Is the blueprint or map that defines how your program functions

What is a software blueprint?

A software blueprint is a high-level plan or outline used in the development of software.

When the term blueprint is used in programming, it usually refers to one of two related, yet slightly different concepts:

a high-level, graphical or written piece of documentation of software architecture («blueprint for humans«)

a piece of code serving as a template for code-generating tools that build or configure applications («blueprint for machines«)

Overall, software blueprints are a powerful tool for planning, building and maintaining software projects.

And first, let’s take a look into how software blueprints are used as documentation.

Blueprints as software design documentation

Blueprints may be used to design and document the architecture of applications. It serves as a high-level representation of software design that supports the development process in several ways:

As part of the planning process of upcoming feature work, a blueprint communicates implementation requirements across an engineering team more efficiently; a software architect may design a new feature and they can then use a blueprint to provide the feature requirements to the software engineers who will implement it later on.

In a similar manner, blueprints help teams consisting of both engineering and non-engineering professionals to collaborate on the development of business applications; blueprints empower stakeholders of either department to define requirements using common terminology that doesn’t require in-depth, technical knowledge. This way, a software blueprinting process reduces the number of cycles needed for planning, implementing and iterating on features by getting application requirements defined well from the beginning. This in turn helps to reduce the overall development time of applications significantly.

Through this process, blueprints become an effective strategy for maintaining documentation of software architecture. As a business goes through the iterative process of blueprinting feature work upfront and implementing features according to the design, a growing documentation for the business’s software architecture is created automatically.

Using Unified Modeling Language (UML) software architects oftentimes visualize the design of the systems they and their team are implementing. Many products and open-source tools support software design with UML, such as Papyrus, Visual Studio or Lucidchart.

For more insight into the rationale behind blueprints as documentation and UML specifically, you may want to continue reading «UmlAsBlueprint» by Martin Fowler.

But the term blueprint isn’t only used to describe software design plans that help people to implement said software. «Blueprint» also refers to those design plans that help computers to implement software automatically.

Blueprints as automatic programming templates

As part of the code generation process, the blueprint outlines the layout and configuration of the resulting program. This makes the blueprint useful in scaffolding and extending applications; a software engineer who uses blueprints in their development process can focus on the implementation of the business logic itself and worry less about how their implementation fits into the code base.

Therefore when used as code generator templates, blueprints improve the immediate developer experience significantly and can reduce overall development time. Lastly, they facilitate scaling and maintaining large applications by making extending applications easier.

Many different tools and frameworks already support blueprints and code generators for developers. This includes, for example and among many others, the Python web framework Flask, the Blueprint visual scripting system of Unreal Engine, and the JavaScript framework EmberJS.

Blueprints as documentation and automatic programming tool

Blueprints are a powerful tool in planning, documenting and implementing software applications.

Have you created or used software blueprints before? Let me know in the comments below!

object-oriented programming (OOP)

Object-oriented programming (OOP) is a computer programming model that organizes software design around data, or objects, rather than functions and logic. An object can be defined as a data field that has unique attributes and behavior.

OOP focuses on the objects that developers want to manipulate rather than the logic required to manipulate them. This approach to programming is well-suited for programs that are large, complex and actively updated or maintained. This includes programs for manufacturing and design, as well as mobile applications; for example, OOP can be used for manufacturing system simulation software.

The organization of an object-oriented program also makes the method beneficial to collaborative development, where projects are divided into groups. Additional benefits of OOP include code reusability, scalability and efficiency.

Examples of an object can range from physical entities, such as a human being who is described by properties like name and address, to small computer programs, such as widgets.

Once an object is known, it is labeled with a class of objects that defines the kind of data it contains and any logic sequences that can manipulate it. Each distinct logic sequence is known as a method. Objects can communicate with well-defined interfaces called messages.

The structure, or building blocks, of object-oriented programming include the following:

Object-oriented programming is based on the following principles:

While Simula is credited as being the first object-oriented programming language, many other programming languages are used with OOP today. But some programming languages pair with OOP better than others. For example, programming languages considered pure OOP languages treat everything as objects. Other programming languages are designed primarily for OOP, but with some procedural processes included.

For example, popular pure OOP languages include:

Programming languages designed primarily for OOP include:

Other programming languages that pair with OOP include:

Benefits of OOP include:

The object-oriented programming model has been criticized by developers for multiple reasons. The largest concern is that OOP overemphasizes the data component of software development and does not focus enough on computation or algorithms. Additionally, OOP code may be more complicated to write and take longer to compile.

