CSCI 1100代写、Python程序语音代写

日期：2022-10-12 10:25

CSCI 1100 — Computer Science 1 Homework 4

Loops and Lists; Passwords and Quarantine

Overview

This homework is worth 100 points total toward your overall homework grade. It is due Thursday,

October 13, 2022 at 11:59:59 pm. As usual, there will be a mix of autograded points, instructor

test case points, and TA graded points. There are two parts in the homework, each to be submitted

separately. All parts should be submitted by the deadline or your program will be considered late.

See the handout for Submission Guidelines and Collaboration Policy for a discussion on grading

and on what is considered excessive collaboration. These rules will be in force for the rest of the

semester.

You will need the utilities and data files we provide in hw4_files.zip, so be sure to download this

file from the Course Materials section of Submitty and unzip it into your directory for HW 4.

Module hw4_util.py is written to help you read information from the files. You do not need to

know how functions provided in hw4_util.py are implemented (but feel free to examine the code,

if you are interested), you can simply use them.

Final note, you will need to use loops in this assignment. We will leave the choice of the loop type

up to you. Please feel free to use while loops or for loops depending on the task and your personal

preference.

Part 1 — Password Strength

Often when you create a password it is judged for its strength. The estimate of strength is compute

by applying several rules — about the length of the password, the presence of certain types of

characters, its match against common passwords, and even its match against license plates. In this

part of the homework you will implement a few simple strength judgment rules and then determine

if a password is to be rejected, or rated poor, fair, good or excellent.

Your program should start by asking for and reading in a password. The program should then

evaluate the password based on the following rules. Each rule contributes to a numerical score

(which starts at 0):

1. Length: If the password is 6 or 7 characters long then add 1 to the score; if it is 8, 9 or 10

characters long then add 2; and longer than 10 add 3.

2. Case: If it contains at least two upper case letters and two lower case letters add 2 to the

score, while if it contains at least one of each, add 1 to the score.

3. Digits: If it contains at least two digits add 2 to the score and if it contains at least one digit

then add 1.

4. Punctuation: If it contains at least one of !@#$ add 1 and if it contains at least one of %^&*

then add 1 (total possible of 2).

5. NY License: If it contains three letters (upper or lower case) followed by four digits, then

it potentially matches a NY state license plate. In this case, subtract 2 from the score.

6. Common Password: If the lower case version of the password exactly matches a password

found in a list of common passwords, then subtract 3 from the score.

Whenever a rule is applied that creates a change in the score, generate an explanatory line of

output. After applying all the rules, output the score and then convert it to a final strength rating

of the password:

ˆ Rejected: the score is less than or equal to 0.

ˆ Poor: the score is 1 or 2.

ˆ Fair: the score is 3 or 4

ˆ Good: the score is 5 or 6

ˆ Excellent: the score is 7 or above.

Part 1 Notes

1. For this part and for part 2 you should write functions to keep the code clean, clear and easy

to manage.

2. We have provided you with a number of examples that show output values and formatting.

Please follow these examples closely.

3. The common passwords are extracted from a file. One of the utility functions we have provided

reads this file and return a list of these passwords. To use this function, start by making sure

that hw4_util.py and password_list_top_100.txt are in the same folder as your code.

Then add the line

import hw4_util

into your program. Finally, call function hw4_util.part1_get_top with no arguments. It

will return a list of strings containing 100 passwords for you to compare against.

4. Submit only your program file hw4_part1.py. Do not submit hw4_util.py.

Part 2 — COVID-19 Quarantine States

The NY State COVID-19 Travel Advisory at

https://coronavirus.health.ny.gov/covid-19-travel-advisory

requires that individuals who travel to New York from states that have significant community

spread of COVID-19 must self-quarantine for 14 days. “Significant spread” in a state is measured

as either

ˆ a daily average of more than 10 people per 100,000 residents tested positive in the previous

seven days, or

ˆ a daily average of more than 10% of tests were positive in the previous seven days.

