CS21 Week 8: Top-Down-Design, String and List Objects

Week 8 Topics

  • Review some Graphics Library features

  • Nested Loops Review

  • More List and String class methods

  • Top-Down Design

Monday

Today, we are going to quickly revisit some of the content we quickly went over in class on Friday before break, and learn some new List and String methods, and start talking about one of the main course topics: Top Down Design.

The Stack

In functionsWS.py is a program that you should not run yet, Instead, first open it in vim, and trace through its execution: (1) draw the stack at the point shown, and (2) list program output.

After you do this, you can try running the program to see if your output is correct.

You could also print out this file if you’d like to trace through on a printout: lpr functionsWS.py

Setting Coordinates

In your cs21/inclass/week07-oop subdirectory are two programs that use the Graphics Library’s setCoords method of the GraphWin class to re-define the x-y coordinate system in the way that we would like (by default, it is specified in pixel width, with point (0,0) in the top upper-left).

In setcoords.py is a program that calls win.setCoords(-pi, -1.5, pi, 1.5) (lower left (-pi, -1.5), upper right (pi, 1.5)) and generates a plot for the sin function using the math library.

In setcoords_try.py is another example program that calls win.setCoords(0,0,10,10) to set the window coordinates to (0,0) in the lower left at (10,10) in the upper right. Let’s open this one up and try drawing a circle somewhere in the lower right quadrant of the graphics window using this new coordinate mapping.

There are also some TODO comments in this file for some other things to try out. You can see our solution in setcoords_try_soln.py, but try them out first on your own.

Nested Loops

We’ve seen the classic for loop many times now:

for i in range(10):
    <LOOP BODY>

We know that the LOOP BODY can contain anything: print statements, calls to input(), if / else conditionals, and many other things. But what if we put another for loop inside the body of a loop?

Putting one loop in the body of another is called a nested loop, and it’s a common (and very helpful!) repetition pattern. Let’s look at some examples in nested.py.

In your cs21/inclass/week07-oop subdirectory is a program nested.py with some example nested loops. Let’s take a few minutes to review some of these.

String and List Objects

As we discussed last week, strings and lists are objects in Python, and thus we can invoke methods on string and list objects using dot notation (e.g., lst.append(6)).

We have also seen how we can write programs that modify the elements stored in a list (e.g., lst[i] = 13). A Python string is similar to a Python list in that they are both a sequence of values, and it would be nice if we could also modify individual elements (characters) in a string like we can modify elements in a list. However, unlike lists, strings are immutable, meaning that we cannot modify their elements.

Instead, in order to "modify" a string, we need to do the following:

  1. Create a list from the string using either the list constructor passing it the string, or using the split string method that returns a newly created list of single character strings, one from each character in the string (note: we will see that list and split do slightly different things in creating a new list from a string).

  2. Modify the elements in the list, changing one or more to point to new strings

  3. Create a new string from this list, using the join string method.

In cs21/inclass/w08-TDD is a file named list_n_string.py that contains some examples of invoking methods on string and list objects, and of converting strings to lists and lists to strings. Let’s take a look at this and see what it does.

Listed off this page are some other common string methods and other common list methods

Top Down Design

One of the primary topics in this class is Top Down Design (TDD), a problem solving technique that computer scientists use to solve larger problems. It is a technique that is done before coding where we:

  • Start with general description of problem

  • Break it into several high-level steps

  • Iteratively break the steps into smaller steps until you have steps that are easier to solve

Top-down design is a lot like creating a paper outline for a large paper where you start with the main sections, and iteratively refine each part with more and more detail until you are ready to start writing the paper.

When you use top-down design, your resulting program’s structure will match the above idea of an outline: the main function should have calls to a few high-level functions, one for each high-level step; high-level functions have calls to medium-level functions that implement sub-steps of the high-level steps; and so on.

After TDD, implementing the program involves:

  • writing program stubs for the functions in your program

  • iterative implementation and testing of functions, often in a bottom-up order (functions representing the lowest-level steps of the TDD first)

  • often, applying more TDD to refine parts further as we need to

In Labs 5 and 6 we did the TDD part for you, specifying the functions you should write and stepping you through the iterative implementation and testing of these functions to ultimately implement a larger program. In Lab 8, you are going to do the TDD part of implementing a larger program.

This week we will step through applying TDD and iterative implementation and testing to a problem together in class.

Wednesday

Top Down Design

One of the primary topics in this class is Top Down Design (TDD), a problem solving technique that computer scientists use to solve larger problems. It is a technique that is done before coding where we:

  • Start with general description of problem

  • Break it into several high-level steps

  • Iteratively break the steps into smaller steps until you have steps that are easier to solve

Top-down design is a lot like creating a paper outline for a large paper where you start with the main sections, and iteratively refine each part with more and more detail until you are ready to start writing the paper.

When you use top-down design, your resulting program’s structure will match the above idea of an outline: the main function should have calls to a few high-level functions, one for each high-level step; high-level functions have calls to medium-level functions that implement sub-steps of the high-level steps; and so on.

Iterative Refinement

When writing a large program, programmers use iterative refinement: do some top-down design, write function stubs for this part of code and maybe some implementation, then test. Iteratively, add more functions to accomplish subproblems, and perhaps refine some of the steps using top-down design, and test, and so on. The idea is to write some code, test it, then write a little more code, and test it before writing even more. Usually, I write a function, then test it, write another function, test it, …​ This way if I’m careful about testing, I know that if there is a bug in my program it is with the new code I’ve just added.

Function Prototyping

We often use prototyping to just put in function stubs so we can test the whole program’s flow of control without having to have a full implementation. For example, here is a stub for a function to compute square root (it doesn’t actually do anything related to the task, but we can call it from other parts of our program to see if the program’s flow matches the design):

def main():

    # a sample call to our function to see if it works
    test = squareRoot(16)

    # for now, the program doesn't crash, but returns an incorrect result
    # of the correct type. We can now go back an refine our function
    print("Answer is: %.2f " % (test))

def squareRoot(num):
    """
    This function computes the square root of a number.
      num: the number
      returns: the square root of num
    """

    print("inside squareRoot")

    # TODO: implement this function

    return 1  # a bogus return value, but it lets me run the program
              # and make calls to this function stub to "see" program flow

main()

Let’s try it out…​

We are going to walk through the process of designing a computer game to simulate the dice game Craps. The rules for a single game are as follows:

  1. A player rolls a pair of six-sided dice.

  2. If the initial roll in step 1 is a 2, 3, or 12, the player loses.

  3. If the initial roll in step 1 is a 7 or an 11, the player wins.

  4. Otherwise, the player must roll for point. In this case, the player keeps rolling until she re-rolls the initial roll in step 1. (a winning game), or rolls a 7 (a losing game).

What are the chances of winning a single game of craps? Instead of heading to the casino, let’s use our Computer Science top down design skills to see if this is a good game to play.

We are going to design a program that asks the user for the number of craps games to simulate, and then output the percentage of games won.

Friday

We are going to continue with TDD today.