by | Released September 2015 | ISBN: 9781491928622

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.Topics include:Built-in Python data structuresPython standard library typesDesign principles for data structuresData structures and associated algorithm examplesGraph representationsHeaps, circular buffers, balanced binary trees, and their variantsGeorge 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. Show and hide more Publisher resources Download Example Code

1. Introduction
   • Welcome to the Course 00:06:28
2. Fundamentals
   • Built-in Data Types 00:22:04
   • API Operations 00:04:50
   • Analysis Techniques 00:18:15
   • Design Principles for Data Structures 00:16:59
3. Ubiquitous Lists
   • Using lists to Implement Stack 00:13:18
   • Principle: Separate Structure from Function 00:03:49
   • Example: Circular Buffer 00:24:24
   • Project: Moving Average / Stdev 00:12:55
4. Pointer Structures
   • Linked Lists 00:17:18
   • Queues 00:06:23
   • Project: Detect Cycles in Linked List 00:04:15
   • Prefix Tree 00:15:15
5. Recursive Structures
   • Binary Tree 00:22:57
   • Implementation of Remove 00:11:18
   • Binary Tree Retrieval Methods 00:08:39
   • Traversal 00:06:22
   • Binary Tree Extension 00:09:41
   • Balancing Binary Trees 00:26:03
6. Heap-based Structures
   • Heaps and heapq 00:21:04
   • Project: Huffman Encoded 00:12:51
   • Binary Heap 00:14:19
7. Graph Representation
   • Graphs with Adjacency Matrices 00:17:09
   • Graphs with Adjacency Lists 00:07:26
   • Third Party Python Libraries 00:08:12
8. Spatial Data Structures
   • KD-Trees 00:19:11
   • Quad-Trees 00:12:56
Show and hide more



9781491928622.designing.data.structures.OR.part1.rar

9781491928622.designing.data.structures.OR.part2.rar