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generate_number(pct_per_digit): Takes one float as input. Returns a random number that is constructed as follows. First, use the function above to get a random number. This number will correspond to the length (number of digits) that the number generated by this function should have. For example, if that function returns 3, then this function should generate and return a random number with three digits. Note that the first digit of the number should never be 0 (but further digits, if any, can be 0). Note: As there are different ways to write this function, we will not be checking the specific examples below but only that the numbers returned from the function (given a length of n as returned from the function above) are equally distributed in the range 10n – 1) to (10") – 1. E.g., for n=5, from 10,000 to 99,999. That is, if we were to run your function many times, then any number in that range should be equally likely to be generated.

generate_number(pct_per_digit): Takes one float as input. Returns a random number that is constructed as follows. First, use the function above to get a random number. This number will correspond to the length (number of digits) that the number generated by this function should have. For example, if that function returns 3, then this function should generate and return a random number with three digits. Note that the first digit of the number should never be 0 (but further digits, if any, can be 0). Note: As there are different ways to write this function, we will not be checking the specific examples below but only that the numbers returned from the function (given a length of n as returned from the function above) are equally distributed in the range 10n – 1) to (10") – 1. E.g., for n=5, from 10,000 to 99,999. That is, if we were to run your function many times, then any number in that range should be equally likely to be generated.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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In python please

• generate_number(pct_per_digit): Takes one float as input. Returns a random number that is constructed as follows. First, use the function above to get a random number. This number will correspond to the length (number of digits) that the number generated by this function should have. For example, if that function returns 3, then this function should generate and return a random number with three digits. Note that the first digit of the number should never be 0 (but further digits, if any, can be 0). Note: As there are different ways to write this function, we will not be checking the specific examples below but only that the numbers returned from the function (given a length of n as returned from the function above) are equally distributed in the range 10'n – 1) to (10") – 1. E.g., for n=5, from 10,000 to 99,999. That is, if we were to run your function many times, then any number in that range should be equally likely to be generated. - >>> random. seed(1337) >>> generate_number(0) >>> random. seed(9002) >>> generate_number(0.5) 41700 • check_equivalency(tokens): Takes a list as input. Returns True if the list contains three elements, the second element is an equals sign ('='), and the first and third elements are equal to each other. Returns False otherwise. >>> check_equivalency([5, '=', 5]) True >>> check_equivalency([1, =', 2]) False >>> check_equivalency([4, 'x', 7]) False
Transcribed Image Text:• generate_number(pct_per_digit): Takes one float as input. Returns a random number that is constructed as follows. First, use the function above to get a random number. This number will correspond to the length (number of digits) that the number generated by this function should have. For example, if that function returns 3, then this function should generate and return a random number with three digits. Note that the first digit of the number should never be 0 (but further digits, if any, can be 0). Note: As there are different ways to write this function, we will not be checking the specific examples below but only that the numbers returned from the function (given a length of n as returned from the function above) are equally distributed in the range 10'n – 1) to (10") – 1. E.g., for n=5, from 10,000 to 99,999. That is, if we were to run your function many times, then any number in that range should be equally likely to be generated. - >>> random. seed(1337) >>> generate_number(0) >>> random. seed(9002) >>> generate_number(0.5) 41700 • check_equivalency(tokens): Takes a list as input. Returns True if the list contains three elements, the second element is an equals sign ('='), and the first and third elements are equal to each other. Returns False otherwise. >>> check_equivalency([5, '=', 5]) True >>> check_equivalency([1, =', 2]) False >>> check_equivalency([4, 'x', 7]) False
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