Python: OOP and Pythonic Paradigms

Overview

Training Agenda

Day 1

Classes and Objects

• Objects, Types, Classes and Values in Python.
• Introspection of objects:
  • • id(), type(), dir()
    • hasattr(), getattr(), setattr(), delattr()
    • isinstance(), vars()
    • str(), repr(), bool()
    • callable(), iter(), reversed(), len()
• Python 3 OOP architecture
• Defining classes and instantiating objects.
• Classes and class attributes.
  • • __name__, __bases__, __doc__, __dict__, __class__.
• Instances and instance attributes.
• Class-Instance relationship: rules and bindings.
• Instance methods, class-methods and static-methods.
• More about the @classmethod and @staticmethod decorator
• Python special methods:
  • • Life-cyle methods: __new__(), __init__(), __del__()
    • Representational methods: __str__(), __repr__(), __len__(), __nonzero__()
    • Comparison methods: __eq__(), __ne__() and family.
  • Inheritance and Generalization techniques using Liskov Substitution Principle (LSP).
• Multiple inheritance support in Python: best practices and trade-offs.
• Using Duck-Typing as an alternative to Generalization approach.
• An overview on ABCs (available from Python 3.5).
• An overview on monkey-patching of Python built-ins, modules, user-defined functions, classes and their instances.
• Encapsulation in Python: best practices and trade-offs.

Day 2

Python data model methods (demonstrations / examples)

• Implementing context managers:
  • __enter__(), __exit__()
  • An overview on contextlib module
• Emulating numerical types:
  • __add__(), __sub__(), __mul__(), __truediv__()
  • __mod__(), __pow__(), __floordiv__(), __divmod__()
  • __iadd__(), __isub__() and family.
  • Bitwise operators – __lshift__(), __rshift()__ and family.
• Emulating subscriptability:
  • __getitem__(), __setitem__(), __delitem__()
• Emulating containers and iterable objects:
  • __len__(), __iter__(), __next__()
• Emulating callable objects using __call__() method
• Implementing custom accessors:
  • __getattr__(), __setattr__(), __delattr__()
  • Using @property decorator on implementing accessor patterns
  • Using __slots__ for implementing instance attributes

Day 3

Decorators and AOP features

• Creating and using decorators in Python.
• Creating decorators with arguments (parameterized decorators)
• Decorator-chaining (nested decorators).
• Dependency injection features: before, after and around filters.
• Sample use-cases and best practices for using decorators.
• Class-based decorators vs function-based decorators: best practices

Creating generators, iterators and co-routines.

• Understanding the concurrency problem while using standard procedural programming paradigm.
• Implementing concurrency using generators in Python.
• Creating a generator using yield statement.
• Interesting generator patterns in the itertools module.
• Creating co-routines using yield expressions.
• Creating execution-pipelines using generators and co-routines.
• An overview on asyncio based co-routines.