Enterprise software and apps are typically used to collect and maintain enterprise-level data, storing large amounts of information that’s processed across multiple levels. Considering the complexity of enterprise software, a lot of important factors need to be considered while building such software such as stability, scalability, reliability, security, user-centricity and ease of maintenance. Python is a scripting as well as an object-oriented programming language and promises more flexibility and higher scalability than other software development languages. It is both easy to code and implement and easily adapts at all stages of software development. A Stack Overflow survey revealed that in comparison to other languages, Python is preferred by almost 73.1% of users worldwide.
8 Reasons Why Python is a Popular Choice for Enterprise Software Development
1. Python is scalable
Due to its versatile nature, Python makes it easy to handle different tasks at different stages and scale of the projects. It supports multiple programming paradigms, including functional, procedural and centres paradigms. Its approach towards software development and the use of integrated programming language makes it easier to write code on a large scale. This cuts down the time required to script a large solution, which translates into lower development costs. Python also supports anytime adoption and expansion because even if you decide to increase the corresponding scale time your production cost will stay the same.
2. Python has the most libraries and tools
Python developers can access a variety of libraries and use modules that have already been researched and developed. This helps developers get the output they want faster and without additional hassles. Some of the libraries that support Python are:
Panda – manages data structures that enable high performance.
Numpy – helps a Python developer in scientific or numerical computing
Keras – helps developers work with machine learning
Tensorflow - helps in developing attractive features like image recognition or face detection
The Scikit-learn– assists helps various Python developers in data mining apart from machine learning and analysis of data.
Python developers have access to a vast range of free tools that are easy and handy. In fact, Python in itself is an ecosystem of tools that are essential for high coding quality.
3. Python has a Fast Prototyping Feature
To cater to the demand for shorter development cycles Python allows programmers to easily switch between prototypes to the solution. It ensures that coding is done in such a way so as to enable faster and proper development.
4. It’s easier to read code in Python
Python is so easy to read because it’s practically in English, and that’s why it’s used universally for writing and developing codes. Python code can be handled by any programmer, especially when it comes to debugging the code. Because it’s easy to read, Python programmers can easily identify any glitches and rewrite the code as required. This means shorter development time and a faster launch to market.
5. Python is easy to learn
Many surveys have ranked Python as one of the easiest programming languages to learn because of its easy readability and simple syntax. Programming details like declaring types of variables or arguments are handled by Python, unlike what happens in other languages.
6. It is ideal to handle the explosion of AI, ML and data
Python has proven to be very useful while programming for AI and ML projects. Its robust framework has also made it a popular choice for data scientists. It is also the best choice for DevOps and system scripting.
7.Huge developer community
Being such a popular and widely used language, Python naturally has a huge developer community. It addition to a vast library, Python also has a friendly, global community which means that if you’re ever facing an issue, you can simply reach out this user base and seek help. By just posting a question or searching for the answer on a Python developer community site, you can get a solution.
8.Better Package Management
Package management is a kind of a connector between various projects, allowing programmers to write, build, and share packages in formats that other developers can easily plug into other applications. Package management in Python is far better than in other languages, and it allows programmers to install, uninstall, upgrade, and use a broad range of sources for internal and external libraries.
Python’s coding standards and simplicity allow programmers to develop complex enterprise software with just a few lines of code as compared to multiple lines of code that would be required in any other programming language. Python’s library of tools helps in implementing large systems that can integrate and manage data from multiple sources, via a user-friendly UI that provides easy access to that data. Even if an organization should decide to migrate to another programming language, it is so much easier to do with Python because of its inherent flexibility and easy integration with other programming languages like .NET, JAVA, CORBA etc. Conversely, if any existing enterprise software has some modules developed in another programming language it could easily be converted and integrated with Python due to Python’s vast libraries.
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With this detailed look at Python’s features and performance, it is clear that Python is the ideal choice for the development of enterprise software since the implementation is simple and hassle-free, and because this robust and versatile programming language offers a plethora of options.
Published Date: Jul 24, 2019