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Python is often a go-to language for developers who want to create mobile or standalone applications and web services, build enterprise-level software, perform complex data analytics or enable machine learning processes.
There are some key benefits of Python that help it maintain its popularity, such as its easy learning curve and expansive function library. However, it still has limitations when it comes to system-level programming because of its high-level nature. Examine some of the most significant benefits of Python that keep it so popular, as well as the limitations developers might face with certain application scenarios.
Quick history of Python
Python is a general-purpose programming language introduced in 1991 by Dutch programmer Guido van Rossum. Python runs on every major OS and in every domain, including systems operations and web development.
Van Rossum based Python on basic English keywords that provide clear syntax to express common program flows. As a result, programmers can easily scan code and identify errors. This also helps them quickly patch and update apps as needed.
The benefit of an object-oriented language
Since Python is an object-oriented programming (OOP) language, it treats all program elements as objects, including modules and libraries. By organizing items into reusable objects within a clear modular structure, programmers can define abstract data types and reuse objects across applications as needed.
And since it's also an interpreted language, Python eases the learning curve and increases deployment success since it clearly displays errors that must be resolved before execution.
Functions and constructs
Python provides dozens of built-in functions that load automatically and are always available. Developers can also create custom functions to carry out specific tasks and reuse that same code many times either within a single application or across several applications. This capability enables them to make changes to a function and replicate those changes throughout the code base.
Another strong feature of Python is its so-called constructs feature. This feature helps to control the order and flow of application instructions. Python will repetitively replicate and execute blocks of code across numerous services and applications, reducing the amount of time developers need to spend hard-coding application instructions.
Don't forget about whitespace
The use of whitespace is a key characteristic of Python and if it's not employed correctly, programming code simply won't function. In contrast to verbose languages like Java, whitespace reduces typing and helps to ensure more precise formatting and overall code clarity.
The Python library
Python also provides developers access to thousands of function libraries accessible through the Python Package Index. This package management system offers a standard format for developers to distribute programs and libraries, which simplifies installation and the use of third-party packages, modules and extensions.
Where Python falls short
In addition to slower builds, Python isn't useful for system-level programming where application instructions relay directly to operating systems, device drivers, network servers and embedded software. It's also not effective for creating cross-platform apps that must run smoothly across Windows, MacOS and Linux systems.
Developers refer to Python as a "glue code" which means it's useful for server-side scripting operations, such as customizing end user interfaces in web development. However, unlike compiled languages, a Python interpreter must convert the program line-by-line into machine code for execution, which will likely slow down runtime operations. This severely impacts the benefits of Python for large-scale system programming.
Finally, developers should watch out for versioning issues. The latest version, Python 3, fixed some of the language's fundamental design flaws and language redundancies. But even though many of the popular Python libraries from older versions have migrated to Python 3, this new version is not backwards compatible. As such, developers may want to focus on libraries strictly designed for Python 3 to avoid compatibility issues down the road. This stipulation is especially important considering that the Python Software Foundation will drop support for version 2.7 as soon as the first day of 2020.