What Is Python? A Guide to Python Programming Basics

What is Python? Only one of the most popular programming languages today. Known for its simple syntax and versatility, Python is both easy to learn and used for high-level applications. Python programs are used throughout the artificial intelligence and machine learning industry as well as for web development.

Today, we’re going to take a deeper look into what Python is, what it’s frequently used for, and how you can start learning Python today.

What is Python? The basics of the Python programming language

Python is a general-purpose object-oriented programming language. Many college computer science majors will learn Python as their first programming language if their first language isn’t Java or C.

Let’s take a look at Python syntax for “Hello World”:

print(“Hello, world!”)

That’s incredibly simple, isn’t it? The same code in JavaScript would be:

console.log(“Hello, world!”);

In C++, the code would look like this:

#include <iostream> int main() { std::cout << “Hello, world!”; return 0; }

Python programs will look similar to anyone who has written in other object-oriented languages. But they will look closer to current programming languages like JavaScript rather than the more complex, compiled languages of C and Java.

Although perceived as simple, Python can achieve anything. It can be modeled in many operating systems using the Python OS module and is therefore highly portable.

Compiled vs interpreted languages

One thing you need to know about Python is that it’s an interpreted rather than compiled language. What does that mean? When you write your code, you then send that code, completely, to the user. The user’s software then interprets that code. If an error occurs, it’s when the user runs the code, occurring as a runtime error.

Compiled code is different. You run your code through a compiler, most errors get caught (although there still may be runtime errors and exceptions), and then the code gets packaged for the user. The user runs the compiled code, not your code directly. 

Let’s say you try to manipulate a substring in Python that you shouldn’t be able to manipulate. The error will get caught when the code is interpreted. If you do the same thing in Java, it will get caught by the compiler before reaching the users.

The advantages of interpreted languages like JavaScript and Python are that they are more flexible, although they are also less efficient.

The history of the Python software foundation 

Python is not a new language! Because it’s so simple and easy to use, some might assume it came about recently. But Python was developed in 1989. While that’s not as old as a language like C, which was developed in 1972, Python still isn’t new by any means.

Python was initially implemented by programmer Guido van Russom. While its development started in 1989, its first stable release was in 1991. It’s remained such a popular language because of its low barrier to entry and excellent utility. From command line arguments to on-the-fly programming, Python is an easy language to learn and deploy.

The major benefits of using Python

What are some of the major benefits of using Python? Why are so many people taught Python in college—and why do they continue to use it in their careers? Here are some answers:

• Python is easy. Python is an easy language to learn and use. In fact, Python is often cited as being one of the easiest languages to learn and use. First, its syntax is very simple, flexible, and forgiving. As an interpreted rather than compiled language, it’s harder to get a fatal error. Python data structures are very easy to learn. And many libraries and code snippets are out there, so you can find examples of pretty much anything.
• Python is versatile. It can work for mobile development, web applications, and desktop applications. Python programmers can go into just about any specialization. For an easy-to-use language, this is quite unique. Anyone can pick up Python programming and start developing games or apps right away.
• Python is well-supported. Python has an extraordinarily active community. If a new programmer has a question about Python, they can ask and get answers almost immediately. This means that new programmers aren’t left confused or adrift.
• Python has a lot of utilities. It’s frequently used as the language of choice in development systems, such as game development kits, mobile development kits, and other forms of software development platforms. 
• Python is fast. Because Python is easy to use, Python programmers tend to be quite fast. They can implement simple solutions quickly. It’s free and open source, and tons of libraries and code snippets are available.

But Python has downsides as well:

• Python is interpreted. Python is an interpreted language rather than a compiled language, which means that it’s interpreted upon launch rather than pre-compiled. This makes Python inherently slower and less lightweight than other programming options.
• Python experiences runtime errors. This is an offshoot of being an interpreted language. Rather than experience compiler errors, it can experience errors while actually running. Not only does this damage user experience, but it can create security flaws.
• Python is dynamically typed. Dynamic typing makes Python faster to program, but it means that type-checking is all on the programmer. This can lead to more errors, especially in larger programs.

Python is never going to be the best language to use in terms of resource usage, and it’s difficult to scale. These challenges have given Python the reputation of being “for beginners.” While this reputation isn’t inherently unearned, there are many reasons to use Python. Let’s take a deeper look at the types of software frequently written in Python.

Types of software written in Python

What is Python used for? In recent years, Python has become a popular language for machine learning and data science. Python use cases include:

• Natural Language Processing (NLP). Python is often used for scripting in NLP, AI, and machine learning. 
• Web and internet development. Frameworks such as Django and Pyramid use Python, as do micro-frameworks like Flask.
• Science, mathematics, and engineering. Many scientific solutions and data science solutions use Python because it’s easy for non-programmers to learn, although R is frequently used, too.
• Software development and business applications. As a general-purpose language, Python can work for ERP solutions, eCommerce platforms, and more.

So, Python has a lot of uses—and Python programmers are very in-demand.

Careers in Python programming

Python is actually one of the “busiest” programming languages in terms of how many job listings are available. There are a multitude of careers in Python programming because the breadth of Python applications is so significant. Data science, machine learning, mobile application development—Python programmers have their pick of specializations.

The average Python programmer makes around $115,000 a year, according to ZipRecruiter. This is about on par with other programmers, but the need for Python programmers is also growing very quickly. Python is often cited as the most popular programming language and the fastest-growing language, in large part because of the growing need for data science, AI, and machine learning.

The most popular Python developer tools

One of the major advantages of using Python is the large number of tools available for Python programmers. Python programmers can avail themselves of an array of development tools, which make it easier and faster to develop applications. Here are some of the most popular Python developer tools:

• PyCharm. Widely considered the best IDE for Python developers, PyCharm can write and deploy Python code quickly.
• Visual Studio Code. Visual Studio also has extensive support for Python developers. Because so many developers use VS for coding, it can be a great option.
• Scikit-Learn. This is the toolkit of choice for many data science developers. Those who are learning Python for data science or machine learning will likely encounter Scikit.
• Keras. A neural network library written in Python, Keras is frequently used by those who are developing their own neural nets or digging deeper into NLP.
• Selenium. Selenium is an open-source automation framework, which can work in Python or Java, C#, PHP, and other languages. It improves the testing process for applications.
• BeautifulSoup. BeautifulSoup is a popular scraping utility used by Python developers who need to collect large volumes of information.

These tools are usually free and open-source, which is another tremendous advantage. You can find many Python utilities through Github, including source code you can use to learn more about the language. 

How to learn Python

If you’re already a seasoned programmer, learning Python is likely a breeze. Github has many open source projects in a multitude of languages, including Python, that you can use to learn. Create a project in Python to stretch your syntax muscles—and to get to know the internal Python functions and libraries.

Otherwise, if you want to learn Python, you can:

• Learn some basic Python string methods.
• Take an introductory bootcamp course.
• Try some easy Python projects or look at coding examples.
• Take a full bootcamp on Python programming.

Python is notoriously one of the easier languages to learn—so it’s a great language for a beginner. It’s even easier if you know what specialization you’re interested in, whether it’s web development or game development.