Comparing Python and Node.js: Which is best for your Project?

By Tech-Act    
02/03/2021  1376 Views

COMPARING PYTHON AND NODE JS WHICH IS BEST FOR YOUR PROJECT

Each and every project is unique and its requirements are different. Therefore, making a right move in selecting a technology for your project is must when you are creating an application as the success of your project widely depends upon the selected technology. Today, in this article we will compare Python and Node.js that would definitely help you in choosing a right technology for your project.

  • Tech stack plays a vital role.
  • Python: Advantages & Disadvantages
  • When to use Python
  • js: Advantages & Disadvantages
  • When to use Node.js
  • Summary

Tech stack plays a vital role


Which technology is best for your project? To seek an answer for this question there are many ways like taking advice from your colleagues, trying to goggle the answer and consulting the developers. However, every source has some or the other opinion but finding a reliable answer is not that easy.

Well, let me help you in understanding how to choose a technology for your project.

  • Firstly, the basic criteria should be to check whether the programming language and frameworks are meeting your project goals.
  • Don’t simply choose a technology because it is popular. For instance, python and R are good fit for Big Data application whereas Java and C++ are best fit for building large desktop application.
  • Technology should be selected after calculating few things. For instance, your project needs and capabilities i.e. type of project, product type, application geography & budget.

Hence, before choosing a technology it is important to take into account each and every feature of the product that is to be build in future.

Python: Advantages and Disadvantages:


Old is Gold!!! It is very much true in case of Python though this language was originated in 90’s still it is one of the most in-demand & multifaceted technologies and this is because of its regularly developing libraries, outstanding documentation and forefront implementations. For instance, python is the devoted language for data science, ML and AI projects.

Python Advantages:


Python has many benefits that facilitate development in various projects right from startups to big enterprise platforms. Check below:

  • It reduces time to market:
    Python makes development of an MVP or a prototype in a limited time frame possible that reduces time to market. Python’s rapid development methodology enables you to maintain several iterations at a time and the DRY (don’t repeat yourself) principle through which you can reuse parts of the code.
  • It has a simpler syntax:
    Python’s simpler syntax makes it the most preferred programming language as concepts can be expressed with fewer lines of code which solves the errors & debug the code easily. The core of python is code readability. Also python is so simple that it is easily comprehensible for the clients enabling convenient collaboration.
  • Wide range of development tools and frameworks:
    Python coding gets a support from sublime text, popular code editor & from editing features and syntax extensions. If the web frameworks are potent enough then it makes the process simpler and enables the developers to place emphasis on the logic of their applications.

Python Disadvantages:


  • Python is single-flow:
    It has a slower speed of execution when compared to compiled languages. Python is not the best choice for the applications which are complex in nature & even in those projects where speed of performance is the primary requirement
  • Fragile in mobile computing:
    Development of server and desktop platforms can be done using python however it is considered weak at mobile computing. Hence, few smartphone applications are written in Python.

When to Use Python:


Python is the most preferred programming language for all kinds of projects whether small or large, simple or complex. For instances, business applications, desktop user interfaces, educational platforms, gaming, and scientific apps. Python is mostly used for:

  • Data science: This involves data analysis (Apache Spark), machine learning (Tensor flow), and data visualization (Matplotlib). Even some Facebook systems use Python’s Pandas library i.e. data analysis tools for face and voice recognition systems, neural networks and deep learning systems.
  • Web development
  • Desktop GUI
  • Scientific Applications
  • Gaming
  • Business applications
  • DevOps, system administration, and automation scripts
  • Parsers, scrapers, and crawlers
  • Software testing

Node.js:


JavaScript can be used for both back-end and front-end development as well as to solve compatibility issues and this is possible because of Node.js. Node.js is also defined as a server-side scripting language.

Node.js Advantages:


  • It enables fast performance:
     Node.js speed is faster when compared to Python. Since Node.js is rooted on Google V8 engine therefore developing chatbots and similar real-time applications using Node.js is easier.
  • It enables full-stack development:
    All you need to do is hire a team of developers who are expert in Javasript and they will do the entire application i.e. front end and back end. This is cost-effective.
  • Best for developing real-time applications:
     Because of Node.js event driven architecture it is good choice for developing real-time application.

Node.js Disadvantages:


  • Needs a clear architecture:
    Number of events can be run at a same time because of its event driven environment however this is possible only if the relationships between them are clearly written.
  • CPU-intensive tasks can’t be maintained by Node.js:
    Processing of all other tasks will be blocked by a heavy computational request and it slows down an application written with Node. Hence, projects based on data science should not go for Node.js.

When to Use Node.js:


For developing applications like Ad services, gaming platforms or forums, Node.js is the devoted technology. It very well handles the projects which has a lot of simultaneous connections or applications that has high-speed and intense I/O (input/output). Node is used in various types of web applications like social and productivity platforms, business applications, payment systems & entertainment platforms.

