By Roberto Tamassia, Michael T. Goodrich, Michael H. Goldwasser
ISBN-10: 1118290275
ISBN-13: 9781118290279
In line with the authors’ industry best facts buildings books in Java and C++, this ebook bargains a accomplished, definitive advent to facts constructions in Python by way of authoritative authors. information constructions and Algorithms in Python is the 1st authoritative object-oriented booklet on hand for Python facts constructions. Designed to supply a finished advent to information buildings and algorithms, together with their layout, research, and implementation, the textual content will continue a similar common constitution as info constructions and Algorithms in Java and knowledge buildings and Algorithms in C++.
Begins by means of discussing Python’s conceptually basic syntax, which permits for a better concentrate on suggestions.
Employs a constant object-oriented standpoint during the textual content.
Presents every one facts constitution utilizing ADTs and their respective implementations and introduces very important layout styles as a way to arrange these implementations into periods, equipment, and items.
Provides an intensive dialogue at the research and layout of basic info buildings.
Includes many beneficial Python code examples, with resource code supplied at the web site.
Uses illustrations to give information constructions and algorithms, in addition to their research, in a transparent, visible demeanour.
Provides countless numbers of workouts that advertise creativity, aid readers the best way to imagine like programmers, and toughen vital suggestions.
Contains many Python-code and pseudo-code fragments, and 1000's of workouts, that are divided into approximately forty% reinforcement workouts, forty% creativity workouts, and 20% programming initiatives.
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Additional resources for Data Structures and Algorithms in Python
Example text
3 Expressions, Operators, and Precedence In the previous section, we demonstrated how names can be used to identify existing objects, and how literals and constructors can be used to create instances of built-in classes. Existing values can be combined into larger syntactic expressions using a variety of special symbols and keywords known as operators. The semantics of an operator depends upon the type of its operands. For example, when a and b are numbers, the syntax a + b indicates addition, while if a and b are strings, the operator indicates concatenation.
2. Objects in Python 9 Sequence Types: The list, tuple, and str Classes The list, tuple, and str classes are sequence types in Python, representing a collection of values in which the order is significant. The list class is the most general, representing a sequence of arbitrary objects (akin to an “array” in other languages). The tuple class is an immutable version of the list class, benefiting from a streamlined internal representation. The str class is specially designed for representing an immutable sequence of text characters.
Because input returns a string as its result, use of that function can be combined with the existing functionality of the string class, as described in Appendix A. split( ) # returns a list of strings, as separated by spaces x = float(pieces[0]) y = float(pieces[1]) A Sample Program Here is a simple, but complete, program that demonstrates the use of the input and print functions. The tools for formatting the final output is discussed in Appendix A. 67 age) # as per Med Sci Sports Exerc. 2 Files Files are typically accessed in Python beginning with a call to a built-in function, named open, that returns a proxy for interactions with the underlying file.