DSA with Python
However, this book is not simply a translation of those other books to Python. In adapting the material for this book, we have significantly redesigned the organization and content of the book as follows:
The code base has been entirely redesigned to take advantage of the features of Python, such as the use of generators for iterating elements of a collection.
Many algorithms that were presented as pseudo-code in the Java and C++ versions are directly presented as complete Python code.
In general, ADTs are defined to have consistent interface with Python’s built-in data types and those in Python’s collections module
Chapter 5 provides an in-depth exploration of the dynamic array-based un-derpinnings of Python’s built-in list, tuple, and str classes. New Appendix A serves as an additional reference regarding the functionality of the "str" class.
Over 450 illustrations have been created or revised.
New and revised exercises bring the overall total number to 750.
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