Summary:


Python & Node.js has its own pros and cons and they are used for different kinds of projects. So when you want to choose between Node.js or Python you need to carefully study their pros and cons to conclude which one is the best suited for your project application.

Each and every project is unique and its requirements are different. Therefore, making a right move in selecting a technology for your project is must when you are creating an application as the success of your project widely depends upon the selected technology. Today, in this article we will compare Python and Node.js that would definitely help you in choosing a right technology for your project.

  • Tech stack plays a vital role.
  • Python: Advantages & Disadvantages
  • When to use Python
  • js: Advantages & Disadvantages
  • When to use Node.js
  • Summary

Tech stack plays a vital role


Which technology is best for your project? To seek an answer for this question there are many ways like taking advice from your colleagues, trying to goggle the answer and consulting the developers. However, every source has some or the other opinion but finding a reliable answer is not that easy.

Well, let me help you in understanding how to choose a technology for your project.

  • Firstly, the basic criteria should be to check whether the programming language and frameworks are meeting your project goals.
  • Don’t simply choose a technology because it is popular. For instance, python and R are good fit for Big Data application whereas Java and C++ are best fit for building large desktop application.
  • Technology should be selected after calculating few things. For instance, your project needs and capabilities i.e. type of project, product type, application geography & budget.

Hence, before choosing a technology it is important to take into account each and every feature of the product that is to be build in future.

Python: Advantages and Disadvantages:


Old is Gold!!! It is very much true in case of Python though this language was originated in 90’s still it is one of the most in-demand & multifaceted technologies and this is because of its regularly developing libraries, outstanding documentation and forefront implementations. For instance, python is the devoted language for data science, ML and AI projects.

Python Advantages:


Python has many benefits that facilitate development in various projects right from startups to big enterprise platforms. Check below:

  • It reduces time to market:
    Python makes development of an MVP or a prototype in a limited time frame possible that reduces time to market. Python’s rapid development methodology enables you to maintain several iterations at a time and the DRY (don’t repeat yourself) principle through which you can reuse parts of the code.
  • It has a simpler syntax:
    Python’s simpler syntax makes it the most preferred programming language as concepts can be expressed with fewer lines of code which solves the errors & debug the code easily. The core of python is code readability. Also python is so simple that it is easily comprehensible for the clients enabling convenient collaboration.
  • Wide range of development tools and frameworks:
    Python coding gets a support from sublime text, popular code editor & from editing features and syntax extensions. If the web frameworks are potent enough then it makes the process simpler and enables the developers to place emphasis on the logic of their applications.

Python Disadvantages:


  • Python is single-flow:
    It has a slower speed of execution when compared to compiled languages. Python is not the best choice for the applications which are complex in nature & even in those projects where speed of performance is the primary requirement
  • Fragile in mobile computing:
    Development of server and desktop platforms can be done using python however it is considered weak at mobile computing. Hence, few smartphone applications are written in Python.

When to Use Python:


Python is the most preferred programming language for all kinds of projects whether small or large, simple or complex. For instances, business applications, desktop user interfaces, educational platforms, gaming, and scientific apps. Python is mostly used for:

  • Data science: This involves data analysis (Apache Spark), machine learning (Tensor flow), and data visualization (Matplotlib). Even some Facebook systems use Python’s Pandas library i.e. data analysis tools for face and voice recognition systems, neural networks and deep learning systems.
  • Web development
  • Desktop GUI
  • Scientific Applications
  • Gaming
  • Business applications
  • DevOps, system administration, and automation scripts
  • Parsers, scrapers, and crawlers
  • Software testing

Node.js:


JavaScript can be used for both back-end and front-end development as well as to solve compatibility issues and this is possible because of Node.js. Node.js is also defined as a server-side scripting language.

Node.js Advantages:


  • It enables fast performance:
     Node.js speed is faster when compared to Python. Since Node.js is rooted on Google V8 engine therefore developing chatbots and similar real-time applications using Node.js is easier.
  • It enables full-stack development:
    All you need to do is hire a team of developers who are expert in Javasript and they will do the entire application i.e. front end and back end. This is cost-effective.
  • Best for developing real-time applications:
     Because of Node.js event driven architecture it is good choice for developing real-time application.

Node.js Disadvantages:


  • Needs a clear architecture:
    Number of events can be run at a same time because of its event driven environment however this is possible only if the relationships between them are clearly written.
  • CPU-intensive tasks can’t be maintained by Node.js:
    Processing of all other tasks will be blocked by a heavy computational request and it slows down an application written with Node. Hence, projects based on data science should not go for Node.js.

When to Use Node.js:


For developing applications like Ad services, gaming platforms or forums, Node.js is the devoted technology. It very well handles the projects which has a lot of simultaneous connections or applications that has high-speed and intense I/O (input/output). Node is used in various types of web applications like social and productivity platforms, business applications, payment systems & entertainment platforms.

Summary:


Python & Node.js has its own pros and cons and they are used for different kinds of projects. So when you want to choose between Node.js or Python you need to carefully study their pros and cons to conclude which one is the best suited for your project application.