Alternative methods to OOP include:

Most advanced programming languages enable developers to combine models, because they can be used for different programming methods. For example, JavaScript can be used for OOP and functional programming.

Developers who are working with OOP and microservices can address common microservices issues by applying the principles of OOP.

What Is Object-Oriented Programming? 4 Basic Concepts of OOP

By Kyle Herrity

Updated May 18, 2022 | Published February 25, 2020

Updated May 18, 2022

Published February 25, 2020

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Kyle Herrity is a seasoned software engineer with over 15 year of industry experience, ranging from high-level applications development to low-level embedded systems projects.

Knowledge of computer programming is in high demand in today’s technology-driven society. Understanding object-oriented programming (OOP) can be invaluable when developing and maintaining software programs.

In this article, we discuss the basic principles of OOP and explain them in easy-to-understand examples.

What is object-oriented programming?

Object-oriented programming combines a group of data attributes with functions or methods into a unit called an «object.» Typically, OOP languages are class-based, which means that a class defines the data attributes and functions as a blueprint for creating objects, which are instances of the class. Popular class-based OOP languages include Java

. Multiple independent objects may be instantiated—or represented—from the same class and interact with each other in complex ways.

A simple example would be a class representing a person. The person class would contain attributes to represent information such as the person’s age, name, height, etc. The class definition might also contain functions such as «sayMyName» which would simply print that person’s name to the screen.

A family could be constructed by instantiating person objects from the class for each member of the family. Each person object would contain different data attributes since each person is unique.

This programming style is pervasive in popular programming languages such as Java, C++, Python, JavaScript and C# among others. By defining sets of classes that represent and encapsulate objects in a program, the classes can be organized into modules, improving the structure and organization of software programs. Thus, developers often use OOP as a tool when they need to create complex programs since they are easier to reason in terms of classes and their relationships.

4 basic concepts of object-oriented programming

Object-oriented programming has four basic concepts: encapsulation, abstraction, inheritance and polymorphism. While these concepts may seem complex, understanding the general framework of how they work will help you understand the basics of an OOP computer program.

1. Encapsulation

The word “encapsulate” means to enclose something. Just like a pill «encapsulates» or contains the medication inside its coating, encapsulation works in a similar way in OOP: by forming a protective barrier around the information contained within a class from the rest of the code.

In OOP, we encapsulate by binding the data and functions that operate on that data into a single unit known as the class. This hides private details of a class from the outside world and only exposes functionality important for interfacing with it. When a class does not allow calling code access to its private data directly, we say that it is well encapsulated.

Example

Elaborating on the person class example from earlier, we might have private data in the class, such as «socialSecurityNumber,» that should not be exposed to other objects in the program. By encapsulating this data member as a private variable in the class, outside code would not have direct access and it would remain safe within that person’s object.

If a method is written in the person class to perform, say, a bank transaction called «bankTransaction(),» that function could then access the «socialSecurityNumber» variable as necessary. The person’s private data would be well encapsulated in such a class.

2. Abstraction

Often, it’s easier to reason and design a program when you can separate the interface of a class from its implementation, and focus on the interface. This is akin to treating a system as a “black box,” where it’s not important to understand the gory inner workings in order to reap the benefits of using it.

This process is called “abstraction” in OOP because we are abstracting away the implementation details of a class and only presenting a clean, easy-to-use interface via the class’s member functions. Carefully used, abstraction helps isolate the impact of changes made to the code so that if something goes wrong, the change will only affect the implementation details of a class and not the outside code.

Example

Think of a stereo system as an object with a complex logic board on the inside. It has buttons on the outside to allow for interaction with the object. When you press a button, you’re not thinking about what happens on the inside because you can’t see it. Even though you can’t see the logic board completing these functions as a result of pressing a button, it’s still performing them.

This is the concept of abstraction, which is incredibly useful in all areas of engineering and also applied to great effect in object-oriented programming.

Example

In OOP, we might have a class defined to represent the human body. One might define some functions as part of its publicly facing interface such as “walk()” or “eatFood().” Calling code could call these functions and remain completely oblivious to the complex inner workings of the human body and its necessary functions to perform the act of walking or eating. These details are completely hidden in the implementation of the walk() and eatFood() body functions and are abstracted away from the end-user. In these cases, it’s not important for calling code to understand how the brain coordinates walking or how the stomach manages digesting the food but rather simply that a human walked or ate.

