The majority of programmers select a backend technology for their web app development projects based on their training and expertise in that technology. While it is frequently easy, it is not always the best way to get the intended results for organizations. The programming language, environment, and full tech stack must be selected based on the nature of the project.
However, adopting backend technology in connection with the project’s use case is critical. It influences project performance, resource consumption, ease of deployment, scalability, and, in certain cases, even project success.
Despite the fact that Node.js and Python were created on distinct timelines and for different purposes, both are extensively used server-side technologies. Python has been in existence since 1991. It was intended to be a server-side programing language that could be used to create mobile and online apps. Node.js, on the other hand, was released in 2009 as a JaveScript runtime environment that revolutionized the server-side usage of javascript.
As a CTO or app owner, you may be unsure which one to choose for your project. So, in order to make the best decision, it’s critical to research their benefits and drawbacks, as well as follow use scenarios when one would outperform the other and vice versa.
Overview of Node.js vs. Python
The primary distinction between Node.js and Python is that the former is a runtime environment that is heavily reliant on JavaScript. It is designed for efficient computing-resource use and is used for programs that often communicate with web servers.
What exactly is Node.js?
Because Node.js is event-driven, it is scalable and provides tremendous efficiency to the project. Because it is asynchronous, it may process several requests at the same time without interfering with I/O activities. The majority of development teams favor Node.js for using Javascript on both the client and server-side.
What exactly is Python
Python, on the other hand, is a full-fledged, high-level, object-oriented programming language. It has a plethora of libraries, APIs, and supplementary tools because it has been around for over 30 years. Python is well-suited to a variety of programming paradigms and is widely utilized in corporate applications.
It has a large community, libraries, and supporting platforms. As a result, it is a great programming language for most enterprises that need to create applications for various and frequently unrelated use cases.
The popularity of a backend technology influences whether it will be utilized for your project.
First and foremost, from the standpoint of the organization, the development team must determine whether language has a substantial amount of talent accessible in the market. Then, from the perspective of programmers, a choice must be made on whether they are willing to learn languages that are widely used by numerous businesses.
Looking at the popularity of websites, SimilarWeb stated that Node.js was the most popular tool in the first 10,000, 100,000, 1,000,000, and 'entire' categories of websites. According to the Stack Overflow 2019 study, Python was the most "liked" programming language, while Node.js was the most popular tool among professional programmers.
According to the poll, Node.js has been dominating in Computers Electronics & Technology, Lifestyle, Arts & Entertainment, and 16 other areas in terms of industrial usage. Python, on the other hand, is a popular option in fields like Science & Education, Engineering, and others.
Node.js versus Python: A Comprehensive Comparison #1 Node.js versus Python
Scalability
The linear increase in resource needs as you scale your web application is referred to as scalability. When you construct an MVP, you will initially have a light web application that can be used in almost any language/coding environment. However, when you add features and functions to the program, the language/coding environment's resource usage will increase proportionally.
Node.js
Node.js provides enough flexibility to avoid using a core. Instead of developing a core and then growing everything around it, you may develop a series of microservices and modules. When your application is scaled, these microservices and modules can conduct their own operations on the fly. As a result, you may extend the program horizontally by adding nodes to the existing ones and vertically by adding resources.
Threads are a problem in Python. It is based on the Global Interpreter Lock, which prevents it from running several threads at the same time. This implies you can't run another process until the sequentially historical process is finished. Although Python is dynamically typed, this is more of a disadvantage when it comes to scalability. When the project grows in size, larger teams may find it harder to maintain code.
#2 Node.js Learning Curve & Syntax versus Python
The term syntax refers to a language's or programming environment's ability to perform a set of functions with as few lines of code as feasible. This is accomplished by condensing common processes into built-in functions. It's easy to see how this connects to the language's learning curve — the easier the syntax, the flatter the learning curve.
Node.js
If you're already familiar with Javascript, the learning curve for Node.js isn't too severe. Because of Node.js' event-driven programming philosophy, some individuals consider that its installation and documentation are a little difficult. This notion is crucial to Node.js's scalability and efficiency.
However, if you are a rookie developer, you may require some time to fully comprehend event-driven programming. But once that's taken care of, understanding Node.js becomes almost trivial.
