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Noms de pàgina coincidents:
- 1.1 Classes, Instances, Attributes, Methods — introduction
- 1.2 Working with class and instance data – instance variables
- 2.1 Python core syntax
- 2.2 Inheritance and polymorphism — Inheritance as a pillar of OOP
- 2.3 Extended function argument syntax
- 2.4 Decorators
- 2.5 Different faces of Python methods
- 2.6 Abstract classes
- 2.7 Encapsulation
- 2.8 Composition vs Inheritance - two ways to the same destination
- 2.9 Inheriting properties from built-in classes
- 3.1 Advanced techniques of creating and serving exceptions
- 4.1 Shallow and deep copy operations
- 4.2 Serialization of Python objects using the pickle module
- 4.3 Making Python objects persistent using the shelve module
- 5.1 Metaprogramming
Resultats de text complet:
- 3.1 Advanced techniques of creating and serving exceptions
- = 3.1 Advanced techniques of creating and serving exceptions In this module, we'll talk about Python exceptions – objects that represent errors which occur during the execution of a program that disrupts the nor
- 2.4 Decorators
- sses. The decorator's operation is based on wrapping the original function with a new "decorating" function (or class), hence the name "decoration". This is done by passing the original function (i.e., the **decorated** f
- 5.1 Metaprogramming
- = 5.1 Metaprogramming == Introduction to metaclasses Metaprogramming is a programming technique in which computer programs have the ability to modify their own or other
- 2.9 Inheriting properties from built-in classes
- = 2.9 Inheriting properties from built-in classes Python gives you the ability to create a class that inherits properties from any Python built-in class i
- 2.2 Inheritance and polymorphism — Inheritance as a pillar of OOP
- = 2.2 Inheritance and polymorphism — Inheritance as a pillar of OOP Inheritance is one of the fundamental concepts of object oriented programming, and expresses the fundamental relationships bet
- 4.1 Shallow and deep copy operations
- = 4.1 Shallow and deep copy operations == Copying objects using shallow and deep operations In this module, you’ll learn how to copy Python objects. Specifically, y... and deep copies of the objects. It’s hard to imagine writing a piece of Python code that performs any
- 2.1 Python core syntax
- = 2.1 Python core syntax So far we have been using Python core operations that allow us to operate on strings, lists, integers, and floats. It’s natural for us to formulate expressions using algebraic symbols representing operators, or to
- 2.6 Abstract classes
- ython is considered to be a very flexible programming language, but that doesn’t mean that there are n... ls to impose a set of functionalities or an order in a class hierarchy. When you develop a system in a group of programmers, it would be useful to have some means of establishing requirements for classes in matters of interface
- 2.8 Composition vs Inheritance - two ways to the same destination
- = 2.8 Composition vs Inheritance - two ways to the same destination So far we've been using and following the inheritance concept when modeling our classes to represent real-life issues. Inher
- 1.2 Working with class and instance data – instance variables
- = 1.2 Working with class and instance data – instance variables == Instance variables This kind of variable exists when and only when it is explicitl
- 2.5 Different faces of Python methods
- of Python methods Until now, we’ve been implementing methods that have performed operations on the instances (objects), and in particular the attributes of the instance, so we’ve called them i**nstance methods**. The instance m
- 1.1 Classes, Instances, Attributes, Methods — introduction
- = 1.1 Classes, Instances, Attributes, Methods — introduction == Introduction to Object-Oriented Programming This module addresses the advanced Object Oriented Programmi
- 2.7 Encapsulation
- Encapsulation is one of the fundamental concepts in object-oriented programming (amongst inheritance, polymorphism, and abstraction). It describes the idea of bundling attributes and methods that work on those attrib
- 4.2 Serialization of Python objects using the pickle module
- = 4.2 Serialization of Python objects using the pickle module In this section, you will learn how to persist Python objects for later use. **Pickling** is the process of preserving or extending the lifespan of food. The resulting food is called a pic
- 2.3 Extended function argument syntax
- ut function arguments, we should recall the following facts: * some functions can be invoked without arguments; * functions may require a specific nu... s; we have to pass a required number of arguments in an imposed order to follow function definition; * functions might have already defined default valu