Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.

Learn to implement classic algorithms and design new problem-solving algorithms using Python.

Autorentext
Magnus Lie Hetland is an experienced Python programmer, having used the language since the late 1990s. He is also an associate professor of algorithms at the Norwegian University of Science and Technology, having taught algorithms for the better part of a decade. Hetland is the author of Practical Python and Beginning Python, first and second editions, as well as several scientific papers.

Klappentext

Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

• The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner.
• The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs.

• Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.

  Inhalt
  The Basics.- Counting 101.- Induction and Recursion and Reduction.- Traversal: The Skeleton Key of Algorithmics.- Divide, Combine, and Conquer.- Greed Is Good? Prove It!.- Tangled Dependencies and Memoization.- From A to B with Edsger and Friends.- Matchings, Cuts, and Flows.- Hard Problems and (Limited) Sloppiness.