Problem Solving and Programming with Python: For Anna University

The second edition of problem solving and programming with Python is designed as a textbook to meet the requirements of the Python programming course offered to the first year engineering students of Anna University. The book provides an introduction to the problem solving approaches and object Oriented Programming. It deals with the fundamentals and important features of Python language such as control statements, functions, strings, files, data structures, classes and objects, and exception handling. New to this edition new topics as required by the syllabus such as Python interpreter and interactive mode, fruitful functions, function composition, Mutability, list parameters, list as arrays, Boolean values and operators more illustrative examples added under algorithms, pseudocode, and flowcharts elaboration on topics such as modules, packages, command line arguments (under file handling) complete solutions for previous years’ Anna University question Papers of Python programming (Dec/ Jan 2017/18 and Dec/ Jan 2018/19) key features complete coverage of the problem solving and Python programming syllabus offered by Anna University. Simple and to-the-point explanations of concepts using numerous programming examples that make the text easy to understand. Detailed coverage of fundamental constructs, strings, file handling, classes, and exception handling in Python. Notes and programming tips provided to emphasize on the important concepts and help readers avoid common programming errors. Lab exercises and illustrative examples explained through algorithms and flowcharts to help readers hone their logical and programming abilities. Case studies on creating calculator, Calendar, and hash files, compressing strings and files, image processing, shuffling a deck of cards, and Mail merge along with programs are interspersed within the text. Strong chapter-end pedagogy including plenty of objective-type questions, review questions, programming and debugging exercises to facilitate revision and practice of concepts learnt. 2 Solved question papers and 2 Solved Model Question Papers included to help readers prepare for the University examinations. 6 annexures and 4 appendices covering differences between Python 2.X and 3.X, installing Python, debugging and testing, Turtle graphics, plotting graphs, and GUI programming provided to supplement the text. Br>

table of Contents 1. Algorithmic problem solving 2. Basics of Python programming 3. Control flow statements 4. Functions 5. Strings 6. Lists, tuples, and dictionaries 7. File handling 8. Error and exception handling, modules, packages online resources for faculty Chapter-wise PPTs solutions manual chapters on inheritance and operator overloading additional material for students lab exercises test Generator projects solutions to find the output and error exercises extra reading material additional algorithms, pseudocodes, and flowcharts.