This assignment invites you to run and observe two Python programs stored in files called demonstrate-map-function.py and demonstrate-reduce-function.py. Both of these programs demonstrate the use of higher-order functions that can accept as input a callable function and then use that function to perform a computation. Specifically, the demonstrate-map-function.py illustrates the use of a map(f, sequence) function that applies the function f to a list of data values called sequence. The demonstrate-reduce-function.py shows the use of a reduce(f, sequence, initial) function that starts at an initial value and then applies a function f to all of the values in sequence and returns a result. As you run these two programs and study their output you will explore an alternative approach to programming, called functional programming.
If you are a student enrolled in a Computer Science class at Allegheny College,
you can access this assignment by clicking the link provided to you in Discord.
Once you click this link it will create a GitHub repository that you can clone
to your computer. Specifically, you
will need to use the git clone command to download the project from GitHub to
your computer. Now you are ready to add source code and documentation to the
project!
If you change into the source directory of your GitHub repository, you will see a Python program called demonstrate-map-function.py. Your goal for this project is to implement both a map higher-order function and a square function that can serve as the input to the map function. When you run the command python demonstrate-map-function.py after adding the required source code to the program, it should produce the following output:
Squaring all of the numbers in the values tuple
(4, 9, 25, 49, 121)
Squaring all of the numbers output by range(10)
(0, 1, 4, 9, 16, 25, 36, 49, 64, 81)
It is worth noting that the demonstrate-map-function.py should contain the following source code that calls the map function to produce the aforementioned output. Line 1 of this code creates a tuple called values that contains five numbers and line 2 calls the map function by providing it square and the values. After you have correctly implemented the map and square functions the two print statements on lines 3 and 4 will produce the first two lines of output. As shown in the output, the next source code segment in demonstrate-map-function.py performs the same operation while using range(10) instead of the specific numbers in the values tuple.
You should also notice that the source directory of your GitHub repository
contains a Python program called demonstrate-map-function.py. Your goal for
this project is to implement a reduce higher-order function and both a plus
and a multiply function that perform arithmetic on two input numbers and can
serve as the input to the map function. When you run the command python after adding the required source code to the
program, it should produce the following output:
Adding all of the numbers together with a reduce function 15 Multiplying all of the numbers together with a reduce function 120
It is worth noting that the demonstrate-reduce-function.py should contain the
following source code that calls the reduce function to produce the
aforementioned output. Line 1 of this code creates a list called numbers
that contains five numbers and line 2 calls the reduce function by providing
it plus and the numbers list. After you have correctly implemented the
reduce and plus functions the two print statements on lines 3 and 4
will produce the first two lines of output. As shown in the output, the next
source code segment in demonstrate-reduce-function.py performs a similar
computation while calling reduce(multiply, numbers, 1) instead of
reduce(plus, numbers, 0). Why it is sensible to specify that the
initial parameter for reduce should be 1 instead of 0 when using the
multiply function instead of plus?
numbers = [1, 2, 3, 4, 5]
added_numbers = reduce(plus, numbers, 0)
print("Adding all of the numbers together with a reduce function")
print(" " + str(added_numbers))As you continue this source code survey, make sure to note that the function signatures in demonstrate-map-function.py look like those in the following list. This list demonstrates that these functions do not have type annotations. After providing the source code for the square and map functions in this file, please determine and add the type annotations for the formal parameters called value, f, and sequence. Similarly, there are three functions called plus, multiply, and reduce in the demonstrate-reduce-function.py file that do not have type annotations. You can study the source code of these functions and the way that they are called in the demonstrate-reduce-function.py script to learn more about what type annotations you should add to the formal parameters called number_one, number_two, f, sequence, and initial. When you add these type annotations, you should leverage them to enhance your understanding of the inputs, outputs, and behavior of a map-reduce computation.
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Functions in the
demonstrate-map-function.pyfile:def square(value)def map(f, sequence)
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Functions in the
demonstrate-reduce-function.pyfile:def plus(number_one, number_two)def multiply(number_one, number_two)def reduce(f, sequence, initial)
Since this project does not use Poetry to manage
project dependencies and virtual environments, it does not support the use of
commands like poetry run task test. However, you can use gatorgrade --config config/gatorgrade.yml to check your work. If gradle grade shows that all checks pass, you will know that you made progress towards correctly implementing and writing about this project's program.
Once you have finished all of the previous technical tasks, you can use a text editor to answer all of the questions in the writing/reflection.md file. Since this is a source code survey, you should provide output from running each of the provided Python programs on your own laptop and then explain how the program's source code produced that output. A specific goal for this project is for you to understand each line of source code needed to implement a simplified version of the map and reduce functions. You should also think carefully about the steps that you would need to take to implement a distributed and/or parallel computation that uses map and reduce to improve the efficiency of a program.
As you are working, you are to commit and push regularly. The commands are the following.
git add -A
git commit -m ``Your notes about commit here''
git pushAfter you have pushed your work to your repository, please visit the repository at the GitHub website (you may have to log-in using your browser) to verify that your files were correctly sent.
The grade that a student receives on this assignment will have the following components.
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GitHub Actions CI Build Status [up to 50%]:: For the repository associated with this assignment students will receive a checkmark grade if their last before-the-deadline build passes. This is only checking some baseline writing and commit requirements as well as correct running of the program. An additional reduction will be given if the commit log shows a cluster of commits at the end clearly used just to pass this requirement. An addition reduction will also be given if there is no commit during work times. All other requirements are evaluated manually.
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Mastery of Technical Writing [up to 25%]:: Students will also receive a checkmark grade when the responses to the writing questions presented in the
reflection.mdreveal a proficiency of both writing skills and technical knowledge. To receive a checkmark grade, the submitted writing should have correct spelling, grammar, and punctuation in addition to following the rules of Markdown and providing conceptually and technically accurate answers. -
Mastery of Technical Knowledge and Skills [up to 25%]: Students will receive a portion of their assignment grade when their program implementation reveals that they have mastered all of the technical knowledge and skills developed during the completion of this assignment. As a part of this grade, the instructor will assess aspects of the programming including, but not limited to, the completeness and the correctness of the program and the use of effective source code comments.
Students who have questions about this project outside of the class or lab times are invited to ask them in the course's Discord channel or during instructor's or TL's office hours.