Programming languages have unique properties and features, among which Python and Go are two of the most popular at present. Go is procedural, functional, and designed for higher speed, while Python is an object-oriented, imperative, functional, and procedural language. Unlike Python, Go supports concurrency, i.e., the execution of algorithm steps out of order.
The TIOBE Index for June 2022 indicates that Python remains at the top of the list, and Go is ranked 15th. Both languages have distinct advantages, while Python enjoys a slight edge in terms of popularity.
But what are the reasons for this?
Language popularity can be traced back to its origins.
Developed in 1991, Python is a well-documented language with official guides for nearly all libraries and is widely used in various open-source projects. As Python allows for easy duplication of previous code and experience, it can be seamlessly integrated into enterprise-class applications.
Go was developed by Google in 2009 and is designed to deal with bloat issues and excessive complexity found in other programming languages. Even though it offers high performance and speed, it lacks features such as a robust library, inheritance, or object-oriented programming, making it more suitable for lightweight threaded deployments.
Python was created earlier with more users, so it has more documentation and implementation codes. As for Go, it has a lot of advantages but is not suitable for heavyweight projects. It doesn't have enough libraries and can't do object-oriented programming, so moving forward is difficult.
Here are the differences between the two:
- Syntax: Python's syntax employs indentation to indicate a code block, while Go's syntax relies on opening and closing brackets.
- Paradigm:Python is a multiparadigm, object-oriented, imperative, and functional programming language. As a language provides a particular set of functionalities in some contexts, it would ideally offer similar functionalities in all contexts. However, it does not support strong encapsulation and is not a pure OOP language. Using the concurrent paradigm, Go is a procedural programming language that shares superficial similarities with C but is perhaps more like an advanced version of C.
- Concurrency: Go has a built-in concurrency mechanism, while Python does not.
- Typed: Python is a strongly typed and dynamically typed language, while Go is a statically typed one, allowing faster error catching at compile-time and reducing severe errors in later production phases.
- Usage: Data science often uses Python, which is well suited to web applications. Python is considered more of a system language.
- Security: Python is a strongly typed language that is compiled, thereby adding a layer of security. Similarly, Go assigns a type to each variable, thus offering security. Nevertheless, if the code encounters any errors, the user must run it independently.
- Memory management: Go provides excellent flexibility in managing memory. While PythonVM fully automates the memory management in Python, programmers are not permitted to take over the process.
- Libraries: Python offers a much larger number of libraries compared to Go.
- Speed: Go is much faster than Python.
Python: powerful and versatile
- Simple syntax:
Python has fewer requirements for code formatting than traditional languages such as C/C++ and C#, allowing users to focus on the reading and writing of code rather than the details.
Python is a programming language that embodies minimalism. For this reason, it is sometimes referred to as a "pseudo-coding language", which refers to a code with a clear structure, simple design, and readability similar to natural language.
- Open source and free of charge
The Python interpreter and modules, as well as the code written in this language, are open-source, which means they can be improved and updated over time.
- Cross-platforms
In general, Python is written in C. The Python interpreter can be found wherever there is a C compiler. Since C has dominated the world for dozens of years, it already has many adaptable platforms. In the same way, Python is an interpreted language that works across platforms.
- Powerful (with many modules)
Python contains many modules, which are implementations of typical functions. Python modules make it easy to achieve tasks from simple string manipulation to complex 3D graphics drawing.
Furthermore, Python has a well-developed community, and on top of the core modules, many third-party organizations contribute to developing modules, including Google, Facebook, and Microsoft. Even for some niche features, Python often has corresponding open source modules, and there may even be more than one option.
There are numerous areas in which Python can be utilized, such as Web and desktop application development, automated scripting, game design, machine learning, and natural language processing. Programmers will benefit from it by improving their efficiency during development.
Utilizing Python's simplicity makes it easier and more convenient to maintain the program in the future compared to other programming languages. The business benefits include a reduction in costs, and an increase in development efficiency.
Go: the strength lies in higher speed
- Simple deployment
Go is compiled to generate a static executable with no external dependencies other than Glibc. This approach provides a great deal of convenience and ease: all that is required is a basic system on the target machine and the necessary management and monitoring tools. There is no need to worry about the dependencies of various packages and libraries, which dramatically reduces maintenance costs. That is a significant difference from Python.
For historical reasons, the Python deployment tools are a bit confusing, which may cause problems in setuptools, istutils, ip, and buildouts for different applications and compatibility. PyPI's official source tends to be outdated, so you must build your own private image, and maintaining it takes considerable additional effort.
- Well-designed
Academically, Go is mediocre and does not support many advanced language features. From an engineering perspective, Go's design is excellent, but the specification is simple and flexible enough to allow programmers with a background in other languages to move quickly into the language. Furthermore, Go provides a complete set of toolchains that enhance the quality and consistency of team collaboration.
Gofmt, for instance, automatically typesets Go code, thereby reducing the problem of inconsistent typesetting styles created by different developers. This editor is configured to automatically run Gofmt during the editing process, which permits the code to be placed at any location during the writing process, which will be automatically corrected later. Furthermore, there is Gofix, Govet, and other handy tools.
- Better performance and concurrency
There is no doubt that Go executes much faster than Python. Unlike Python, which uses resource-demanding threads, Go uses a separate Goroutine that saves both CPU and memory efficiency. This improves both performance and costs.
- Scalability
Many of Go's features are designed to handle concurrent requests for Web resources, making it an efficient language for compiling applications. Languages that can handle multiple requests simultaneously have an inherently higher level of scalability. As businesses grow, programs will be required to perform many tasks simultaneously. Thus, any growing business using Go's backend support will have greater scalability.
The primary goal of Go is to solve the problems C and C+ programmers encounter when writing highly concurrent programs. Based on its syntactic characteristics, Go is primarily a niche language designed to support large backend server programs and is unlikely to become a mainstream language. Ultimately, it depends on the trade-off between high concurrency and development efficiency.
Which one is better?
Both Go and Python are easy to learn and use. Python has a larger community of users, while Go is speedy. At present, Go is primarily used for server-side applications. Python is the preferred language of data scientists and will likely remain that way for some time.
In terms of the use by developers, Python will become more prominent for intellectual analysis, and Go will become more critical for specific underlying calls.
Scalability was a significant consideration during the design of Go. Python also uses concurrency. However, it is not built-in and is parallelized using threads. Therefore, if you plan on working with large data sets, Go seems to be a more appropriate choice.
In terms of performance, Python is not a memory/CPU-friendly language, but it is equipped with various libraries to accomplish basic development tasks. Go has a set of features that make it a better fit for micro-services architectures, which are built into the language.
From an application perspective, Python is more suitable for artificial intelligence, data analytics, deep learning, and web development tasks, while Go is better suited to systems programming, cloud computing, and cluster computing.
Thanks to its long history, Python has a significant advantage in communities and libraries. A vast number of libraries and a considerable community underpin Python's success. However, Go is still in its infancy and has a limited set of libraries and community support. Despite this, the growth and adoption rate of Go has been phenomenal.
Regarding implementation, Go is significantly better in terms of speed.
Hence, the specific use case will dictate which language is appropriate. Go is the better choice for development teams creating microservices due to its high performance, ease of code, and excellent scalability. In contrast, Python is better suited to tasks related to artificial intelligence, machine learning, and data analysis. Developers should consider the nature and size of the project, and their skill set requirements before selecting a programming language.
Nevertheless, it is not that difficult to decide on a language. After all, both Go and Python continue to develop, expand, and grow. Therefore, regardless of the language you choose to use in the future, you can expect more features and improvements to be added to it in the future.
