baali

# Something in lines of http://stackoverflow.com/questions/348630/how-can-i-download-all-emails-with-attachments-from-gmail
# Make sure you have IMAP enabled in your gmail settings.
# Right now it won't download same file name twice even if their contents are different.

import email
import getpass, imaplib
import os
import sys

detach_dir = '.'

baali

import vision_definitions
import numpy
import time
import Image

camProxy = ALProxy("ALVideoDevice", NAO_IP, PORT)
t0 = time.time()

# block to capture image from NAO's camera with 640x480 resolution and YUV422 colorspace
client = camProxy.subscribe("client", vision_definitions.kVGA, vision_definitions.kYUV422ColorSpace, 5)

baali

# usage python rot-n.py encodedeMessage n
# python rot-n.py "Va gur ryringbef, gur rkgebireg ybbxf ng gur BGURE thl'f fubrf." 13

import sys
if __name__ == '__main__':
    encodedMsg = sys.argv[1]
    n = int(sys.argv[2])
    # lets make everything lower case
    encodedMsg = encodedMsg.lower()
    decodedMsg = ''

baali

from urllib.parse import urlparse
def check_url_similarity(url_1, url_2):
    '''Method to compare two URLs to identify if they are same or not.
    Returns bool: True/False based on comparison'''
    def check_path(path_1, path_2):
        # handles cases where paths differ because of trailing /
        if path_1 == path_2:
            return True
        if path_1 == path_2+'/' or \
               path_1+'/' == path_2:

baali

'''
A hack based on this http://mikepultz.com/2011/03/accessing-google-speech-api-chrome-11/. While with smaller voice samples google speech to text works really good, as length increases quality decreases. So here using audiolab and numPy we are breaking audio sample, in smaller chunks, and removing blank/empty spaces from audio signal and then pushing them to google for processing. 
It takes wav file format as input but can be changed to other formats too.
'''

from scikits.audiolab import wavread, play, flacwrite
from numpy import average, array, hstack
import os
import sys

baali

# based on http://mikepultz.com/2011/03/accessing-google-speech-api-chrome-11/
# needs pyaudio package http://people.csail.mit.edu/hubert/pyaudio/
# Linux based, sox commands to convert from way to flac format.

import pyaudio
import wave
import subprocess, shlex

CHUNK = 1024
FORMAT = pyaudio.paInt16

baali

def swear(self, mess, args):
 "swears randomley from a list of high level swear words"
 swears = ["neech","kameen","kuttey", "howley", "saaley", "monkey", " kaachina vennela to tea pettukune mohavu nuvvu nu ","thitlu adukkunne mohamu nuvvoonu ", " currentu teegaki uyyala eskune ooge mohavu nuvvu" ,  "donkey", "vudathalu patte mokam", "chapathi mokam", "washbasin lo chepalu patte mokam", "gaali vaanalo visnakarrlu ammukune mokam", "Chunchu mokam", "ghootley", "jaffa", "tussha", "daffa", "jumper mein bumper", "panther pagdi" ,"lapaki paapa" ]
 from random import choice
 self.message_queue.append(choice(swears)+ " " + choice(swears) + " " + choice(swears) + " "+ args)

baali

Keybase proof

I hereby claim:

• I am baali on github.
• I am baali (https://keybase.io/baali) on keybase.
• I have a public key whose fingerprint is F891 136A 3FFB 0C7A B11E CDB5 5DB9 B0A6 8529 E773

To claim this, I am signing this object:

baali

import sys
import audioop
try:
    import pyaudio
except ImportError:
    sys.exit('You need to install pyaudio to installed to run this demo.')

SAMPLING_RATE = 22050
NUM_SAMPLES = 1024
line = None

baali

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import linear_kernel
import numpy as np
from itertools import combinations
from random import shuffle

def majorclust_sklearn():    
    texts = [
        "foo blub baz",
        "foo bar baz",