Introduction to Programming in Python: An Interdisciplinary Approach : 9780134076430

Introduction to Programming in Python: An Interdisciplinary Approach

Sedgewick & Wayne
Published by
Pearson Higher Ed USA
In stock
Title type
Title type
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it.

Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasises important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience.

This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science.

Coverage includes

  • Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound
  • Functions, modules, and libraries: organising programs into components that can be independently debugged, maintained, and reused
  • Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more
  • Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables
  • Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3
Table of contents
  • Chapter 1: Elements of Programming
  • 1.1 Your First Program
  • 1.2 Built-in Types of Data
  • 1.3 Conditionals and Loops
  • 1.4 Arrays
  • 1.5 Input and Output
  • 1.6 Case Study: Random Web Surfer
  • Chapter 2: Functions and Modules
  • 2.1 Defining Functions
  • 2.2 Modules and Clients
  • 2.3 Recursion
  • 2.4 Case Study: Percolation
  • Chapter 3: Object-Oriented Programming
  • 3.1 Using Data Types
  • 3.2 Creating Data Types
  • 3.3 Designing Data Types
  • 3.4 Case Study: N-Body Simulation
  • Chapter 4: Algorithms and Data Structures
  • 4.1 Performance
  • 4.2 Sorting and Searching
  • 4.3 Stacks and Queues
  • 4.4 Symbol Tables
  • 4.5 Case Study: Small-World Phenomenon
  • Context
  • Glossary
  • Index
Features & benefits
  • A broad-based, applications-based approach: teaches Python through examples from science, mathematics, engineering, and commercial computing
  • Focuses on what matters most: the most useful and important Python language features
  • Teaches through code tested for compatibility with Python 2.x and Python 3.x
  • Includes question-and-answer sections, exercises, and creative exercises throughout
Author biography

Robert Sedgewick is the William O. Baker professor of computer science at Princeton University. He has held visiting research positions at several advanced research laboratories and serves on the Adobe Systems board. He is also the coauthor (with Kevin Wayne) of Introduction to Programming in Java and Algorithms, Fourth Edition (both from Addison-Wesley).


Kevin Wayne is the Phillip Y. Goldman senior lecturer in computer science at Princeton University, where he has taught since 1998. He is an ACM Distinguished Educator and holds a Ph.D. in operations research and industrial engineering

from Cornell University.


Robert Dondero is a lecturer in computer science at Princeton University. He has taught there since 2001, earning eight excellence in engineering education awards, and a lifetime achievement award for excellence in teaching. He holds

a Ph.D. in information science and technology from Drexel University.

Sample Pages