What is Python Used for? Real World Applications

Python is arguably the most dynamic and popular programming language in use today. Famed for being simple, easy to read, and highly versatile, Python has applications in most industries, powering web development to artificial intelligence. Its extensive set of libraries and frameworks makes Python the go-to choice for data science, automation, machine learning, cybersecurity, and many other applications

Read on to learn how Python powers today’s leading industries and it’s real world applications that have changed our lives and made it easier.

Why Python?

Python is a high-level and general-purpose programming language, which means it’s easy to learn and can be used to tackle a wide variety of issues! Python is a great language to learn and use for various applications due to its simple syntax, high readability, and portability between operating systems.

It’s therefore not surprising that Python is prevalent in not only today’s job market but also in common technology we use every day.

Python programming is a talent that applies to practically every business and job function other than software development. Python-based technology is driving innovation and innovative solutions across sectors such as banking, healthcare, insurance, and disciplines such as aerospace and entertainment.

In our What is Python 101 guide, we introduced Python and a few of the fields Python is used in, such as tech, finance, and biotech. But in this article, we’ll be taking a deeper look at even more of Python’s broad uses — specifically in the following areas:

• Web development
• Data science
• Machine learning
• Artificial intelligence

Applications of Python

Web Development

Even though HTML, CSS, and Javascript are the most popular choices for web development, Python is also an excellent option to consider. Static, plain text pages to dynamic e-commerce sites and interactive internet applications are part of web development.

Coding is crucial in web development to build out site functions, optimize user experience, and ensure that information is organized properly. Python’s web frameworks, such as Django and Flask, have become popular options for website development.

Python is an excellent option for backend web development and is used by many companies today. These open-source frameworks allow users to build web applications more efficiently due to Python’s ability to handle vast amounts of data and automate tasks. In fact, companies such as Instagram, Pinterest and Google incorporate Python in their backend web development.

Data Science

Python is also a dominant language of preference when it comes to data science and data analysis. In the era of big data, we often interact with data in our daily lives, with technology like navigation (GPS), online purchases, energy consumption, and wearables like smartwatches. The typical home has about eleven devices, and that number is only going to grow in the future! With so many devices, there is such a huge amount of data that companies have to process in order to deliver their services.

Python tools are frequently utilized to visualize, process, and analyze large datasets. Data science is all about processing data and inferring trends — and Python is extremely handy in this respect because of its intensive packages such as Scipy, NumPy, and pandas. Also, the Matplotlib package can be utilized to construct data visualizations. This renders Python a favorite in disciplines such as bioinformatics that also have a lot of data and modelling involved.

These Python-based tools have become popular due to their ease of use and scalability. For example, Netflix uses Scipy and Numpy for numerical computing to manage user traffic across the platform.

Also Read: Use of Big Data and Data Mining in the Healthcare Sector

Machine Learning

Through examining huge amounts of data, machine learning algorithms are able to identify patterns and use those patterns to interpret future behaviour. The most self-evident application of machine learning in products is recommendation systems. Netflix, Spotify, and Youtube companies gather user activity to predict and recommend playlists and videos.

Scikit-learn and TensorFlow are Python libraries that enable the use of algorithms for classification, clustering, and regression on large data sets. The high performance and extensive functionality of these libraries make them essential in any exploration of machine learning.

Artificial Intelligence

Machine learning is actually just one facet of artificial intelligence. AI refers to the brightness of machines and the development of computer systems to perform human-oriented tasks such as perception or decision-making.

One prominent example of artificial intelligence is in ridesharing apps like Uber and Lyft. Python is used in artificial intelligence for apps like Lyft or Uber. The AI system can then predict things like user demand and estimated arrival times. Uber utilizes AI for predicting user demand and estimated arrival times (among other features), and much of this is accomplished through Python.

In addition to some of the previously mentioned Python libraries, AI functionality such as prediction models and neural networks can be created through other libraries like Keras and PyTorch.

Python is Everywhere!

Among popular programming languages, Python is one of the most diverse in its applications. Moreover, it’s deeply integrated into our everyday life as well as today’s leading companies.

Professionals in a wide range of fields can use Python in their work. These include software engineers and web developers, as well as data scientists and product managers. Python is the ideal tool for data-driven decision making in today’s modern age, regardless of industry.

If you or your child are interested in the fields or roles listed above, then learning Python is a great choice!