Python vs. Ruby: Which is Better for Your Projectblog
This post tries to answer the eternal question, “Which is better?” and the opponents are Python and Ruby. We will not hold the answer for the end — the battle of Ruby vs. Python has no winner. Both programming languages are great and on-demand. Each has unique features, pros, and cons, and our goal is to shed light on them and help readers consider what language will fit their project needs better.
- Historical Overview
- Language Peculiarities
- Use Cases
- Performance Tests
- Which is More Popular
- Demand in the Job Market
Ruby vs Python: Historical Overview
Created in 1995 and 1991 respectively, Python and Ruby were representatives of the new-school of high-level languages, designed to provide programmers the ability to concentrate on coding instead of keeping attention on syntax and hierarchy (Who asked Java?). Python and Ruby are scripting languages and have much in common: they were written using C, they are multi-platform and work with Windows, Linux, and other operational systems, support object-oriented programming out-of-the-box, and perfectly prove themselves in web development for backend coding.
Python and Ruby are decently mature languages, and both have strong communities around the globe. To date, each programming language has tons of ready-made solutions and libraries that make programming on them much more comfortable and efficient.
Ruby vs. Python: Language Peculiarities
Guido Van Rossum
Year of creation
Many features for web development
Elegant to read
Easy to read
many third-party libraries and modules
Use in ML and AI
Can be difficult to debug
High cost of the mistake
Explicit to read compared with Ruby
High memory consumption
Ruby on Rails
Websites that use
Twitter, Apple, Github, Shopify
Google, Pinterest, Youtube, Dropbox
Despite having a lot in common, these languages are different, and the differences begin at the core of how to solve issues. Ruby and Python creators follow the same purpose: “Make coding simple.” However, Yukihiro Matsumoto, Ruby creator, and Guido Van Rossum, creator of Python, have achieved simplicity in their own ways.
Ruby offers developers more freedom. Its conception allows you to solve one problem using numerous approaches, depending on your need and preferences, providing developers with highly flexible options. Experienced Ruby developers know many tricks using a few code lines to solve problems, making Ruby code much more elegant, especially when it comes to the web development framework Ruby on Rails. However, this is a double-edged sword, and learning written code highly depends on its author’s expertise; otherwise, debugging can become a challenge.
In turn, Python follows a more conservative approach to programming: all must be visible to developers. The philosophy of “one possible solution for one problem” possibly makes Python code a bit bulky compared to Ruby. However, programmers always have a clear and transparent picture of element interaction in code. From this angle, Python has an advantage in the case of debugging performance and learning code. Additionally, a more straightforward approach to coding decreases the entry threshold for newbies in learning Python.
Ruby vs. Python: Use Cases
Python and Ruby are multifaceted programming languages that can be used for server scripting, enterprise software, mobile applications, and artificial intelligence in different forms, and of course, web development. However, their core application areas differ.
Python is a more versatile programming language. At their disposal, developers have numerous frameworks such as Pandas, Matplotlib, Scipy, Keras, and TensorFlow that make this language a powerful instrument for creating solutions based on machine learning and data science technologies. It’s also often used for programming Linux servers, and overall, Python is a more science-oriented programming language than Ruby. Possibly, this is due to its direct style.
Moreover, Python also has all the necessary to accomplish web development tasks. World-renowned companies created their websites using Django, a Python-based framework that follows model-template-views (MTV) architectural pattern. Google, Youtube, Dropbox, Pinterest, and National Geographic are developed using Django, and this is an impressive list.
Ruby is a more narrowly-focused programming language, and its main application area is web development. Possibly, this is because of Ruby on Rails (RoR) and its relevance and applicability for business and e-commerce apps. RoR is a server-side web application framework that was developed just on Ruby. RoR, as well as Django, provides programmers all concepts of MTV architectural patterns for databases, web services, and web pages. Approximately, the backend of 1 million websites were written Ruby on Rails, and among them such giants as Github, Shopify, Twitch, Airbnb, Zendesk, and many others.
Due to the unique flexibility and elegance of Ruby, programming with RoR allows developers to quickly create market-ready products, concentrating on the business process of the future solution rather than programming all functions from scratch. Developers highly appreciate it for its elegant solutions and flexibility in solving issues. Moreover, RoR has proved to be an effective tool for creating web applications that raise popularity. Along with high development speed, it often plays a decisive role in choosing a server-side programming language.
Ruby vs. Python Performance Tests
Speed testing of programming languages is not a piece of cake, especially regarding estimation fairness. A language can demonstrate lower performance in solving one task and be extremely quick in another. Benchmarks.games conducted competitions for Python and Ruby, using various programs that involve multiple features of both languages. For the test, they use the latest versions — Python 3.9.0 and Ruby 3.0.0-preview2. Several parameters were tracked during testing, but we would consider the only time needed for program processing. If you are interested in a full report, you will find it here.
Processing time (sec)
Indexed-access to tiny integer-sequence
Eigenvalue using the power method
Generate Mandelbrot set portable bitmap file
Streaming arbitrary-precision arithmetic
Match DNA 8-mers and substitute magic patterns
Generate and write random DNA sequences
Hashtable update and k-nucleotide strings
Read DNA sequences – write their reverse-complement
Allocate and deallocate many many binary trees
Python defeated Ruby in 7 out of 9 performance tests. However, this is without considering the hardware resources that each language took for processing. In other words, in real-life tasks, these numbers will not play essential roles and will show equal processing speed, unless it’s about a heavy program that is quite rare.
Ruby vs. Python: Which is More Popular
Another chart shows what percent of Stack Overflow questions in the months related to Python and Ruby. The Python community is many times bigger, but the overall picture of rising Python and declining Ruby trends is obvious.
The situation with frameworks Ruby on Rails and Django looks similar to the Ruby vs. Python chart. Experts claim that a sharp increase in Django popularity began in 2017 alongside AI implementation in web development processes.
Ruby vs. Python: Demand in the in the Job Market
According to the Hacker News Hiring Trends chart, Python developers are required 5-10% more often than Ruby experts.
However, comparing Ruby on Rails and Django, the situation is the opposite. RoR’s specialists are more demanded in the market. This is because Ruby is used in millions of websites worldwide, and companies need specialists for their updates and maintenance. The high speed of development with Ruby and its options to quickly create website prototypes and launch demos make it popular for startups and small-sized companies.
Ruby vs. Python: Conclusion
With regards to web development, Ruby on Rails and Django are used to create a website server-side, and both do it at the highest level. In general, any results you achieve with Ruby, you also gain with Python. Often, in this case, workforce capability plays a decisive role. If you need a quick time to a market solution, Ruby looks like a better option. If you are going to use machine learning or data science in the product, pay attention to Python.
NIX United has experience in software development using Python and Ruby as well. If you doubt what technology fits your project, feel free to contact us for consultation.