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Python and Ruby are the two new generations, high-level, server-side scripting languages focusing on simpler, better and high-performance codes. These two programming languages have their own similarities, and differences. This article on Ruby vs Python will differentiate between the two programming languages in the following sequence:
Ruby | Python |
The core function of Ruby is Web development and functional programming. | Python is mostly used for Academic and scientific programming. It has numerous libraries for data science. |
Ruby | Python |
Rails is a Ruby framework which is strongly opinionated and favoring convention over configuration. |
Django is the framework that is similar to Rails. It expedites the modeling process and acts as an ORM. |
Ruby | Python |
It is used for data-heavy sites and servers with high-traffic volume. It operates faster with math, big data, and scientific calculations. |
This is mostly used for implementing complex and high-traffic sites and applications quickly. |
Ruby | Python |
Ruby might take more time to get used to when compared to Python. | The syntax is easier to understand, and it’s more readable to the beginner. |
Ruby | Python |
You will always find many different methods to achieve a task in Ruby. | Python code is not the most flexible but it has a good readability to an inexperienced programmer. |
Ruby | Python |
Ruby’s use has gone down in the list of top 10 languages, from fifth place in 2014 to tenth place in 2018. | Whereas, Python has steadily kept its popularity, moving from the fourth most used language in 2014 up to the third spot in 2015, where it remained through 2018. |
These were some of the comparison factors between the two programming languages. I hope this will help you understand which language fits your goal better.
Now that you have understood the comparison between Ruby & Python, check out the Python Certification Training by Edureka. Python Certification Training will help you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role.
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