Python Programming

L 3 C 3

Teachers Continuous Evaluation: 40 marks. Term-End Semester Examination: 60 marks.

Course outcomes

• Ability to write procedural programmes in Python.
• Ability to write programs using standard data structures.
• Ability to use object oriented paradigm to write program in Python.
• Ability to write modular program in Python

Unit I

Identifiers, keywords, indentation, comments, documentation strings, Unicode and encoding, data types and type hints, object identity vs equality, operator precedence and associativity, input/output (print formatting with f-strings, format(), old %), command-line arguments using sys.argv, control flow: if, elif, else, match statement (PEP 634), loops: for, while, break, continue, else with loops, iterator protocol (__iter__, __next__), comprehensions (list, set, dict, nested), unpacking and zipping, enumerate, zip, range.

Unit II

Defining and calling functions, arguments: positional, keyword, default, variable-length (*args, **kwargs), recursion, anonymous functions with lambda, map, filter, reduce, any, all, sorted, min, max with custom keys, first-class functions, closures, decorators (basic and with arguments), generators (yield, send), iterators vs generators, import system, module search path, creating and importing user-defined modules, packages and __init__.py, virtual environments and dependency management, built-in collections: list, tuple, dict, set, frozenset, Counter, defaultdict, OrderedDict, deque.

Unit III

Classes and objects, class and instance attributes, methods (self), constructor (__init__), attribute access control, class variables and methods (@classmethod, @staticmethod), inheritance, method overriding, composition vs inheritance, super(), abstract classes and interfaces using abc, operator overloading (__add__, __eq__, etc.), duck typing, multiple inheritance, MRO (Method Resolution Order), introspection (dir(), hasattr(), getattr()), exception hierarchy, custom exceptions, structured exception handling (try-except-else-finally), resource management with with, file I/O, JSON and CSV processing, pickling, error and exception best practices.

Unit IV

Modeling with Python data structures (lists, stacks, queues, dictionaries, sets), simulation problems, trees: node-based and list-based representations, binary tree traversal, recursion vs iteration, search and sorting using Pythonic methods, time and space complexity analysis using empirical profiling, introduction to timeit and cProfile, unit testing (unittest, doctest, pytest), assertions, type checking (mypy, typeguard), type annotations and gradual typing (PEP 484), introduction to NumPy arrays, basic file-based or JSON-based persistence, project structure, naming conventions (PEP 8), packaging and publishing modules, documentation with pydoc and sphinx.

Textbooks

• Fluent Python, Luciano Ramalho, O’Reilly Media, Latest Edition.

References

• Think Python: How to Think Like a Computer Scientist, Allen B. Downey, Green Tea Press, Latest Edition.
• Effective Python, Brett Slatkin, Addison-Wesley, Latest Edition.
• Python for Everybody, Charles Severance, Open Access Edition.
• Automate the Boring Stuff with Python, Al Sweigart, No Starch Press, Latest Edition.