(See https://coronavirus.health.ny.gov/covid-19-travel-advisory.) We will refer to states

having a significant spread as quarantine states. In this part of HW 4 you will use per state data

downloaded from https://covidtracking.com/ to answer queries about which states were quarantine states and when.

The data we obtained was downloaded (on October 5) in the form of a large “comma-separated

value” file. This file contains one line per day per state, and there are many fields per line. We

have condensed it to a form suitable for a CS 1 homework. The data are shared under the Creative

Commons BY 4.0 license which means we can

ˆ Share: copy and redistribute the material in any medium or format and

ˆ Adapt: remix, transform, and build upon the material for any purpose, even commercially.

Note that there are other versions of the Creative Commons BY 4.0 license that are more restrictive

in the uses they allow.

We have provided a simple utility to give you access to the condensed data. To use this (similar to

Part 1) you must have the files hw4_util.py and prob2_data.csv in the same folder as your own

code. You must then

import hw4_util

into your program. hw4_util has a function called part2_get_week that accepts a single integer

argument, w, and returns a list of lists. Argument w is the index of a previous week, with w==1

being the most recent week, w==2 being the week before that, etc., up to w==29 which corresponds

to 29 weeks ago, all the way back to March 15. The returned list contains one list per state, plus

the District of Columbia (DC) and Puerto Rico (PR) — 52 in all. Each state list has 16 items:

ˆ Item 0 is a string giving the two letter (upper case) state abbreviation. These are correct.

ˆ Item 1 is an integer giving the state’s population estimate — from the 2019 Census Bureau estimate https://www.census.gov/newsroom/press-kits/2019/national-state-estimates.

html.

ˆ Items 2-8 are the number of positive tests for that state in each of the seven days of the

specified week — most recent day first.

ˆ Items 9-15 are the number of negative tests for the state in each of the seven days of the

specified week — most recent day first.

For example, the list for Alaska for week 1 is

['AK',731545,189,147,128,132,106,125,118,3373,3819,6839,4984,6045,6140,1688]

Here is what you need to do for this assignment. Your program, in a loop, must start by asking

the user to specify the index for a week, as described above. (You may assume an integer is input

as the week number.) A negative number for the week indicates that the program should end. For

non-negative numbers, if the data are not available for that week the function will return an empty

list; in this case, skip the rest of loop body. Otherwise, after getting the list of lists back, the

program should answer one of four different requests for information about that week. Answering

the request starts by the user typing in a keyword. The keywords are 'daily', 'pct', 'quar',

'high'. Here’s what the program must do for each request:

ˆ 'daily': Ask the user for the state abbreviation and then output the average daily positive

cases per 100,000 people for that state for the given week, accurate to the nearest tenth.

ˆ 'pct': Ask the user for the state abbreviation and then output the average daily percentage

of tests that are positive over the week, accurate to the nearest tenth of a percent.

ˆ 'quar': Output the list of state abbreviations, alphabetically by two-letter abbreviation,

of travel quaratine states for the given week as discussed above. There should be ten state

abbreviations per line — call hw4_util.print_abbreviations with your list of abbreviations

to print the output as required. (Note: every week has at least one quarantine state.)

ˆ 'high': Output the two-letter abbreviation of the state that had the highest daily average

number of positive cases per 100,000 people over the given week, and output this average

number, accurate to the nearest tenth.

Input key words and state abbreviations may be typed in upper or lower case and still match

correctly. If a key word is not one of these four or if a state is not found (because its abbreviation is

incorrectly typed), output a simple error message and do nothing more in the current loop iteration.

Part 2 Notes:

1. As always, look at the example output we provide and follow it accurately.

2. All reported values for numbers of positive and negative test results will be at least 0; however,

some may be 0. You may assume, however, that there will never be a week where all days

have 0 negative tests.

3. Compute the daily percentage of tests that are positives by summing the positive cases for

the week, and summing negative cases for the week. If these sums are P and N respectively,

then the percentage positive is P/(P + N) ∗ 100. This is not exactly the same as the average

of daily percentages for a week, but it is easier to compute.

4. Submit only your program file hw4_part2.py. Do not submit hw4_util.py.