When should you use Python’s built-in data types, and when should you develop your own? In this video course, George Heineman introduces Python programmers to several important data structures and demonstrates their use with example algorithms. Generic data structures such as arrays, linked lists, and stacks can solve many problems, but to work through some specialized problems, you need to learn different ways to structure data appropriately.
Many Python programmers learned their skills through non-traditional routes, rather than through an undergraduate computer science degree. This video helps complete your education in fundamental data types step-by-step. For many of the data structures, you’ll write sample code using a variety of existing modules, and define a process that will help you evaluate and assess these modules for use in your own software. All you need to get started is a working knowledge of Python's built-in data types.
- Built-in Python data structures
- Python standard library types
- Design principles for data structures
- Data structures and associated algorithm examples
- Graph representations
- Heaps, circular buffers, balanced binary trees, and their variants
George T. Heineman is an associate professor of computer science at Worcester Polytechnic Institute in Massachusetts. His research interests are in software engineering. He is the author of Algorithms in a Nutshell and Working with Algorithms in Python, both for O’Reilly Media.
Table of contents
- Ubiquitous Lists
- Pointer Structures
- Recursive Structures
- Heap-based Structures
- Graph Representation
- Spatial Data Structures
- Title: Designing Data Structures in Python
- Release date: September 2015
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491928622
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