A comprehensive overview of Python

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What is Python?

Python is a general-purpose computer programming language that can be used for virtually anything. From web development and automation to data analysis and software testing, the language is incredibly versatile.



Guido van Rossum developed Python in 1991 and got its name from Rossum’s love of an old BBC series called Monty Python’s Flying Circus. When he created the program, he had a few specific goals:

  • Create an easy, intuitive language that was as powerful as competitor languages.
  • Develop an open-source program where anyone could contribute to its development.
  • Write code that was as readable as English.
  • Create something that was suitable for everyday tasks.

Twenty years later, these goals have certainly been fulfilled as the code is one of the most readable and flexible languages on the market.


Java vs. Python

Java and Python are two of the most popular programming languages available; however, there are key differences between them. These include:

  • Language: Python is an interpreted language and automatically converts code from machine-readable to human-readable. Java is both a compiled and interpreted language program as its source code is a binary bytecode.
  • Typing: Python is dynamically typed while Java is statically typed.
  • Applications: Java is typically only used in web development settings such as embedded systems or desktop applications. Python can be used for both numeric and scientific computing. This includes machine learning, language development, image processing, and more.
  • Syntax: Java requires significantly more coding and requires all variables be inputted while Python is less rigid and doesn’t require the developer to type in all variables since they’re inputted during the runtime.
  • Speed: The ease of Python makes for fast development while Java, an older language, takes more time.

Why is Python important?

Python is one of the most widely used programming languages available, beating out other common codes like Java, C#, and R. The rapid growth of Python is primarily due to its flexibility, scalability, and ease of use. It enables you to build and develop a variety of applications, including web and mobile applications, scientific applications, game development, and so much more with ease.



Businesses looking to stay on top of evolving technology such as artificial intelligence or machine learning must take advantage of the versatility and ease of use featured within Python. Utilizing this code ensures businesses can adapt and evolve to today’s rapidly changing business environment.

How does Python work?

Python consists of roughly three stages when executing code:

  • Initialization: During this stage, CPython (Python written in C Program) prepares specific data structures within Python. This includes configuring built-in models, preparing the import system, and more.
  • Compilation: CPython does not actually produce code but rather interprets it. After interpretation, it generates bytecode — which is a series of instructions—and sends it off.
  • Interpretation: Python’s virtual machine then interprets and executes the bytecode.

Python use cases

Because Python is so user-friendly, both programmers and non-programmers are able to use it in a variety of settings, including:

Web development

The flexibility of Python makes it an ideal choice for both simple and complex web development projects. The program relies on whitespace and common expressions, which means you can write fewer lines of code.

Additionally, Python features a vast library of tools that streamlines development time. For example, Python provides easy access to Pygal, SLQALchemy, Numpy, Pandas, and more so you can easily complete mathematical analysis, charting, and queries rapidly. You’ll also have access to Django and Flask, some of the most popular and robust web frameworks available.

Artificial intelligence and machine learning

Python is at the forefront of AI and machine learning. There are several reasons for this including its efficient, precise syntax, low entry point, and easy integration. However, Python’s open-source libraries have made it the go-to for machine learning and AI.




The amount of time spent on manual, repetitive tasks is astronomical. Automating these tasks and processes with Python allows you to work more efficiently, reduces data errors, and eliminates duplicate data.

Because Python is beginner-friendly, virtually anyone can automate simple tasks like finding data or sending text messages or emails.

Data analysis and visualization

The cross-functional, interpretive nature of Python makes it ideal for data analysis and visualization. This is primarily due to Python’s:

  • Readability: Python has a clear, easily understandable syntax and readability, meaning developers can quickly master the language and spend less time inputting code.
  • Flexibility: The hyper-flexibility of the language allows developers to create algorithms and data models, web services, and data mining with little time and effort.
  • Scalability: Many organizations have migrated to Python because of its scalability. The language can be used in a variety of fields or to solve a number of different problems.
  • Graphics and visualization tools: Python features a number of data visualization tools including charts, web-ready interactive plots, and grabs, that allow you to visualize all types of data.
  • Analytics: Data-mining companies from around the world rely on Python to analyze data for patterns. Python also correlates this information into large sets to provide better insights alongside other KPIs.

Software testing

Python is often used to support or automate software testing or prototyping tasks such as build control or bug tracking or testing. By automating these tasks, developer’s time is freed up so they can focus on more important tasks.

For example, one of the most popular libraries is scikit-learn. It’s built on NumPy and SciPy and features a number of algorithms that are commonly used for classification, clustering, regression, and preprocessing.

TensorFlow is also another popular Python library and supports organizations such as Google and Uber to build and train models to find patterns and correlations. Python’s flexibility and power make it easy to deploy computations across platforms.

The future of Python

In today’s rapidly changing business landscape, it’s not uncommon for technology, services, languages, or apps to come and go. However, Python appears to be a future-proof language. Its versatility and flexibility are something that few other languages have come close to beating.



Python lies somewhere between a full programming language and a scripting language, making it ideal for a seemingly endless number of use cases. For example, Spotify relies on the code to suggest music to listeners. Pixar uses it for film production, and Google uses it for data scraping and analysis. The chances of these big-name companies finding a better coding language than Python is slim.

The future of Python is becoming more and more secure as multiple businesses move toward automation, machine learning, and data analysis. Few other programming languages have the traits needed to support these technologies like Python.



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