3. Inheritance

Object-oriented languages that support classes almost always support the notion of “inheritance.” Classes can be organized into hierarchies where a class might have one or more parent or child classes. If a class has a parent class, we say it is derived or inherited from the parent class and it represents an “IS-A” type relationship. That is to say, the child class “IS-A” type of the parent class.

Therefore, if a class inherits from another class, it automatically obtains much of the same functionality and properties from that class and can be extended to contain separate code and data. A nice feature of inheritance is that it often leads to good code reuse since a parent class’s functions don’t need to be re-defined in any of its child classes.

Consider two classes: one being the superclass—or parent—and the other being the subclass—or child. The child class will inherit the properties of the parent class, possibly modifying or extending its behavior. Programmers applying the technique of inheritance arrange these classes into what is called an “IS-A” type of relationship.

Example

For instance, in the animal world, an insect could be represented by an Insect superclass. All insects share similar properties, such as having six legs and an exoskeleton. Subclasses might be defined for grasshoppers and ants. Because they inherit or are derived from the Insect class, they automatically share all insect properties.

4. Polymorphism

In OOP, polymorphism allows for the uniform treatment of classes in a hierarchy. Therefore, calling code only needs to be written to handle objects from the root of the hierarchy, and any object instantiated by any child class in the hierarchy will be handled in the same way.

Because derived objects share the same interface as their parents, the calling code can call any function in that class’ interface. At run-time, the appropriate function will be called depending on the type of object passed leading to possibly different behaviors.

Example

Suppose we have a class called, “Animal” and two child classes, “Cat,” and “Dog.” If the Animal class has a method to make a noise, called, “makeNoise,” then, we can override the «makeNoise» function that is inherited by the sub-classes, «Cat» and «Dog,» to be “meow” and “bark,” respectively. Another function can, then, be written that accepts any Animal object as a parameter and invokes its «makeNoise» member function. The noise will be different: either a “meow” or a “bark” depending on the type of animal object that was actually passed to the function.

OOPs Concepts in Python | Python OOPs Concepts

Learn about OOPS Concepts in Python.

Overview

Object-oriented programming (OOP) is a programming pattern based on the concept of objects. Objects consists of data and methods. The object’s data are it’s properties, that defines what it is. And the object’s methods, are it’s functions, that defines what the object can do. Object-oriented style of programming is very popular because of it’s ability to map the virtual world entities i.e. our code, to the real world objects. OOPS concepts are widely used by many popular programming languages due to the several advantages it provides.

In this article we will study about the OOPS concepts in python programming.

Scope of the Article

In this article, you’ll learn the following concepts:

The overall article will meet the scope we have mentioned above, and deal with all the OOPS concepts in python.

Introduction to Python OOPS

OOPS concepts in python are very closely related to our real world, where we write programs to solve our problems. Solving any problem by creating objects is the most popular approach in programming.

This approach is termed as Object Oriented Programming. Object oriented programming maps our code instructions with the real world problems, making it easier to write and simpler to understand. They map real-world entities(such as company and employee) as ‘software objects’ that have some ‘data’ associated with them and can perform some ‘functions’.

What is OOPS in Python?

OOPS in programming stands for Object Oriented Programming System. It is a programming paradigm or methodology, to design a program using classes and objects OOPS treats every entity as an object.

Object-oriented programming in Python is centered around objects. Any code written using OOPS is to solve our problem, but is represented in the form of Objects. We can create as many objects as we want, for a given class.

So what are objects? Objects are anything that has properties and some behaviours. The properties of objects are often referred to as variables of the object, and behaviours are referred to as the functions of the objects. Objects can be real-life or logical.

Suppose, a Pen is a real-life object. The property of a pen include: it’s color, type(gel pen or ball pen). And, the behaviour of the pen may include that, it can write, draw etc.

Some Major Benefits of OOPS Include:

Difference Between Object Oriented & Procedural Oriented Programming

Do you know Python follows 4 types of programming paradigms?

They include: imperative, functional, procedural, and object-oriented programming!

Here we will see the difference between 2 of the most important programming paradigms in Python: Procedural Oriented Programming (POP) & Object Oriented Programming (OOP). Let’s begin.

1. What are They?

In a similar way, POP requires a certain procedure of steps to operate. POP consists of functions. A POP program is divided into functions, each of which is dedicated to a specific task. The functions are arranged in a specific order and the program control flows sequentially.

OOP: OOP consists of objects. They divide the program into objects. These objects are the entities that combine the properties and methods of real-world objects.

2. Where are They Preferred?

POP is suitable for small tasks only. Because, the complexity of the code increases as the length of the program increases, and it ends up being filled with functions. It becomes even more difficult to debug.

OOP is suitable for larger problems. They can make the code reusable using recursion, which makes the code cleaner and less complicated.

3. Which Provides More Security?

POP is less secure, because it provides the functions, with all the data. So, our data is not hidden. POP is not a recommended option if you want to secure your credentials or any private information!

OOP is more secure because it provides you security through data hiding. OOP has a special concept known as «Encapsulation», which blesses it with the property of data hiding(we will read about this further).

4. Approach of Programming

POP follows the Top-down approach of programming. The top-down approach of programming, focuses on breaking down a big problem into smaller and understandable chunks of codes. Then it solves those smaller chunks of problems.

OOPS concepts, follows the Bottom-up approach of programming. The Bottom-Up approach first focuses on solving the smaller problems at the very fundamental level, and then integrating them into a whole and complete solution.

5. Usage of Access Modifiers:

Access specifiers or Access modifiers in python are used to limit the access of class variables and class methods outside of class while implementing the concepts of inheritance. This can be achieved by: Public, Private and Protected keywords.

Note:

Python’s access modifiers are extremely useful when using inheritance concepts. This concept can also be applied to class methods.

Class and Objects in Python

Suppose you wish to store the number of books you have, you can simply do that by using a variable. Or, say you want to calculate the sum of 5 numbers and store it in a variable, well, that can be done too!

Primitive data structures like numbers, strings, and lists are designed to store simple values in a variable. Suppose, your name, or square of a number, or count of some marbles (say).

But what if you need to store the details of all the Employees in your company? For example, you may try to store every employee in a list, you may later be confused about which index of the list represents what details of the employee(e.g. which is the name field, or the empID etc.)

Example:

Even if you try to store them in a dictionary, after an extent, the whole codebase will be too complex to handle. So, in these scenarios, we use Classes in python.

A class is used to create user-defined data structures in Python. Classes define functions, which are termed as methods, that describe the behaviors and actions that an object created from a class can perform. OOPS concepts in python majorly deals with classes and objects.

Classes make the code more manageable by avoiding complex codebases. It does so, by creating a blueprint or a design of how anything should be defined. It defines what properties or functions, any object which is derived from the class should have.

IMPORTANT:

An instance of a class is called the object. It is the implementation of the class and exists in real.

An object is a collection of data (variables) and methods (functions) that access the data. It is the real implementation of a class.

Quick Tip:

class = blueprint(suppose an architectural drawing). The Object is an actual thing that is built based on the ‘blueprint’ (suppose a house). An instance is a virtual copy (but not a real copy) of the object.

When a class is defined, only the blueprint of the object is created, and no memory is allocated to the class. Memory allocation occurs only when the object or instance is created. The object or instance contains the real data or information.

How to Define a Class in Python?

Syntax:

Indented code below the class definition is considered part of the class body.

‘pass’ is commonly used as placeholders, in the place of code whose implementation we may skip for the time being. «pass» allows us to run the code without throwing an error in Python.

What is an __init__ method?

The properties that all Human objects must have, are defined in a method called init(). Every time a new Human object is created, __init__() sets the initial state of the object by assigning the values of we provide inside the object’s properties. That is, __init__() initializes each new instance of the class. __init__() can take any number of parameters, but the first parameter is always a variable called self.

The self parameter is a reference to the current instance of the class. It means, the self parameter points to the address of the current object of a class, allowing us to access the data of its(the object’s) variables.

Note:

Let us see, how to define __init__() in the Human class:

Code:

self.name = ‘name’ creates an attribute called name and assigns to it the value of the name parameter.

self.age = age attribute is created and assigned to the value of age parameter passed.

self.gender = gender attribute is created and assigned to the value of gender parameter passed.

There are 2 types of attributes in Python:

1. Class Attribute:

These are the variables that are same for all instances of the class. They do not have new values for each new instance created. They are defined just below the class definition.

Code:

Here, the species will have a fixed value for any object we create.

2. Instance Attribute:

Instance attributes are the variables which are defined inside of any function in class. Instance attribute have different values for every instance of the class. These values depends upon the value we pass while creating the instance.

Code:

Here, name,age and gender are the instance attributes. They will have different values as for new instances of class.

For properties that should have a similar value per instance of a class, use class attributes. For properties that differ per instance, use instance attributes.

Creating an Object in Class

When we create a new object from a class, it is called instantiating an object. An object can be instantiated by the class name followed by the parantheses. We can assign the object of a class to any variable.

Syntax:

As soon as an object is instantiated, memory is allocated to them. So, if we compare 2 instances of a same class using ‘==’, it will return false(because both will have different memory assigned).

Suppose, we try to create objects of our Human class, then we also need to pass the values for name, age and gender.

Code:

Here, we have created 2 objects of the class Human passing all the required arguments.

Warning: If we do not pass the required arguments, it will throw a TypeError: TypeError: init() missing 3 required positional arguments: ‘name’, ‘age’ and ‘gender’.

Let us now see, how to access those values using objects of the class. We can access the values of the instances by using the dot notation.

Code:

Output:

So, we find that we can access the instance and class attributes just by using the dot operator.

Code:

Output:

However, we can change the value of class attributes, by assigning classname.classAttribute with any new value.

Code:

Output:

Instance Methods

Code:

Output:

This Human class has two instance methods:

Having gained a thorough knowledge of what Python classes, objects, and methods are, it is time for us to turn our focus towards the OOP core principles, upon which it is built.

Fundamentals of OOPS in Python

There are four fundamental concepts of Object-oriented programming –

Let us now look into each of the OOPS concepts in python deeply.

Inheritance

People often say to new born babies that they have got similar facial features to their parents, or that they have inherited certain features from their parents. It is likely that you too have noticed that you have inherited some or the other features from your parents.

Inheritance is the process by which a class can inherit or derive the properties(or data) and methods(or functions) of another class. Simply, the process of inheriting the properties of parent class into a child class is known as inheritance.

The class whose properties are inherited is the Parent class, and the class that inherits the properties from the Parent class is the Child class.

Let us see the syntax of inheritance in Python:

Code:

So, we define a normal class as we were defining in our previous examples. Then, we can define the child class and mention the parent class name, which it is inheriting in parentheses.

Code:

Output:

Let’s see the issue we face if we are trying to call child class’s methods using parent class’s object:

Code:

Output:

So, here we get the AttributeError: ‘Human’ object has no attribute ‘schoolName’. Because, the child classes can access the data and properties of parent class but vice versa is not possible.

Super()

Syntax: This is the syntax of the super function. We write the super() keyword followed by the method name we want to refer from our parent class.

Code:

Output:

Here, we have defined the dance() method in Human and Girl classes. But, both the methods have different implementations as you can see. In Human class, the dance method says «I can dance», whereas in Girl class, the dance method says «I can do classical dance». So, let us call the parent class’s dance method from the child class.

When we call any method using super(), the method in the superclass will be called even if there is a method with the same name in the subclass.

Polymorphism

Suppose, you are scrolling through your Instagram feeds on your phone. You suddenly felt like listening to some music as well, so you opened Spotify and started playing your favorite song. Then, after a while, you got a call, so you paused all the background activities you were doing, to answer it. It was your friend’s call, asking you to text the phone number of some person. So, you messaged him the number, and resumed your activities.

So, Polymorphism is something similar to that. ‘Poly‘ means multiple and ‘morph‘ means forms. So, polymorphism altogether means something that have multiple forms. Or, ‘some thing’ that can have multiple behaviours depending upon the situation.

Polymorphism in OOPS refers to the functions having the same names but carrying different functionalities. Or, having the same function name, but different function signature(parameters passed to the function).

A child class inherits all properties from it’s parent class methods. But sometimes, it wants to add it’s own implementation to the methods. There are ample of ways we can use polymorphism in Python.

Example of inbuilt polymorphic functions :

len() is an example of inbuilt polymorphic function. Because, we can use it to calclate the length of vaious types like string, list, tuple or dictionary, it will just compute the result and return.

