In the fickle world of programming, few languages have stood the test of time, technology and changing quality parameters. Yet Python has endured and evolved as a programming language for over two decades now. It is now popular for general usage and in high-level structured software applications of every kind. That is why several systems based on other programming languages are looking to move to Python.
Before you consider the conversion/migration, check if:
i. Re-writing/conversion will serve any significant purpose? ii. Adequate programmers are skilled enough in Python? iii. It is economically viable to do so?
Here are a few reasons why you should consider Python for migration/conversion:
Neat, Clean, Easy
Python is clean and easy-to-read. It stresses on indentation and white space, the former factor lets the language be easily readable, scannable and allows identification of blocks of code. Coding is usually minimal, except in case of exceptions and outliers. Flexible and compressible, Python is well structured and aspect oriented, with its functional properties in place. This disciplined outlook helps programmers keep it tight and organized. The language syntax is such that even new programmers can easily pick up Python and start working on it within a reasonable time period. Thus, training beginners shouldn’t be an intimidating task. In fact, Python has even got non-programmers interested, such is its learning comfort factor.
Reusable & Multipurpose
Using a single language across the organization, leads to uniformity and increased efficiency. Presently, Python is the most suited language for this purpose, encouraging users to revisit and reuse it, impressive as its modules are. Take the Standard Python library, a crucial part of the Python package. Functionalities can be shared among various programs, just by separating them as modules and using them again as specific sections of a program.
Python is especially suited for a large or complex project with varying requirements. A great support library ensures that programmers’ productivity is enhanced during any project. Python was never aimed to serve a particular section of users, it is a multipurpose language, cutting across varied sections – web programming, education, software development, game programming, scientific computation, GUI and more.
Python has transformed to a common programming language that links up different units, while serving as a one-point medium for sharing data. No wonder then that the language is playing a vital part in data science.
Great for Testing & Prototyping
Thanks to the instant feedback that Python provides on execution, the programmer can skip several time-consuming steps. Testing is done simply, ensuring that you check and recheck before implementing code. This allows you to build a solid structure before you add code for the functions. The Python testing framework helps reduce time spent in debugging and quickens the workflow.
Another task made easy is prototyping, thanks to flexibility and assimilation of most technologies by the language. Suitability to web programming is a huge plus, since programming largely concerns the web world, at present.
Compatible & Extensible
Python is object-oriented and also extensible in C, C++. Everything about this language is object-oriented, making it useful and simple for programmers. The quality of modularity allows clear separation of program structures into packages, modules and classes, allowing for a greater design flexibility. Also, compatibility to high-level functions provides Python with a dynamic and interactive build up. Easy compatibility is another of Python’s perks, be it Windows, Linux or a Mac.
Web & Applications
Creating web services on Python is comparatively easy, the language has resources to gel with all known databases.It has great support to work with various data interchange formats like JSON, XML, etc. Be it document or text processing, Python provides consistent, sturdy results. Several scientific and numeric applications make use of various Python tools. Customizing or extension of an application is second nature for Python, it was designed as an ’embeddable’ language.
More Results for Less
Relevant fact: Python requires five time lesser lines of code, as compared to languages such as Java. By migrating or adopting Python, you drastically cut down on number of hired programmers for any project involving the language. Apart from benefits to new programmers, seasoned developers can save valuable time and energy. They have the luxury to built directly over Python, without any framework as a starting point. Of course there is django, as a third-party framework, to fall back on. But try working on Python without the framework initially, to appreciate its framework-like role.
About Namespaces and Modules
Several languages have the concept of namespaces and modules, these are present in the form of files in Python. But here the namespace is the name of the file itself, so comprehending namespaces is not a necessity. As far as modules are concerned, the same modules can be re-imported without any loss in its effectiveness. The library, unless stated otherwise, needs to be imported only once, later imports only refer to the original import, for the availability of namespaces.
In summation, Python is a dynamic, powerful language that is easy to learn. It encourages programmers to write prompt and precise code. There are several advanced features and tools that add dynamism to the language, numerous enough to enhance programming, as a task. Compatible with almost every application and operating system, Python’s sizeable and helpful developer community is one its greatest strengths.