As per common understanding of development technologies, there are no ‘good’ or ‘bad’ programming languages. Everything comes down to the preferences of an individual developer. One size doesn’t fit all in programming languages, and what works for one developer might not exactly work for another.
Python and Node.js are ranked among the most extensively used languages for back-end programming and development. But is it wise to make your choice on popularity alone? The language you choose for back-end research and development should befit your capabilities and requirements.
Factors influencing your choice of programming language include:
- Product Type: Do you operate a data analytics platform or a basic messenger?
- Type of Project: Are you planning to build a business application, payment software for financial transactions, or a game?
- Budget: How much are you willing to spend on your technology of choice? Factor in for long term support as well.
- Application Geography: Is your end product bound to be local, national or global?
The list doesn’t stop here. It can go on to include other factors as well, including your own skill-set and your team’s preferences. However, understanding these preferences and selecting the appropriate programming language is a task in its own.
By the end of this article you’ll not only be able to understand your own needs better, but will also be able to decide which programming language emerges as a victor for you in the Python vs. Node.js battle.
Python is a high-level open-sourced programming language that first saw the light of day in 1991. The language has grown leaps and bounds during the three decades after that, with the latest version – Python 3.8 – offering a number of features to users. Python 3.7 was their most popular version and is still preferred by developers.
Python development can easily be used through Google’s App Engine. You can use a variety of tools and libraries to develop web apps on the App Engine with Python.
Node.js is based on Google’s V8 engine. The V8 engine works as a virtual machine with built-in optimizers, compilers and interpreters. Google’s V8 replicates the high efficiency and speed of the physical engine it is named after to offer consistent and advanced performance.
Python Pros, Cons and Use Cases
Like any other development technology, Python comes with its own set of pros, cons and spheres where it can best be implemented. Python has been around for quite some time, and has proven itself to be a robust programming technology.
Has a Simple Syntax
Python comes with a simple syntax that makes it easier for developers to express concepts, solve issues and debug codes. Python is easy for clients to understand as well, and can significantly enhance code readability.
Reduces Time to Market
Python helps you develop a virtual prototype without any further delays. This eventually reduces time to market (TTM) and allows you to maintain multiple iterations at one time.
Has a Wide Range of Frameworks and Development Tools
Powerful web frameworks, including Django, optimize the time required for project completion and simplify the development process. Developers can increase focus on the logic of applications, while Sublime Text offers support for coding and editing.
A Growing Community
In comparison to Node.js, Python has a bigger user community. From juniors to experienced pros, you can find a number of contributors. Businesses can easily find developers with expertise in the language and can also get support from community members during complex issues.
Limitations in Mobile Computing
While Python works best for desktop platforms and server development, it has certain limitations in mobile computing. Not many smart phone applications are developed through Python.
Python can be slow upon execution in comparison to other compiled languages including Swift and C. Applications that involve a number of complex calculations are hard to develop through Python.
Python Use Cases
Python is mostly used in:
- Web Development: Web development frameworks including Flask, Django and Bottle assist completion.
- Data Science: Python offers a holistic solution for data science and its branches – machine learning, data visualization and data analysis.
- Scientific Applications: 3D modeling is possible through Python.
- Desktop GUI: 3D animation software like Maya and Cinema 4D can help here.
- Gaming: 3D game engines available.
- Business Applications: Reddit and Netflix were both written in Python.
- Software Testing: Web testing tools like Selenium and unit-testing tools like Pytest make this process easier.
Python is an easy to work on yet extremely powerful and versatile programming language. It is suitable for business solutions, scientific applications and educational platforms. It can also be used as the go-to language for Data Science and Big Data applications.
Node.js Pros, Cons and Use Cases
In a battle of pure, brutal speed, Node.js will outrun Python. Node.js is based on Google’s V8 engine and can handle the extensive requirements of real-time applications including those of chatbots.
Perfect for Real-Time Apps
Node.js comes with an event-driven architecture that allows the development of dynamic real-time web games and chat applications.
Assists Full-stack Development
Unlike Python’s up-to-date and comprehensive documentation process, Node.js can be found slacking here. Plus, the environment doesn’t offer core tools and libraries to choose from.
Cannot Maintain CPU-Intensive Tasks
Node.js isn’t suitable for projects based on data science or big data for that matter. It requires heavy computational power and can block or slow down the processing of other tasks.
Node.js Use Cases
Node.js is the go-to platform for developing real-time applications including gaming platforms, chatbots, ad services and other forums. It is also good at handling applications with intense I/O (Input/output) requirements. Additionally, it can manage content management systems, ecommerce platforms and P2P marketplaces.
Use Cases include:
- Social Platforms: Trello and LinkedIn
- Payment Systems: PayPal is a popular example
- Business Applications: Walmart and eBay
As we have discussed above, both, Python and Node.js have their unique sets of advantages and disadvantages. Both of them are also used for different kinds of projects, so there is no absolute winner. While Node.js trumps Python in terms of speed, the latter performs a lot better at offering functional enterprise-grade solutions to complex problems.
With the information and ideas presented in this article, you can understand your requirements better, and choose the best option out of these two.