pmallory

import io
import sys
import urllib

import bs4
import requests
from PIL import Image

def get_image_list(url):
    """Given the url of an HTML document, return a list of urls of all images

pmallory

import time
import urllib

import bs4
import requests


start_url = "https://en.wikipedia.org/wiki/Special:Random"
target_url = "https://en.wikipedia.org/wiki/Philosophy"

pmallory

films = [('Brief Encounter', '1945'),
 ('Casablanca', '1942'),
 ('Before Sunrise', '1995'),
 ('Before Sunset', '2004'),
 ('Breathless', '1960'),
 ('In the Mood for Love', '2000'),
 ('The Apartment', '1960'),
 ('Hannah & Her Sisters', '1986'),
 ('Eternal Sunshine of the Spotless Mind', '2004'),
 ('Room With a View', '1985'),

pmallory

import math
import requests

class GitHubRepo:
    """
    A demonstration of iterables.

    You can iterate over the commits made to a GitHub repo by iterating over
    an instance of this class.

pmallory

P1 - Movie Trailer Website - Eduardo

# Project: Movie Trailer Website  - [Author’s Name]
================================

## Required Libraries and Dependencies
-----------------------------------
[In this section list your project’s dependencies. A basic Movie Website Trailer project requires Python v2.* to be installed]

pmallory

def fact(n):
    result =1
    for i in range(1, n+1):
        result *= i
    return result

pmallory

{
  "retirementStartYear": 2014,
  "retirementEndYear": 2043,
  "portfolio": {
    "initial": 8000,
    "percentEquities": 75,
    "percentBonds": 25,
    "percentGold": 0,
    "percentCash": 0,
    "percentFees": 0,

pmallory

# coding: utf-8
import csv
from collections import Counter
from pprint import pprint

with open('./440801.csv') as f:
  # data from 
    obs = []
    csv = csv.DictReader(f)
    for line in csv:

pmallory

from decimal import *

def count_ways(n, max_step_size=2):
    table = [Decimal(1), Decimal(1), Decimal(2)]
    assert len(table) >= max_step_size

    for i in xrange(3,n+1):
        table.append(sum(table[i-max_step_size:i]))

    return table[n]

pmallory

import matplotlib.pyplot as plt
import random

def binary_search(target, epsilon):
    guess = 1.0
    bottom = 1.0
    top = float("inf")
    steps = 0

    while abs(target-guess)>epsilon: