Python is an amazing & essential programming language to master in advanced domains like Data Science, Web Development, Robotics, the Internet of Things (IoT) & more. With its extensive usage on various apps, Python has emerged as a computer language with rapid development.
Python’s app in cutting-edge technologies like Data Science, Machine Learning & Artificial Intelligence is a major factor in its popularity. This tech's efficiency, simplicity & adaptability have also transformed software development.
After JS, Python is the 2nd most famous programming language on GitHub. If you want to learn Python from scratch, or you already got some coding experience & looking to upscale your skills for more job opportunities & careers, then this blog is for you!
Python is a commonly used advanced general-purpose programming language in the developer community. Its syntax enables programmers to express concepts in fewer lines of code since it was built with a strong emphasis on code readability.
What does a Python program look like? Let’s look at an example of adding 2 numbers,
Here’s how the input should look.
And the output will look like this:
This simple Python program calculated the sum of 2 numbers the user entered. But why use Python over other programming languages?
It’s only because of increasing popularity & demands are some of the notable factors.
Additionally, it’s a fairly universal language. It is utilized by several other massive corporations, including FB, NASA, Reditt & Amazon, in a wide range of projects. They value the features of Python, such as robustness & flexibility. Hence, its global adoption is set to elevate on a large scale.
Let’s know some more about it.
Python has emerged as the language for developers creating Artificial Intelligence (AI) apps. Python appeals to data scientists and machine learning engineers because of its simplicity, readability, and many libraries.
According to Jeff Hammond, vice president & lead analyst at Forrester - "We see something of a renaissance because Python has shown to be very helpful for folks doing artificial intelligence or machine learning type of things...There is some excellent structure. You have some wonderful tools for data scientists or those who want to be data scientists."
But what else makes Python the go-to choice for AI development?
Python has prebuilt libraries such as NumPy for scientific calculations, Scipy for sophisticated computing, and Pybrain for machine learning (Python Machine Learning), making it one of the top languages for AI.
Some libraries include:
Python developers worldwide provide considerable support and guidance through tutorials and forums, making it much easier to aid the coder than with another popular language. For instance, PyLadies is a global association for women and other gender minorities who enjoy Python coding.
Python is platform-independent, making it one of the most versatile and well-known solutions for numerous platforms and technologies, with only minor changes to the coding basics.
Python offers the most versatility of any application, having the choice of using an OOPs technique or scripting. You can also utilize the IDE to search for all codes and help developers suffering from different algorithms.
So, where is Python being used in AI? In many ways. Spotify, the music streaming service, primarily employs Python for data analysis and backend support. They use a Python program called Luigi to simplify the execution of thousands of task processes.
Skyscanner, a travel business, implemented a Python-based unsupervised algorithm to anticipate how new flight routes would perform. In the financial business, AI handles issues such as automation, customized banking, fraud prevention, and risk management. In this way, it raises the standard of financial services.
AI is transforming the healthcare industry by assisting in the scanning, detecting, and predicting ailments. Through mobile-friendly apps, it assists people in maintaining excellent health. For example, AirCure is a business that ensures patients receive the proper meds on time. They use Python to assist them with action, pill, and face recognition.
Python provides strong data analysis capabilities, allowing you to go deeper into your data and extract more insights. Python's simplicity and readability make building and expressing data-driven insights easier.
Installing any programming language is the first step toward learning it. Python currently comes with the majority of operating systems. To see if Python is accessible, use the following command in your terminal:
You’ll notice the output.
Please keep in mind that your Python version may differ. You can skip this part if you have Python installed and the version is above 3.5.2.
Once installed, you can run a code in it, such as
Now we will learn some of the fundamentals.
To emphasize the code chunks, Python uses indentation. Python indents text using whitespace. A block of code comprises all statements spaced uniformly to the right. A block is indented farther to the right if further testing is required.
Let’s understand it better with an example.
Here’s the output.
The code blocks print('Logging in to Marsdevs...') and print('retype the URL.') are distinct. In our example if-statement, the two code sections are indented four spaces. The last print ('All set!') is not a part of the else block since it is not indented.
Developers frequently put helpful information in comments to help readers understand the source code. It explains the logic, or a portion of it, employed in the code. Python supports two different comment types:
Single-line comments - Python single-line comments begin with the hashtag sign and include no white spaces.
Here’s more about comments in Python -
Python does not have "statically typed" variables. Thus we do not need to declare them before using them or stating their type. A variable is created when it is assigned a value.
Let’s take an example.
Operators are the foundation of any programming language. Operators enable the programmer to execute various operations on operands. These operators are classified according to their functionality:
Here’s an example of a Python program using arithmetic operators.
Relational Operators - Value comparison is performed using relational operators. The return value depends on the condition and is either True or False.
Let’s look at an example.
Here’s an example.
Let’s look at an example.
Now that we have understood Python programming fundamentals let’s move on to the OOP concepts.
Python is an excellent programming language that supports functional and object-oriented paradigms. Whether they are software developers, engineers specializing in machine learning, or something else, Python programmers should be able to employ the basic notions of object-oriented programming.
Python's object-oriented programming system supports encapsulation, abstraction, inheritance, and polymorphism, the four fundamental components of a general OOP framework.
Like many other object-oriented languages, Python allows you to construct classes to create objects. Python's most popular data types, such as strings, lists & dictionaries, are built-in Python classes.
A class defines a certain object type through related methods and instance variables. A class can be compared to the model or blueprint of an item. The terms assigned to the variables that make up a class are called attributes.
An object is an instance of a class with a specified set of attributes. As a result, an unlimited number of objects can be created using the same class.
Let’s look at an example.
The output will look like this:
In the example, we established a class - Parrot with the characteristics name and age. The Parrot class is then used to generate instances. In this case, the references (values) parrot1 and parrot2 correspond to our new objects. We retrieved and changed the instance attributes ' values using the object's name and the (.) notation.
One of OOP's most important aspects is inheritance. It is called inheritance when a class can inherit traits or methods from another. A derived class (or child class) is a newly created or inherited class. The existing class is a base class/a parent class.
Take a look at this example.
The output will look like this -
In this case, dog1 (the Dog-derived class object) has access to Animal-derived class members due to the Dog inheriting traits from the Animal.
One of the essential components of object-oriented programming is encapsulation. The grouping of characteristics and methods into a single class is called encapsulation.
It restricts access to and modification of a class's properties and methods by exterior classes. Additionally, this aids in data hiding. We use the underscore prefix in Python to indicate private attributes such as single _ or double __. For instance,
And here is the output -
Here, we have defined a Computer class. We incorporated the __init__() function to save the highest selling rate of the Computer. Take note of the code here.
Here we modified the value of __maxprice apart from the class. However, because __maxprice is a private variable, this change is not shown in the output. To modify the value, we implicated a used concept, such as setMaxPrice(), known as price.
Polymorphism is another crucial one in object-oriented programming. It just implies there are several forms. The same entity (method, operator, or object) can carry out many activities under various circumstances.
Here’s an instance for better understanding.
In the above example, we defined a superclass called Polygon and two subclasses called Square and Circle. Take note of the use of the render() function.
The render() method's primary function is to render the form. On the other hand, the procedure of rendering a square differs from that of rendering a circle. As a result, the render() function operates differently among types. Alternatively, render() is polymorphic.
Python is one of the most diverse and powerful programming languages available, powering some of the most popular websites and apps and being utilized in advanced analytics. With so much innovation in Python programming, there are plenty of fascinating development trends to look out for in 2023.
Python is becoming increasingly popular in machine learning because it allows developers to design advanced algorithms fast and effectively.
It has become the language of choice for many developers aiming to construct complex machine learning models by introducing new technologies such as artificial intelligence (AI), natural language processing (NLP), and computer vision.
Python is becoming the programming language of choice for many developers, and this trend is expected to continue in 2023. Python is frequently praised for its ease of use and straightforward syntax, making it an excellent choice for beginners just starting in programming.
Karen Panetta - an IEEE Fellow and Dean of Graduate Engineering at Tufts University, remarks, "Python is the closest language to what we call an 'instant gratification language,' implying it can do so much with very little code, even if you are a newbie programmer. Python reads like English, making learning easier for many learners."
Python is also an excellent data science and machine learning language, with various libraries dedicated to these topics. It can also be used for web development and scripting, giving it a flexible option for individuals who want to learn one language.
The Internet of Things (IoT) is a fast-paced tech that allows items to connect over the Internet. Python allows developers to build complex programs that interface with IoT devices.
It has grown in popularity recently & is likely to continue beyond 2023. This programming style relies heavily on functions to design and construct programs. By splitting the code into smaller, self-contained units, developers can create strong programs with fewer problems and mistakes. As a result, functional programming may assist developers in creating more efficient and dependable apps.
It is becoming an increasingly popular platform for various types of developers, including Python. Cloud computing has become an essential component of many online applications, and cloud-based solutions such as Amazon online Services, Microsoft Azure, and Google Cloud Platform have made installing and operating Python-based apps easier.
Python is a sophisticated programming language that shows no signs of slowing down in its growth. It provides developers with a wide range of features, from machine learning to natural language processing, and its uses will only evolve.
So, we have covered a few basic Python functions. But there is still much more to learn to become a Pro in Python language. However, if you want to learn Python, you must set a reasonable goal.
Whether you are a novice or already have some expertise with programming languages, you must take up a detailed learning resource. It can be videos, text-based learning, online courses, books, short projects, podcasts, blogs, or a hybrid strategy!
But always remember to choose a chapter that resonates with your skill level. Once you have done that, use your skills in hands-on projects to gather experience and keep yourself updated.
And if you are looking for more technical assistance. MarsDevs is your reliable partner for your tech needs & can offer resources that can help you understand Python development much better.
Need any help with your ongoing Python projects? Book a slot with MarsDevs today & let us handle all your end-to-end development needs.
Python supports OOPS, functional & structural programming methods. It can be used in scripting languages or converted to byte code to create large-scale apps.
The four pillars of Python are Objects & Classes, Encapsulation, Inheritance & Polymorphism.
Python supports four data types,
It is usually referred to as one of the simplest programming languages for beginners. If you want to take up a programming language, then Python is a great place to kick-start things.
Python developers are among the highest-paid professionals globally, with the added benefits & its popularity.