Implementing a Stack in PythonΒΆ
Now that we have clearly defined the stack as an abstract data type we will turn our attention to using Python to implement the stack. Recall that when we give an abstract data type a physical implementation we refer to the implementation as a data structure.
As we described in Chapter 1, in Python, as in any object-oriented programming language, the implementation of choice for an abstract data type such as a stack is the creation of a new class. The stack operations are implemented as methods. Further, to implement a stack, which is a collection of elements, it makes sense to utilize the power and simplicity of the primitive collections provided by Python. We will use a list.
Recall that the list class in Python provides an ordered collection
mechanism and a set of methods. For example, if we have the list
[2,5,3,6,7,4], we need only to decide which end of the list will be
considered the top of the stack and which will be the base. Once that
decision is made, the operations can be implemented using the list
methods such as append
and pop
.
The following stack implementation (ActiveCode 1) assumes that
the end of the list will hold the top element of the stack. As the stack
grows (as push
operations occur), new items will be added on the end
of the list. pop
operations will manipulate that same end.
Remember that nothing happens when we click the run
button other than the
definition of the class. We must create a Stack
object and then use it.
ActiveCode 2 shows the Stack
class in
action as we perform the sequence of operations from
Table 1. Notice that the definition of the Stack
class is
imported from the pythonds
module.
Note
The pythonds
module contains implementations of all data structures discussed in this book. It is structured according to the sections: basic, trees, and graphs. The module can be downloaded from pythonworks.org.
It is important to note that we could have chosen to implement the stack
using a list where the top is at the beginning instead of at the end. In
this case, the previous pop
and append
methods would no longer
work and we would have to index position 0 (the first item in the list)
explicitly using pop
and insert
. The implementation is shown in
CodeLens 1.
This ability to change the physical implementation of an abstract data
type while maintaining the logical characteristics is an example of
abstraction at work. However, even though the stack will work either
way, if we consider the performance of the two implementations, there is
definitely a difference. Recall that the append
and pop()
operations were both O(1). This means that the first implementation will
perform push and pop in constant time no matter how many items are on
the stack. The performance of the second implementation suffers in that
the insert(0)
and pop(0)
operations will both require O(n) for a
stack of size n. Clearly, even though the implementations are logically
equivalent, they would have very different timings when performing
benchmark testing.
Self Check
Q-10: Given the following sequence of stack operations, what is the top item on the stack when the sequence is complete?
m = Stack()
m.push('x')
m.push('y')
m.pop()
m.push('z')
m.peek()
Q-11: Given the following sequence of stack operations, what is the top item on the stack when the sequence is complete?
m = Stack()
m.push('x')
m.push('y')
m.push('z')
while not m.isEmpty():
m.pop()
m.pop()
Write a function revstring(mystr) that uses a stack to reverse the characters in a string.