin/bash

	### Blender compile & bench for Ubuntu
	### Author : LEGRAND David - PC INpact
	###
	### [email protected]
	### http://www.pcinpact.com
	###
	### test.blend is needed for benchmark
	### http://www.eofw.org/bench/

tazjel / replace.bash

Created August 6, 2013 05:49 — forked from PierrickKoch/replace.bash

 #!/bin/bash
 STR_ORIG="_blendobj"
 STR_REPL="_blender_object"
 files=$(grep -rlF "${STR_ORIG}" . --include=*.{py,rst} --exclude-dir="build" --exclude-dir=".git")
 # --exclude="${0}" --exclude="*.pyc" --exclude="*.blend"
 for f in $files; do
     sed -i "s/${STR_ORIG}/${STR_REPL}/g" $f

tazjel / samsung_remote.py

Created August 9, 2013 03:48 — forked from danielfaust/samsung_remote.py


	import time
	import socket
	import base64

	src = '192.168.1.2' # ip of remote
	mac = '00-AB-11-11-11-11' # mac of remote
	remote = 'python remote' # remote name
	dst = '192.168.1.3' # ip of tv
	app = 'python' # iphone..iapp.samsung

tazjel / install-sdk

Created August 18, 2013 15:21 — forked from rpetrich/install-sdk

	#!/bin/sh
	SDK=`dirname $0`
	SCRIPT=`basename $0`
	SDKPARENT=`dirname $SDK`

	PLATFORM=`uname -sp`
	if [ "$PLATFORM" = "Darwin i386" -o "$PLATFORM" = "Darwin x86_64" ]; then

	echo "iPhone Toolchain installer script by rpetrich"
	echo ""

tazjel / search.py

Created October 21, 2013 07:02 — forked from GaretJax/search.py

	import sys
	import re


	def iterwords(fh):
	for number, line in enumerate(fh):
	for word in re.split(r'\s+', line.strip()):
	# Preprocess the words here, for example to strip out punctuation
	# (the following example is sloooow, compile this regex if you
	# really want to use it):

tazjel / summary_tool.py

Created November 2, 2013 22:16 — forked from shlomibabluki/summary_tool.py

	# coding=UTF-8
	from __future__ import division
	import re

	# This is a naive text summarization algorithm
	# Created by Shlomi Babluki
	# April, 2013


	class SummaryTool(object):

tazjel / np_extractor.py

Created November 2, 2013 22:37 — forked from shlomibabluki/np_extractor.py

	# coding=UTF-8
	import nltk
	from nltk.corpus import brown

	# This is a fast and simple noun phrase extractor (based on NLTK)
	# Feel free to use it, just keep a link back to this post
	# http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/
	# Create by Shlomi Babluki
	# May, 2013

tazjel / np_extractor.py

Created November 2, 2013 22:44 — forked from shlomibabluki/np_extractor.py

	# coding=UTF-8
	import nltk
	from nltk.corpus import brown

	# This is a fast and simple noun phrase extractor (based on NLTK)
	# Feel free to use it, just keep a link back to this post
	# http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/
	# Create by Shlomi Babluki
	# May, 2013

tazjel / evaluate_taggers.py

Created November 3, 2013 17:39 — forked from sloria/evaluate_taggers.py

	#!/usr/bin/env python
	# -- coding: utf-8 --
	import string
	from text.blob import Blobber
	from text.taggers import PerceptronTagger, PatternTagger, NLTKTagger

	def accuracy(test_set, tagger):
	n_correct = 0
	total = 0
	tb = Blobber(pos_tagger=tagger)

tazjel / term_frequency.py

Created November 3, 2013 18:08 — forked from marcelcaraciolo/term_frequency.py

	auth = OAuthHandler(CLIENT_ID, CLIENT_SECRET, CALLBACK)
	auth.set_access_token(ACCESS_TOKEN)
	api = API(auth)


	venue = api.venues(id='4bd47eeb5631c9b69672a230')
	stopwords = nltk.corpus.stopwords.words('portuguese')
	tokenizer = RegexpTokenizer("[\w’]+", flags=re.UNICODE)

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