A Calculator (or two)

In this project you will build a simple interactive calculator.
The calculator is limited to integers (no floating-point numbers).

When you have completed the project, interaction with rpncalc.py will look like this:

Expression (return to quit):3 5 * x =
x = (3 * 5) => 15
Expression (return to quit):x 2 *
(x * 2) => 30
Expression (return to quit):
Bye! Thanks for the math!

Interaction with llcalc.py will look like this:

xpression (return to quit): x = 3 * (5 + 2)
x = (3 * (5 + 2)) => 21
Expression (return to quit):y = 7 * 3
y = (7 * 3) => 21
Expression (return to quit):x + y
(x + y) => 42
Expression (return to quit):
Bye! Thanks for the math!

Learning objectives

The calculator project provides practice in:

• "Refactoring" redundant code from concrete subclasses into a shared abstract base class.

• Using dynamic dispatch to tie together refactored code. Specifically, abstract base classes BinOp and UnOp will refer to methods and fields that exist only in the concrete subclasses like Plus and Neg.

• Recursive traversal of object structures. __str__, __repr__, and eval will make recursive calls in a style that is a little different than recursive functions you have written before.

Instructions

Guidance for building the calculator that interprets reverse Polish notation is in doc/HOWTO.md.

A separate document, doc/LLPARSING.md, describes how llcalc.py interprets algebraic notation like (3 + 4) * 12. doc/LLPARSING.md and llcalc.py are provided as extra reading if you are interested. You are not responsible for reading and understanding them, but you might find them interesting.

Turn in

The two files you should turn in are expr.py and rpncalc.py.

Overview: The expression structure

The heart of the calculator is the Expr class in expr.py. We can think of the expression structure as a tree. Nodes in the tree may be constants (like 7), variables (like x), or binary operations like addition, subtraction, multiplication, and division. Constants and variables are leaves of the expression tree. Binary operations are interior nodes with two children, their left and right operands.

Computer scientists and software developers customarily draw the root of a tree at the top and the leaves at the bottom. We are apparently not very good at botany.

Each node in the tree is represented by an object that has an eval method.
We begin at the root of the tree. Before we can evaluate that node, we must evaluate its left and right operands, and before we can evaluate its left operand, we must evaluate its left operand ... thus we work our way recursively down to the Var node at the leftmost leaf:

We have bound variable x to the constant value 7 with the assignment 7 x =, so the eval() method applied to Var("x") returns the value IntConst(7):

The IntConst(3).eval() returns IntConst(3), so now the Plus node can be evaluated. Seeing that both of its operands have evaluated to constants, it can add them and produce IntConst(10).

The Plus node at the root still needs to evaluate its right operand. If y is unbound (we have not given it a value), we will raise an exception. If we have given it a value, that value will be "bound" to the variable name in the "environment". In concrete terms, the environment is a dict with variable names as keys and IntConst objects as values. Assume for this example that the (key, value) pair ("y", IntConst(0)) is in the environment. We say that variable y is "bound" to 0. Evaluating the expression Var("y") the produces IntConst(0).

Now that the root node has the results of its operands, it returns its result: