Python still remains the most popular programming language in the world, but Go is starting to climb the ladder. According to Statista, despite Python’s lead with 44.1% of developers using it, Go is gaining traction and comes in at 8.8%.
All technologies and tools eventually die, but some survive. According to a study, Go has just 1.1 million active users, while Python has 7 million users, making it one of the most popular languages in the world.
The reason for Python’s popularity is that it has remained on top of the competition for over a decade. Why should software developers use Golang for software development? This article will analyze the advantages and disadvantages of Python and Go to determine which is the best option for your next project.
Python vs Go: Basic Definitions
What is Python?
Python is a general-purpose, high-end programming language in high demand. As a programming language, it is useful for web development, machine learning applications, data analysis, and other areas of software development. Python is an easy-to-learn programming language that improves readability and reduces the cost of maintaining programs. In addition, it has a package and support system that encourages program modularity and code reuse.
Python’s Best Features
- Free and Open Source
- Easy to code
- Object-Oriented Language
- GUI Programming Support
- Extensible characteristics and Portable
- A high-level language that is interpreted
- Python is a portable language
What is Go?
Golang is a compiled, procedural, and statically typed computer language created by Google. It was developed by Ken Thompson, Rob Pike, and Robert Griesemer at Google in 2007. The language was first released as an open-source coding language in 2009.
In order to handle dependencies effectively, packages can be used to build programs. The use of Golang facilitates the adoption of patterns in the environment, as it does with dynamic languages.
The Go programming language is primarily designed for networking and infrastructure applications. The goal was to replace Java and C++ as the highest-performance server-side programming languages.
Features of Go
- Simplicity
- Robust Standard Library
- Web Application Building
- Concurrency in Golang
- Speed of Compilation
- Testing Support
Python and Go are two different programming languages. Python was created in 1991, which makes it an old programming language. In contrast, Google released Go in 2012. Go is relatively new compared to its competitors. It was developed by Google developers who created the Go programming language. The language was developed to improve development efficiency and eliminate problems.
As we all know, Go is a newer programming language than Python. It is generally considered that Python is a slower language. However, Golang is known for its efficiency. There is flexibility in Python, but there is more rigidity in Go, both from a grammatical and layout perspective.
In terms of Python vs Go, both languages have their own advantages and disadvantages. In contrast, Python is significantly more adaptable than Go, according to experts. The Go programming language is similar to Python and has a wide range of applications.
Go vs Python: Which one is best?
Which is better, Go or Python? When do you use Python, and when do you use Golang? The answer to this question must be based on the specifics of your project. The Python programming language is a popular choice for data analytics, AI-driven projects, machine learning, and web development. A large number of frameworks and libraries support the development of Python in these fields compared to other languages.
What are the benefits of using the Go programming language? The strength of Go lies in its ability to program systems. Due to its support for concurrency, developers are able to utilize cloud computing, and the built-in libraries facilitate the development of websites quickly and efficiently.
Due to Golang’s young age, comparing Go to Python is not very fair. Just ten years after its inception, Go has attracted a number of large companies and developed a small but supportive community. While Python is still the top choice for data science, machine learning, etc., Go can also be used.
Go is highly versatile and can be used for a variety of things. Media company Medium uses Golang for scaling their database, CI/CD pipeline tools for Kubernetes, and eCommerce applications with lots of traffic. Python is also an all-around language used for gaming, enterprise applications, e-Learning platforms, etc. Python is for anyone who needs a language that can handle big data and advanced visualization.
Python vs Go for Scraping
In 2021, a simple experiment was conducted to compare the performance of Go vs Python when scraping public web data. Stock ticket prices were scraped from Yahoo as part of the test. In order to scrape structured, parsed data, the BeautifulSoup library was selected when Python was considered.
It was decided that Goquery combined with Goroutines for multi-threading was the best approach to scraping with Go. According to its name, Goquery is a library that is very similar to JQuery. There were two sets of public web data scrapers, one consisting of 2000 URLs on seven threads and the other consisting of 500 URLs on five threads. Unsurprisingly, the results were staggeringly unequal. When compared to Python, Golang’s performance was more than twice as fast on average.
The fact is that Go is significantly better suited for most public web data scraping needs if you are concerned with performance. As well, such a conclusion is not unexpected, as, within the performance/speed section, it was evident that Go was designed with high performance in mind, as opposed to Python, which is designed with slow performance in mind.
Related: What is a Data Management Platform?
Conclusion
There has probably become apparent that choosing between Go and Python is not as straightforward as it might seem at first. The above-discussed use cases illustrate that both languages were designed with different strengths in mind. Consequently, despite the fact that Go is unlikely to completely replace Python, it has become a serious consideration for speed, scalability, scraping, and machine learning.
