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#!/usr/bin/env python

# Linux usage: ./extract_tampermonkey_script.py "/home/<USER>/.config/<BROWSER>/Default/Local Extension Settings/<EXTENSION_ID>"
#        i.e.: ./extract_tampermonkey_script.py "/home/foo/.config/google-chrome-beta/Default/Local Extension Settings/gcalenpjmijncebpfijmoaglllgpjagf"
#   Mac usage: ./extract_tampermonkey_script.py "/Users/<USER>/Library/Application Support/Google/Chrome/Default/Local Extension Settings/<EXTENSION_ID>/"
#        i.e.: ./extract_tampermonkey_script.py "/Users/foo/Library/Application Support/Google/Chrome/Default/Local Extension Settings/dhdgffkkebhmkfjojejmpbldmpobfkfo/"

import leveldb
import sys
import re

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import random

def play(bankroll, wager_perc, prob_win, payout_perc, num_turns, seed):
    """ Plays a coin flipping game and returns the final balance
    Inputs:
        start (number):       starting bankroll
        wager_perc (number):  percent of bankroll you want to wager at each turn
        prob_win (number):    probability of a win (e.g. 0.5 is 50% win probability)
        payout_perc (number): the payout multiple in case of win (payout = payout_perc * wager)
        num_turns (number):   the number of turns in the game

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# coding: utf-8
# py2 origin author lrdcq
# usage python3 unwxapkg.py filename

__author__ = 'Integ: https://github.com./integ'

import sys, os
import struct

class WxapkgFile(object):

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#!/usr/bin/env python2
 
# lrdcq 
# usage python2 unwxapkg.py filename
 
import sys, os
import struct
 
class WxapkgFile(object):
  nameLen = 0

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Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

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#!/usr/bin/perl

#--------------------------------------------------
# Usage:
# ./speak.pl en input.txt output.mp3
#
# Prerequisites:
# sudo apt-get install libwww-perl libhtml-tree-perl sox libsox-fmt-mp3
#
# Compiling sox:

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# naivebayes.txt
#
# sex height weight  footsize
# male  6    180	12
# male	5.92 190	11
# male	5.58	170	12
# male	5.92	165	10
# female 5	100	6
# female 5.5	150	8
# female 5.42	130	7

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from __future__ import division, print_function, absolute_import

from keras.models import Sequential, model_from_json
from keras.layers import Dense, Dropout, Flatten, Conv3D, MaxPool3D, BatchNormalization, Input
from keras.optimizers import RMSprop
from keras.preprocessing.image import ImageDataGenerator
from keras.utils.np_utils import to_categorical
from keras.callbacks import ReduceLROnPlateau, TensorBoard

import h5py

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TODO

• Create a CLI-Interface with the following options:
  • Unicast or Multicast? Default: Unicast
  • Locally Administered or Globally Unique? Default: Locally Administered
  • Prescribe specific OUI (overwrites the above two)
  • Number of MACs to generate (they should not collide and be piped out separated by newlines)

Resources

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curl --header 'Authorization: token INSERTACCESSTOKENHERE' \
     --header 'Accept: application/vnd.github.v3.raw' \
     --remote-name \
     --location https://api.github.com/repos/owner/repo/contents/path

# Example...

TOKEN="INSERTACCESSTOKENHERE"
OWNER="BBC-News"
REPO="responsive-news"