Code:

Output:

Here we have passed a string, list and dictionary to the len function and it computed the result. So, it is the example of an inbuilt Polymorphic function.

We also have polymorphism with the ‘+’ addition operator. We can use it to ‘add’ integers or floats or any arithmetic addition operation. In the other hand, with String, it performs the ‘concatenation’ operation.

Code:

Output:

So, we can see that a single operator ‘+’ has been used to carry out different operations for distinct data types.

Polymorphism with Class Methods

We can perform polymorphism with the class methods. Lets see how:

Code:

Output:

Polymorphism with Inheritance

We can have polymorphism with inheritance as well. It is possible to modify a method in a child class that it has inherited from the parent class, adding it’s own implementation to the method. This process of re-implementing a method in the child class is known as Method Overriding. Here is an example that shows polymorphism with inheritance:

Code:

Output:

Here, the Square and Triangle class has overriden the method of the shape class. So, here the method no_of_sides has different implementations with respect to different shapes. So, it is in line with Polymorphism.

Encapsulation

You must have seen medicine capsules, where all the medicines remain enclosed inside the cover of the capsule. Basically, capsule encapsulates several combinations of medicine.

The process of binding data and corresponding methods (behavior) together into a single unit is called encapsulation in Python.

In other words, encapsulation is a programming technique that binds the class members (variables and methods) together and prevents them from being accessed by other classes. It is one of the concept of OOPS in Python.

Encalpsulation is a way to ensure security. It hides the data from the access of outsiders. An organization can protect its object/information against unwanted access by clients or any unauthorized person by encapsulating it.

Getters and setters

We mainly use encapsulation for Data Hiding. We does so by defining getter and setter methods for our classes. If anyone wants some data, they can only get it by calling the getter method. And, if they want to set some vlaue to the data, they must use the setter method for that, otherwise they won’t be able to do the same. But internally, how this getter and setter methods are performing remains hidden from outside world.

Code of getter & setter in Encapsulation

Output:

In the above example, we defined the getter getBookName() and setter setBookName() to get and set the names of books respectively. So, now we can only get and set the book names upon calling the methods, otherwise, we cannot directly get or modify any value. This promotes high security to our data, because others are not aware at a deep level how the following methods are implemented(if their access are restricted).

We can also promote safety of our data using access modifiers. Let’s see what are access modifiers.

Access Modifiers

Access modifiers limit access to the variables and methods of a class. Python provides three types of access modifiers private, public, and protected.

In Python, we don’t have direct access modifiers like public, private, and protected. We can achieve this by using single underscore and double underscores.

Single underscore _ represents Protected class. Double underscore __ represents Private class.

Suppose we try to make an Employee class:

Code:

Here, we have made the employee’s name public, employee’s ID protected and the employee’s salary private. Suppose we try to print all the values. Now, we will be able to access the employee’s name or his ID, but not the salary(because it is private). Look into the error below:

Output:

However, we can access the employee’s salary by calling that getter method getSalary() we have created in our Employee class.

Now, you might have understood the importance of getters and setters, and also the access modifiers which restricts the access to your data.

Complete code:

Output:

We can access private members from outside of a class by creating public method to access private members (just like we did above). There is one more method to get access called name mangling.

A protected data member is used when inheritance is used and you want the data members to have access only to the child classes.

So, encapsulation protects an object from unauthorized access. It allows private and protected access levels to prevent accidental data modification.

Abstraction

It is likely that you are reading this article on your laptop, phone, or tablet. You are also probably making notes, highlighting important points, and you may be saving some points in your internal files while reading it. As you read this, all you see before you is a ‘screen’ and all this data that is shown to you. As you type, all you see is the keys on the keyboard and you don’t have to worry about the internal details, like how pressing a key may lead to displaying that word onscreen. Or, how clicking on a button on your screen could open a new tab!

So, everything we can see here is at an abstract level. We are not able to see the internal details, but just the result it is producing(which actually matters to us).

Abstraction in a similar way, just shows us the functionalities anything holds, hiding all the implementations or inner details.

The main goal of Abstraction is to hide background details or any unnecessary implementation about the data so that users only see the required information. It helps in handling the complexity of the codes.

Key Points of Abstract classes

Syntax of Abstract Class in Python

To use abstraction, it is mandatory for us to import ABC class from the abc module.

Syntax:

ABC stands for Abstract Base class. The abc module provides the base for defining Abstract Base classes (ABC).

