Python object oriented programming cheat sheet pdf

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Python object oriented programming cheat sheet pdf

From Computer Science See also Python Programming - Getting Started Following are terse descriptions for Python3 keywords, programming concepts, and commonly used functions. For more information, see w3schools for a bit more explanation and for the language reference. Contents 1 Keywords 2 Concepts 3 Commonly Used Functions Keywords The following are heavily used in all levels of Python programming. This is a minimum set of keywords to know how to use. break - exit the current loop continue - in a loop, go to next iteration of the loop is - determine whether two objects are the same object (not just value) import, from - to load a module def - declare a function while - loop with only condition if, elif, else - conditional statements (three keywords) for - loop with that iterates through a list return - keyword to send a value back from a function and - boolean operator, True only if both sides are True or - boolean operator, True if either side is True not - boolean operator, negates True, False - boolean values (two keywords) del - remove from a list by position try, except - handle an exception, basic use (2 keywords) raise, assert - raise/indicate an exception (2 keywords) in - test if something is inside of a list/string/tuple/dictionary None - special value for a variable that has no value pass - empty statement that does not do anything More Keywords These keywords are often not introduced or heavily used until the second Python course. as, finally, with, else - exception handling, more keywords (4 keywords) class - defining new class data type (for object-oriented programming) lambda - create unnamed / anonymous function global, nonlocal - access variables outside of current scope (2 keywords) async, await - for writing asynchronous code with asynchio package (2 keywords) yield - for creating generator functions Concepts See this video for a demo and explanation of basic data types and variables. These are terms that we use to describe programs. These are terms that have a precise meaning when talking about programs. string - text data type boolean - data type for True and False floating point - data type that stores numbers with fractional parts (e.g., 3.14 or 2.2) integer - data type that stores only integers None - a special value in Python that means "nothing" but is different than 0, False, and "" variable - name for a place in memory to store values. Two basic things you do with a variable - (i) store a value into the variable, (ii) get the value from the variable. keywords - also called reserved words - these are names that should not be used for variable names because they have special meaning to python. Example: for is used for loops and shouldn't be used as a variable name. function - also called procedures or methods - name for a block of code that does something and that your code can use when needed. Two basic things you can do with a function - (i) define what the function is (specify the code for the function), (ii) call the function later on in your code. Three main parts of defining function - (a) function code (called the body), (b) function parameters (aka input variables), (c) function return values. Three main parts of calling/using a function - (1) specify the arguments to the function (which are passed in to the parameters of the function), (2) call the function, (3) get the return value of the function. Note that the function prototype refers to the line that declares the function, which has the function name, return type, and list of parameters to the function. When a function is called, the arguments to the function are passed to the function (parameter variables are set equal to the arguments). flow chart - diagram that shows the steps / flow of control in a program (also used to diagram decision-making in other settings - e.g., diagnosis of an illness, managing a factory, ...) binary operator - operator that takes two values to produce a result. An example is addition, 2 + 3 results in 5. Another example is == comparison, 'hi' == 'bye' results in False because the two are not equal. unary operator - operator that takes one value to produce a result. An example is Boolean not, not True results in False. operator precedence - rules for which operators are evaluated first in an expression. For example, in 1 + 2 * 3, the multiplication is performed first, giving 1 + 6, and then the + is performed to result in 7. For Python, see . operator associativity - rule whether operators of the same type are evaluated left-to-right or right-to-left. Math operators are left-to-right. For Python, see . Commonly Used Functions print - function to write to the screen int, float, str - functions to convert to integer, floating point number, or string range - function to generate a sequence of numbers len - function to get the length of a string, list, or tuple open, read, write, close - functions for reading/writing text files and options 'r', 'w', 'a' for open string methods - isalpha, isdigit, split, join list methods - sort, index, append, remove, copy tuple methods - index, count dictionary methods - keys, values, items syntax for using strings, lists, tuples dictionaries - methods in random module - randint, shuffle methods in sys module - exit, argv list methods from the copy module - copy.deepcopy This Python OOP explains to you the Python object-oriented programming clearly so that you can apply it to develop software more effectively.By the end of this Python OOP module, you'll have good knowledge of object-oriented principles. And you'll know how to use Python syntax to create reliable and robust software applications.What you'll learnCreate objects in Python by defining classes and methods.Extend classes using inheritance.Understand when to use object-oriented features, and more importantly when not to use them.Who this tutorial is forIf you're new to object-oriented programming, or if you have basic Python skills and wish to learn in-depth how and when to correctly apply OOP in Python, this is the tutorial for you.Classes and objects ? learn how to define a class and create new objects from the class.__init__() method ? show you how to define a constructor for a class by using the __init__() method.Instance & class attributes ? understand instance attributes and class attributes, and more importantly when you should use class attributes.Private attributes ? learn about private attributes and how to use them effectively.Properties ? show you how to use the @property decorate to define properties for a class.Static methods ? explain to you static methods and shows you how to use them to group related functions in a class.