Python
Python's unique selling point has always been its universality and simple syntax. Python has a shorter code length than Node.js or other programming languages and runtime environments, which is an industry-wide truth. Writing code in Python is a piece of cake.
ManekTech’s Preference
One significant difficulty with both languages is their sensitivity to indentation and whitespace. As a rookie developer, you may make these two errors regularly, and resolving such issues might be tough.
Both languages are simple to learn. However, depending on your prior knowledge, one may be simpler than the other. If you're already familiar with Javascript, Node.js is a no-brainer. If you're new to programming, Python will discipline you with indentation and whitespaces while also allowing you to create applications with a simpler syntax. So, let your requirements guide your decision!
Node 3 architecture. Python vs. js
Architecture defines the common practice/principles that must be followed in order to comply to the framework/environment/language. Node.js features a single-threaded design, which allows it to handle numerous requests with a single thread. Python, on the other hand, adheres to a standard implementation known as "cpython," which employs interchangeable code modules.
Node.js
Node.js, as previously stated, is a runtime environment that supports server-side asynchronous programming. This implies that the input-output capabilities are not obstructed since another process is still running.
You can run parallel processes, allowing you to deploy the application more quickly. Because of its event-driven design, Node.js may do actions as and when an event happens.
Python
Python, in contrast to Node.js, lacks such features and does not allow multithreading. Before others may be called in, you must execute and complete one procedure. Python becomes a little more strict as a result of this.
Although there are several tools that can assist you in creating asynchronous Python programs, they do not make Python inherently asynchronous. You'd wind up relying on workarounds in the project and not achieving the intended asynchronicity. For Python project connect with
python development service
ManekTech’s Recommends: Node wins this round due to its more responsive and accommodating architecture.
#4 Node Performance and Speed Python vs. js
When growing an application, every bit of efficiency helps to lower running expenses. As a result, while evaluating a programming language or environment, performance and speed are essential considerations.
Node.js
We've already looked into Node.js's non-blocking design. Its execution procedure is simplified and speedier as a result of this advantage. On top of that, Node.js has one additional advantage that makes it a strong contender: it executes code outside of the web browser.
As a result, the software running in the web browser processes at a quicker rate and scores higher on efficiency measures. This also enables the program to access capabilities such as TCP sockets that would otherwise be unavailable in the system.
Python
Python's fundamental design forbids multithreading, which is also a challenge in this regard. It reduces processing speed since processes are not performed concurrently. While Python's syntax is simple to learn and use, it is too slow for applications that often retrieve data from the webserver.
ManekTech’s Recommendation: The syntax of Python is simple to learn, but it is not designed for speed and performance. Node.js is also the obvious victor in this category.
#5 Libraries & Dev Tools in Node.js vs Python
Libraries are responsible for the rapid growth of app development technologies over the previous few decades. The idea is simple: if something has previously been created as a code, you shouldn't have to reinvent it. Instead, you should be able to include this code straight from a library into your application while just creating code for the functionality you want to add. However, the size or width of these libraries is insufficient. You should also check the documentation provided to effectively utilize a language's library.
Node.js
Node.js contains extensive and well-documented libraries that are handled using the Node Package Manager. NPM is the world's largest package repository, with 350,000 packages.
Python
Pip - an abbreviation for 'Pip Installs Packages' – manages Python's libraries. Python libraries are well-documented and simple to deploy, according to industry standards. Although this is often true, it is not true for new libraries. Modern technologies are frequently less well-documented than older ones, making newer libraries less dependable.
With both technologies, you will have a plethora of possibilities for libraries and ancillary-development tools. Both are equally effective!
#6 Node.js Community versus Python
A community is a collection of people who use and develop technology. Because they are active, they will continue to update popular libraries, undertake debugging exercises, and even introduce new features. In general, the most effective communities are maintained by a single, dedicated organization for the language/programming environment.
The Node.js Community
You may consider Node.js to be a relatively recent kind of technology, with a tiny community. You'd be shocked to find, though, that the Node.js community is fairly vast and globally active, with
skilled Node.js Developers.