Let us take an example and see the implementation of abstract class:

So, the above code for your reference is:

Code:

Output:

Some notable points on Abstract classes are:

Advantages of OOPS in Python

Conclusion

With that, we come to the end of this tutorial. I hope you enjoyed it thoroughly.

Data Analysis with R Programming Coursera Quiz Answers

All Weeks Data Analysis with R Programming Coursera Quiz Answers

This course is the seventh course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll learn about the programming language known as R.

You’ll find out how to use RStudio, the environment that allows you to work with R. This course will also cover the software applications and tools that are unique to R, such as R packages.

You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Data Analysis with R Programming Coursera Quiz Answers

Data Analysis with R Programming Week 01 Quiz Answers

Quiz- 1

L2 Programming languages:

Quiz- 2

L3 R programming language:

Quiz- 3

L4 Programming with RStudio:

Data Analysis with R Programming Weekly challenge 1 Answers

Q6. RStudio’s integrated development environment lets you perform which of the following actions? Select all that apply.

Data Analysis with R Programming Week 02 Quiz Answers

Quiz- 1

L2 Programming concepts:

Quiz- 2

L3 Coding in R:

Q2. An analyst is checking the value of the variable x using a logical operator, so they run the following code:

Quiz- 3

L4 R Packages:

Quiz- 4

L5 Explore the tidyverse:

Q3. An analyst is organizing a dataset in RStudio using the following code:

arrange(filter(Storage_1, inventory >= 40), count)

Data Analysis with R Programming Weekly challenge 2 Answers

Q3. You want to create a vector with the values 12, 23, 51, in that exact order. After specifying the variable, what R code chunk allows you to create the vector?

Q5. A data analyst inputs the following code in RStudio:

Data Analysis with R Programming Week 03 Quiz Answers

Quiz- 1

L2 Explore data and R:

Quiz- 2

L3 Cleaning data:

Q2. A data analyst is trying to sort the penguins bill_length_mm data in descending order. They input the following code:

Quiz- 3

L4 R functions:

Q2. A data analyst inputs the following command:

quartet %>% group_by(set) %>% summarize(mean(x), sd(x), mean(y), sd(y), cor(x, y)).

Data Analysis with R Programming Weekly challenge 3 Answers

Q3. A data analyst is working with a large data frame. It contains so many columns that they don’t all fit on the screen at once. The analyst wants a quick list of all of the column names to get a better idea of what is in their data. What function should they use?

Q6. A data analyst is working with the penguins data. They write the following code:

Q7. A data analyst is working with the penguins dataset. They write the following code:

What code chunk does the analyst add to find the mean value for the variable body_mass_g?

Q12. A data analyst is studying weather data. They write the following code chunk:

Data Analysis with R Programming Week 04 Quiz Answers

Quiz- 1

L2 Aesthetics in analysis:

Quiz- 2

L3 Aesthetics in analysis:

Q3. You can use the color aesthetic to add color to the outline of each bar in a bar chart.

Quiz- 3

L4 Annotating and saving visualizations:

Q3. What function can you use to put a text label inside the grid of your plot to call out specific data points?

Data Analysis with R Programming Weekly challenge 4 Answers

Q3. A data analyst creates a plot using the following code chunk:

Which of the following represents a variable in the code chunk? Select all that apply.

Q5. A data analyst is working with the penguins data. The analyst creates a scatterplot with the following code:

What does the alpha aesthetic do to the appearance of the points on the plot?

Q6. You are working with the penguins dataset. You create a scatterplot with the following code chunk:

Q7. Fill in the blank: The _____ creates a scatterplot and then adds a small amount of random noise to each point in the plot to make the points easier to find.

Q10. You are working with the penguins dataset. You create a scatterplot with the following lines of code:

Data Analysis with R Programming Week 05 Quiz Answers

Quiz- 1

L2 Documentation and reports:

Q3. A data analyst creates an interactive version of their R Markdown document to share with other users that allows them to execute code the analyst wrote. What did they create?

Quiz- 2

L3 Creating R Markdown documents:

Q1. What information does a data analyst usually find in the header section of an RMarkdown document? Select all that apply.

Quiz- 3

L4 Code chunks:

Data Analysis with R Programming Weekly challenge 5 Answers

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Share Data Through the Art of Visualization

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