jjfiv

Q1: Draw the Chessboard

Fill in draw_chessboard() with a two-dimensional loop that calls the given draw_chessboard_cell(t, x, y) with 64 x,y pairs.

Q2: is_prime(n)

Write a function is_prime that takes an integer n and determines whether any numbers besides n and 1 evenly divide it.

• Consider zero not prime.
• Consider a negative number prime if it is prime when positive.

jjfiv

### Q1: Making Change [4 points]
#
# US Currency:
# dollar = 100c
# quarter = 25c
# dime = 10c
# nickel = 5c
# penny = 1c
#
# We would expect the following for 99 cents:

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from dataclasses import dataclass
from typing import List
from abc import ABC, abstractmethod


class DTreeNode(ABC):
    """ DTreeNode is an abstract class. All nodes in the Decision Tree can 'predict'. """

    @abstractmethod
    def predict(self, x: List[float]) -> float:

jjfiv

# v3_ids.gz
# gzipped list of document ids in v3 collection
python3 wapo-print-docids.py $COLLECTION | gzip > v3_ids.gz

# data/dup-pairs.gz
cat wapo-near-duplicates | awk '{print $1, $2}' > dup-pairs
gzip dup-pairs

jjfiv

import json, gzip, os
from tqdm import tqdm
import re

DIGITS = re.compile('\d+')

DATASET_PATH = os.path.join(os.environ['HOME'], 'data', 'poetry50k.dedup.jsonl.gz')

with gzip.open('windows.jsonl.gz', 'wt') as out:
    with gzip.open(DATASET_PATH, 'rt') as fp:

jjfiv

NICER_HMMM = """
#
# Calculate N factorial.
#
# Input: N
# Output: N!
#
# Register usage:
#
#  r1  N

jjfiv

def swap(xs, i, j):
    """
    Proj. 5:
    Given the list xs, swap elements i and j.
    
    Modify xs; don't return anything.
    """
    tmp = xs[i]
    xs[i] = xs[j]
    xs[j] = tmp

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def swap(xs, i, j):
    """
    Proj. 5:
    Given the list xs, swap elements i and j.
    """
    tmp = xs[i]
    xs[i] = xs[j]
    xs[j] = tmp
    
swap_ex = [1,2,3,4]

jjfiv

def swap(xs, i, j):
    """
    Proj. 5:
    Given the list xs, swap elements i and j.
    """
    tmp = xs[i]
    xs[i] = xs[j]
    xs[j] = tmp
    
swap_ex = [1,2,3,4]

jjfiv

def has_duplicates(xs):
    # Now with dictionaries:
    # create a dictionary "seen_already" that is empty.
    # loop over every element of xs
    #    if an element is in seen_already, return True
    #    else; add it to seen_already
    # if we haven't returned True by the end of the function, return False
    return False

assert(has_duplicates([1,2]) == False)