Python Data Structures: Stacks, Queues, and Deques

سرفصل های دوره

Data structures like stacks and queues come up frequently in interviews for technical roles. Though many candidates may never encounter data structures in day-to-day programming, showing a mastery of these concepts can help you rock your next interview—and add to your coding toolkit. In this course, Erin Allard shows how to use Python to build the top three linear data structures: stacks, queues, and deques. She compares and contrasts the data structures and shows how to implement them in an object-oriented way in Python. Learn how to define each class and use Python's built-in methods to accomplish the necessary behaviors, such as push, pop, and peek; enqueue and dequeue; and add_front and remove_rear. Challenges in each chapter help practice your new skills and prepare for your next interview.

01 - Introduction

01 - Python data structures primer

02 - What you should know

02 - 1. Abstract Data Types and Data Structures

01 - Abstract data types

02 - Data structures

03 - 2. The Stack

01 - Stacks as a linear abstract data type

02 - Creating the stack class and its methods

03 - push()

04 - pop()

05 - peek()

06 - size()

07 - is_empty()

08 - Challenge Balanced symbols

09 - Balanced symbols solution approach

10 - Balanced symbols solution in code

04 - 3. The Queue

01 - Queues as a linear abstract data type

02 - Creating the queue class and its methods

03 - enqueue()

04 - dequeue()

05 - peek()

06 - size() and is_empty()

07 - Challenge Print queue

08 - Print queue solution approach

09 - Print queue solution in code

05 - 4. The Deque

01 - Dequeues as a linear abstract data type

02 - Creating the deque class and its methods

03 - add_rear() and add_front()

04 - remove_rear() and remove_front()

05 - peek_rear() and peek_front()

06 - size() and is_empty()

07 - Challenge Palindrome checker

08 - Palindrome checker solution approach

09 - Palindrome checker solution in code

06 - Conclusion

01 - Next steps

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تولید کننده: LinkedIn Learning (Lynda)