Introduction to Python
Python is the prominent programming language used for a variety of application development process, including the web based applications, data analytical applications and machine learning implementation. Some of the alternate options for Python are NodeJS, Ruby, PHP, Golang, Java and Scala. Most of these python alternate frameworks or platforms offer all of the functions of Python, and a few have partial features of Python combined with their own improved qualities, which makes them either equal or finer than Python.
List of Python Alternatives
Below is the different Python Alternatives which are as follows:
- It is an object-oriented language like python, which is used to handle bulky applications carrying very involved business logic.
- Many products have been developed using Java and currently, all the upcoming versions are being handled by Oracle Corporation.
- Java offers multiple features from basic OOPS concepts to multithreading, streams, lambdas, functional interfaces, etc.
- You can follow design patterns implementation using concepts of abstract classes, inheritance, interfaces, etc.
- Rest Webservices, SOAP web service can be developed with Java (web services are used for inter-application communication).
- Java-based projects are generally chosen with a stack containing Spring (for dependency resolutions, security and JDBC template, etc.), Hibernate (for persisting with database) and Java (8 or above preferred). These all make the backend of the application.
- Android-based applications, video-streaming based applications, applets, etc. can be developed with Java.
- Java is platform-independent too.
- Multiple middlewares can be added to perform the task.
- People have published their packages using a node package manager.
- You can incorporate new services like Kafka, Twilio, LogDNA, Auth0, etc. with great ease here.
- The small-scale companies find it easy to continue with this technology for application development.
- A very flexible and in-demand stack called MEAN stack is used, M-> MongoDB, E-> Express.js, A-> AngularJS and N -> AngularJS
- Applications like Paypal and Linkedin use this technology.
- Highly compatible with NoSQL databases too as they deal with JSON or BSON formats.
- This is one of the most flexible languages of all time and many small-scale and some large-scale applications are developed using it.
- Good products based on PHP like WordPress have come up in the market, where it’s easy for people to host and maintain their websites and also they can manage content easily.
- PHP and MySQL are used in conjunction with solution building.
- PHP has a limited scope as it is restricted to the web development arena only, while Python is a full-stack programming language that can be used in data analytics and machine learning also.
- PHP is a scripting language and python is a programming language.
- So only a subset of features offered by PHP match up with python and if just web application development is only the focus then you can go by PHP only.
- Some good products like Github and Slideshare have been developed in Ruby.
- Ruby and Rails structure up a stack when we look for web application development.
- Together these two are so strong that you can get the CRUD operation done in few steps with very little code, while with python you have to do a lot for this.
- Ruby and Rails provide ample advantages as they generate a healthy skeleton for web development.
- Again the major difference is that python holds a strong hand in domains other than web development like data science and machine learning while Ruby is just for web development’s sake.
- Ruby keeps certain things abstract to keep a life of developers easy while python throws up everything to the programmer.
- Just like Python, Ruby is also a cross-platform interpreted language.
- Ruby is dynamically typed language which means a program written in ruby can be modified while the program is running. The ability to treat data as the executable code is called as metaprogramming.
- Well, this language has been developed by Google and hence certain products developed by Google like Kubernetes and Docker are built on Golang only.
- Go is fast, statically typed, compiled programming language. Go is similar in syntactic to C language but has memory safety and garbage collection like features.
- The concurrency mechanisms are good which makes them write programs for multicore and networked machines.
- Go has support for runtime reflection.
- Go is ideal to develop the backend for Single Page Applications and mobile applications but traditional applications need not be developed using it.
- Go offers simple syntax fast compilation and kind of object-oriented programming based on “structural typing”.
- Go has support for socket programming via TCP and UDP protocols.
- Building REST APIs is more powerful and reliable with Go. Probably the developers are fine to migrate from Node and C# to Golang for this.
- While Python is dynamically typed language, Go is statically typed only.
- Scala is both a functional programming language and object-oriented language, primitives are not present here and hence everything is an object, static keyword also is not significant here. Scala is a contraction of the words “scalable” and “language.”
- Apache Kafka and Apache spark like tools have been built on scale.
- Scala’s static types help avoid bugs in complex applications.
- Scala is designed to interoperate with Java Runtime Environment, Scala allows functions to be nested and supports currying.
- Singleton objects provide a convenient way to group functions that aren’t members of a class.
- Using Scala means we need to put less code into a picture and it will be efficient.
- Scala also offers features like immutability, pure functions, recursion, high-order functions, currying, and partially applied functions.
Python is an all-around functional language as it has to offer a lot in both web development as well as data science and machine learning. Now it all depends on what perfectly fits in your application and satisfies your business logic, taking care of scalability and complexity like constraints.
This has been a guide on Python Alternatives. Here we have discussed the basic concept with top 6 Python Alternatives with their features. You may also look at the following article to learn more –