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Introduction to Python Stack Implementation
A stack refers to a linear data structure that reserves data in a First-In/Last-Out (FILO) and Last-In/First-Out (LIFO) way. This stack can only be put in or removed at one particular side of it. The data storage is done as compared to arranging plates in the kitchen one above the other. One of the main features of the stack is the undo option. It works best for all kinds of events you are working on. In this article, you will be able to understand all you need to know about python stack implementation.
What is a Stack?
A stack is quite similar to the queues we see around us. In this sense, as mentioned above, it refers to a collection of items in a linear format. However, the order in which they are retrieved differs. Stacks can be used for different fields starting from implementing compound data structures like Graphs and Trees, to OSS (Operating System Software), in Language Parsing and Compilers. There are two types of operations that are done in a stack. These include:
- PUSH – PUSH is an operation element that is used if you want to add any element to the stack.
- POP – POP is an operation element that is used if you want to remove any element from a stack.
Some functions which are associated with a stack include:
- empty() – checks if the stack is empty
- size() – checks the stack’s size
- top() – checks for any reference at the highest element of the stack
- push(a) – puts the ‘a’ element in the highest range of the stack
- pop() – removes the highest element of a stack
Python Stack Implementation
There are different ways to use python stack implementation like using models from the python library and other data structures. Python stack implementation can be done in the following ways:
The Queue model includes a LIFO Queue which is essentially a stack. The put() function inserts data in the queue, and the get()function retrieves the data from the queue. This type of model mainly includes the following functions:
- maxsize – This refers to the maximum number of items that are allowed in the queue.
- empty() – If the queue is found to be empty, then items must return true. If not it would return as false.
- full() – Returns true if the queue contains items of maxsize. If the queue was created with the default (maxsize = 0), full() will never return as true.
- get() – Removes and returns a queue item. Must stand by till an item becomes available if the queue is seen as empty.
- get_nowait() – If an item is straight away available, return it. If not, raise QueueEmpty.
- put(item) – Put any item in the queue. If it is full, then wait to get a free space before adding the item back.
- put_nowait(item) – Putting items in a queue without having to block anything.
- qsize() – This function returns the total number of items in a queue. If there are no free slots available right away, set QueueFull to true.
The list data structure built into python can be utilized as a stack. Append() is used instead of push() in order to attach elements and the topmost stack, whereas pop() is used to remove the elements in a LIFO way.
However, this type of stack implementation has a few flaws. The main issue is that as it expands, it may encounter speed issues. The items available in the list are situated in memory next to each other. If the stack increases bigger as compared to the block of memory that holds it, Python must perform some allocations for the memory. As a result, some append() calls may take significantly longer than others.
The collections.deque class module can be used to implement a python stack. Deque is generally considered to be liked better as compared to other types of implementation when and if you require faster pop and append operation from both sides of the container. Deque has an O(1) complexity time for pop and append operations, whereas list has an O(n) complexity time.
Deque uses the same methods as mentioned in the list stack implementation above. These include both pop() and append().
The singly linked list has two types of constant. These include:
- addHead(item); and
These two constant methods are appropriate for implementing a stack.
- getSize() – Determines the number of items in a stack
- isEmpty () – If a stack is empty, then it will return true. However, if it is not empty, it will return as false.
- peek() – Returns the item at the top of the stack. However, it creates an exception when/if a stack is empty.
- push(value) – inserts a value at the top of a stack
- pop() – Returns and removes the value from the stack’s head. However, it creates an exception when/if a stack is empty.
Which Python Stack Implementation should you Choose?
Generally, the deque stack implementation is more beneficial if you decide not to use threading. However, if you want to use threading then you can choose the LifeQueue stack implementation. This would be useful unless and until you have studied the performance and come to the conclusion that a tiny increase in speed for popping and pushing is enough to make difference to gain a warranty for maintaining risks. List stack implementation is also beneficial, however, the only drawback is that it has the potential to have memory reallocation problems. Although the interface for Life is similar to that of the deque, where deque does not face these issues. Hence, the deque is considered to be the best choice if you want to use it for a non-threaded stack in python.
Python Stack Implementation will help you recognize which stack to select to get a good data structure and which method to implement to solve your issues. With the help of these stack implementations, you will be able to code easily and understand which method is the most suitable for you.