gerryjenkinslb

gerryjenkinslb

# elapsed timer: as generator
# Youtube subscribe link: https://goo.gl/ZgZrZ5
# Gerry Jenkins

import time

class ElapsedTime():

    def __init__(self):
        # store only start time

gerryjenkinslb

# hexgame.py: to learn the hex digits for binary patterns
# written to run in python 2.7 and 3+
# Subscribe: https://www.youtube.com/user/gjenkinslbcc?sub_confirmation=1

from __future__ import division, print_function
from random import randrange
from time import time
import sys

hex_digits = '0123456789ABCDEF'

gerryjenkinslb

# gen sequence i.e. "1,3,5-7,9" > [1,3,5,6,7,9]
def seq_gen(s):
  for item in s.split(','):
      if '-' in item:
          a, b = map(int, item.split('-'))
          for i in range(a,b+1):
              yield i
      else:
          if len(item):
              yield int(item)

gerryjenkinslb

''' comparing speed of new dataclass 
    with standard class attributes and slots, 
    running in 3.7.0b1'''

# subscribe to me: https://www.youtube.com/user/gjenkinslbcc?sub_confirmation=1
# I recommend reading PEP557: https://www.python.org/dev/peps/pep-0557/
# this code at gist: http://bit.ly/slotsVdatclass

from dataclasses import dataclass
from timeit import timeit

gerryjenkinslb

""" One Example of how to implement a Adjacency Matrix implementation of a Graph Data Structure
    that matches the Abstract Data Type as defined in the eBook
    https://runestone.academy/runestone/static/pythonds/index.html
    and goes with the video course at http://youtube.com/gjenkinslbcc channel
    """


class Vertex(object):
    """vertex with key and optional data payload"""

gerryjenkinslb

""" Graph Data Structure: Adjacency List implementation
    that matches the Abstract Data Type as defined in the eBook
    https://runestone.academy/runestone/static/pythonds/index.html
    and goes with the video course at http://youtube.com/gjenkinslbcc channel
    This code is attributed to the book
    "Problem Solving with Algorithms and Data Structures using Python"
    by the Authors Bradley N. Miller and David Ranum
    under the Creative Commons
    Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA)
    License link: https://goo.gl/m2m1ww

gerryjenkinslb

# Undirected Graph ADT with edge data stored as adj_vertices dict for each Vertex
# The key to each edge is a nomalized tuple of the vertex ids ordered from low to high
# edge id (eid) for v1, v2  is (v1,v2) or (v2,v1) such that the first tuple item is less than second


def edge_id(v1,v2):  # normalize key v1,v2 to tuple (v_low,v_hi)
    return (v1, v2) if v1 <= v2 else (v2, v1)

class Vertex(object):

gerryjenkinslb

from bs4 import BeautifulSoup
import re
import requests
import csv
import time
import json

# version 1.1 added handling of youtube.com/channel/
#  to already handling of youtube.com/user based channels

gerryjenkinslb

import random
""" Create random events where event probabilities are 
    set by a frequency list
    This shows two functional approaches, the second being more terse
    and then a object oriented approach"""

# functional approach using a closure
# setup: x = event_gen(freq_table)
# get sample:  x() -> sample index
def event_gen(freq_table):