__str__ method ? show you how to use the __str__ dunder method to return the string representation of an object.__repr__ method ? learn how to use the __repr__ method and the main difference between __str__ and __repr__ methods.__eq__ method ? learn how to define the equality logic for comparing objects by values.Section 4. InheritanceInheritance ? explain to you the inheritance concept and how to define a class that inherits from another class.Abstract classes ? show you how to define abstract classes and how to use them to create blueprints for other classes.Did you find this tutorial helpful ? What are Objects, Lists & Tuples?Properties of Objects, Lists & Tuples. Various Examples to get you started Q: What's the object-oriented way to become wealthy? A: Inheritance. Your vocabulary determines the reality of your life.In this tutorial, I have compiled the most essential terms and concepts of object-oriented programming in Python. My goal was to create the best Python OOP cheat sheet that shows them in one place. Well -- here it is:Download All 8+ Python Cheat SheetsDownload only this cheat sheet as PDFBefore we dive in the code from the Python OOP cheat sheet, let's swipe through the most important OOP concepts in this Instagram post: Want to get more printable PDF cheat sheets like the following one?Join my free email series with cheat sheets, free Python lessons, and continuous improvement in Python! It's fun! So let's study the code!class Dog: # class attribute is_hairy = True # constructor def __init__(self, name): # instance attribute self.name = name # method def bark(self): print("Wuff") bello = Dog("bello") paris = Dog("paris") print(bello.name) "bello" print(paris.name) "paris" class Cat: # method overloading def miau(self, times=1): print("miau " * times) fifi = Cat() fifi.miau() "miau " fifi.miau(5) "miau miau miau miau miau " # Dynamic attribute fifi.likes = "mice" print(fifi.likes) "mice" # Inheritance class Persian_Cat(Cat): classification = "Persian" mimi = Persian_Cat() print(mimi.miau(3)) "miau miau miau " print(mimi.classification) Before we dive into the vocabulary, here's an interactive Python shell: Exercise: Create a new class Tiger that inherits from the parent class Cat and add a custom method!Let's dive into the Vocabulary!OOP Terminology in PythonClass: A blueprint to create objects. It defines the data (attributes) and functionality (methods) of the objects. You can access both attributes and methods via the dot notation.Object (=instance): A piece of encapsulated data with functionality in your Python program that is built according to a class definition. Often, an object corresponds to a thing in the real world. An example is the object Obama that is created according to the class definition Person. An object consists of an arbitrary number of attributes and methods, encapsulated within a single unit.Instantiation: The process of creating an object of a class.Method: A subset of the overall functionality of an object. The method is defined similarly to a function (using the keyword def) in the class definition. An object can have an arbitrary number of methods.Method overloading: You may want to define a method in a way so that there are multiple options to call it. For example for class X, you define a method f(...) that can be called in three ways: f(a), f(a,b), or f(a,b,c). To this end, you can define the method with default parameters (e.g., f(a, b=None, c=None)).Attribute: A variable defined for a class (class attribute) or for an object (instance attribute). You use attributes to package data into enclosed units (class or instance).Class attribute (=class variable, static variable, static attribute): A variable that is created statically in the class definition and that is shared by all class objects.Dynamic attribute: An "?>instance attribute" that is defined dynamically during the execution of the program and that is not defined within any method. For example, you can simply add a new attribute neew to any object o by calling o.neew = ... .Instance attribute (=instance variable): A variable that holds data that belongs only to a single instance. Other instances do not share this variable (in contrast to "?>class attributes"). In most cases, you create an instance attribute x in the constructor when creating the instance itself using the self keywords (e.g., self.x = ... ).Inheritance: Class A can inherit certain characteristics (like attributes or methods) from class B. For example, the class Dog may inherit the attribute number_of_legs from the class Animal. In this case, you would define the inherited class Dog as follows: class Dog(Animal): ...Encapsulation: Binding together data and functionality that manipulates the data.If you have understood these OOP terms, you can follow most of the discussions about object-oriented programming. That's the first step towards proficiency in Python!Automate Your Learning Progress in PythonThanks for reading that far--you're clearly ambitious in mastering the Python programming language.For your convenience, I have created a Python cheat sheet email series where you will get tons of free stuff (cheat sheets, PDFs, lessons, code contests). Join 5,253 subscribers. It's fun! Where to Go From Here?Enough theory, let's get some practice!To become successful in coding, you need to get out there and solve real problems for real people. That's how you can become a six-figure earner easily. And that's how you polish the skills you really need in practice. After all, what's the use of learning theory that nobody ever needs?Practice projects is how you sharpen your saw in coding!Do you want to become a code master by focusing on practical code projects that actually earn you money and solve problems for people?Then become a Python freelance developer! It's the best way of approaching the task of improving your Python skills--even if you are a complete beginner.Join my free webinar "How to Build Your High-Income Skill Python" and watch how I grew my coding business online and how you can, too--from the comfort of your own home.Join the free webinar now! While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.To help students reach higher levels of Python success, he founded the programming education website . He's author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.

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