Python's Community
Python, being the elder of the two languages, naturally has a bigger community. Python has a wealth of talent, from novice to senior-level contributors. One of the most significant benefits of having a large community is the ease with which developers may be found. And active collaboration from these developers leads to quick fixes and overall language enhancement.
ManekTech suggests:
Both languages are expanding, and worldwide contributions to their tech stacks have been made. They are open-source and completely free to use. As a result, picking one over the other solely on the basis of talent availability and community support should not be a consideration in your selection.
#7 Node.js versus Python Extensibility
The extent to which a language may be extended via third-party tools is referred to as its extensibility. More extensibility across third-party tools simply means that the language may be tweaked to include new capabilities. As a result, it is critical to examine this element while deciding between Node.js and Python.
Node.js
If you're still using earlier versions of Node.js, you may couple it with Babel for faster front-end development. Webpack and PM2 can help you with module bundling, and Express is a popular framework for Node.js.
Python
Sublime Text is frequently used to modify code in Python. The Robot Framework is useful for automated testing. Then there are popular Nodejs frameworks such as Django and Web2Py, which bring a slew of new functionalities.
So, on a relative scale, both Node.js and Python offer considerable extensibility, with a plethora of frameworks and tools available to assist you to enhance their functionality.
#8 Node Universality. Python vs. js
A web application may now be accessible from as many devices as there are fingers on a hand. With so many different paths to go, it's only reasonable that the development of language/environment be just as complicated.
Node.js excels in this area since it can be used for both backend and frontend development owing to Javascript. Node.js is an all-arounder when it comes to websites, web apps, desktop applications, mobile applications, and cloud and IoT solutions.
Python's simplified syntax makes it suitable for all types of projects with the exception of mobile apps. Python is increasingly being utilized by a huge number of programmers for IoT solutions and cloud apps.
ManekTech Recommends: Because these technologies are platform agnostic, they may be used in projects with Mac, Linux, or Windows users.
#9 Node.js Error Handling Capabilities versus Python
Nothing beats the satisfaction of error-free coding. As a result, the language with the finest error-handling systems is always the language of choice for CTOs.
Node.js
The parallel-process execution functionality of Node.js may make discovering faults and problems in programming time-consuming.
Python
Python's simplified syntax and absence of concurrent processes come in useful when searching for flaws and problems.
ManekTech Recommends: If error handling is an important factor in your selection, you may have already inferred correctly that Python has a major advantage over Node.js.
#10 Node Data Processing
This may appear to be a minor point, but it deserves to be addressed. Better data-processing capacity makes a language/environment more efficient and adaptive by default.
Node.js
If your app's use case is data-intensive, Node.js should be your first pick. The technology provided by the runtime environment makes it perfect for programs where data is regularly transferred and managed. Node.js is the more efficient candidate here due to its parallel operating and smooth I/O operations.
Python
Python is rather sluggish in data processing due to its simple syntax and just one thread running at a time.
ManekTech Recommends: Node.js is superior in this area due to its resource efficiency.
When should you use Node.js?
Because Node.js is based on Chrome's JavaScript engine, it aids in the development of scalable network applications. It has an event-driven, non-blocking I/O mechanism, making it an excellent choice for designing data-intensive real-time applications.
When comparing Node.js with Python, Node.js outperforms Python in terms of performance and quickness. It is an excellent choice for creating messaging or talking applications. It is also beneficial for designing high-load apps and e-commerce sites that rely on processing speed.
When should you use Python?
Python offers an open-source data analysis tool, web framework, and testing instrument library. As a result, its ecosystem is one of the largest of any programming community.
Python is a very approachable language for beginning programmers, thanks to the community's abundance of basic materials. The language is also taught at colleges and is used to deal with user-friendly devices like the Raspberry Pi.
Python outperforms Node.js in terms of consistency, stability, and ease of use. It is widely used in the development of scientific applications, large data solutions, and government initiatives.
Conclusion
Choosing between Node.js and Python might be difficult, especially if you want to create a full-fledged product rather than a side project. Both sides' features and benefits might be overpowering, clouding your judgment.
As a result, concentrating on the ultimate use of your product is the best method to cope with this quandary. List all of your product's features and how you intend to engineer them. And the language or runtime environment that shows to be more useful should be chosen.
