Switching to a new language is a big step, specifically when only one of your mates has prior experience with that specific language. These days, most of the starred/forked codes at Github have various tags: categories seem to be written in GO language. 2 to 3 years back, it was a similar scenario with Python, but the game has changed.
This blog compares both these languages and provides you with a clarification as to which one will be ideal for your next project: Go vs Python in 2022.
In the technological world of web development, Agility is a king. Businesses are gaining a competitive edge by having their digital presence. However, on-demand web development does not fulfill the product’s requirements, as there is a special demand for seamless user experience and advanced usability. This is where one needs to adopt a more functional and advanced programming language with a modern server-side stack. Is it going to be Golang or Python? Find it out Go for web development or Python for backend.
Before beginning any new project, almost all of the development teams these days have to go through a series of meetings to decide which one is the best programming language for the software that they are going to develop. When it comes to this discussion, two of the most popular and used options are Python and Golang.
If we compare the Google trends of both these programming languages in the past year, here are the results.
Of course, Python is proven and here for a long time, so the difference in the graph. Go is quite new but has immense potential. Golang for Machine Learning is gaining good traction so far.
Without a doubt, machine learning is the future but the doubt rises when you got to choose the ideal programming language for developing machine learning applications.
Earlier machine learning enthusiasts would always prefer Python because of its simplicity, consistency, established community, and exclusive libraries. However, the trend changed as Golang came into the picture.
Python is a highly readable language. It is simple for the human mind to understand, and hence it becomes easy to use Python for Machine Learning. Developers find Python easy to learn, so they prefer to use it over any other programming language.
For a big complicated machine learning project, Python is highly suitable because it allows collaborative implementations from multiple developers. Moreover, it is a general-purpose language, so a set of machine learning tasks can make use of it, and developers can build prototypes to test their AI products.
The most prominent benefit of using Python is the availability of extensive support libraries. Specifically, for AI and ML, Python has the following:
Such tremendous support eliminates the development time and overhead for programming.
Python has a vast ecosystem, and it has the OSI-approved open-source license, which makes it free to use and distribute. The vibrant and active community members are continuously collaborating by creating new libraries, updating documentation, and extending the toolset.
Because Python is an interpreted language, your ML program may execute slowly line by line. Now, when we want futuristic AI/ML applications, then how can we compromise on the speed?
Python is not considered a strong backend language for mobile computing. This is the reason why Android and iOS do not support Python for their official programming.
The database access layer of Python is quite underdeveloped when compared to JDBC and ODBC. Hence it is not an ideal choice when developing applications for big enterprises.
Golang is comparatively new. It was launched a decade back in 2009 by Google. NOT because Python is an older one, but just because of Go’s advancement and Golang popularity.
The main plus-point of Go is its simplicity. Developers thought that Python was simple & easy only until they used Go because Go is simpler than Python.
Golang is a compiled language, and it compiles into a single library. It is a statically typed language, and it links all the dependency libraries and modules into a single binary file.
Here, developers need not install dependencies on the server. Instead, she just had to upload a compiled file for her app to start working.
Go uses goroutines for concurrency, which is a resource-efficient way to save CPU and memory. Programmers are super-impressed by the faster performance of Go as it saves costs and resources.
Most of the tools needed for ML are already in-built into the Go library, so developers don’t look for third-party libraries. Go programming language has superficial native support for tools that speed up the entire process of app development. Also, the Go community is getting strong and reliable for any kind of help.
A significant advantage of using Go is getting a top-notch Integrated Development Environment (IDE). Most developers feel that in an agile, competitive world, an IDE is the most crucial aspect for development as it can speed-up or hinder the process. Golang comes with a comprehensive IDE and excellent debugging tools and plugins.
The Go language has a precise syntax, which makes it easy and straightforward. No unnecessary components are holding back the developers on the structure. Instead, development becomes direct and clear.
Knowing such ease and usefulness of Go, it seems to be an ideal choice for machine learning development services and she started implementing ML. And here’s what she found:
As mentioned earlier, Golang doesn’t require additional libraries; it writes everything in core. Though it provides lesser libraries, those specific libraries cover a broad scope of purposes. The GoLearn library covers data handling; Hector covers binary classification problems; Theano is similar to TensorFlow, and Goml for passing data.
However, Go still needs to work on its toolkit development. It is still in progress and has already set up a good community on GitHub.
Math computations are like cake pieces for Go. Unlike Python, large-scale projects are better suited to Go owing to its scalability and performance. When it comes to complex AI computational math programs, Go performs 20-50% better than Python.
Go follows the minimalistic approach for its AI and ML algorithms. After the implementation, developers of Go create very readable code because of this minimalistic approach.
The choice between these two amazing programming languages often becomes a difficult one for someone who is not familiar with the characteristics of each. In this blog, we will be discussing these two programming languages in detail and will compare the parameters which can help in finding out the best one between these two.
Here we are going to have a head-on comparison of these two programming languages to find out which one is best suited in-between Go vs Python for backend projects.
The performance of both these programming languages can be tested easily by including several factors such as memory management, functionality, and speed. Both the programming languages performed remarkably.
You might want to compare Go vs Python speed, where you will find Golang a bit better. However, both Python and Go performance is unquestionable.
In this day and age, having an application building process that is scalable is one of the most important things to consider for a development company. Golang as a language was created, keeping this parameter in check. For a Golang Development company like Google, the support and ideas of concurrent process channeling proved to be a significant factor.
However, when it comes to Python, the language surely showed some problems in the case of concurrency but had fantastic results when it came to parallelism. Python provided consistent results when it came to splitting up the tasks in order to provide better scalability for the programming language.
The term concurrency means that a particular app is making significant progress when it concurrently comes to multitasking. Let us provide you with an example. Say a computer has just a single CPU, then the application might not progress in different tasks. However, inside an app, various tasks are being processed. In a way, the computer will not be able to finish a task properly before it starts with the new one.
On the other hand, Parallelism states that an application can split up the tasks to create smaller divisions for processing in a parallel format, which makes the job of completing the tasks a lot easier. The bottom line here is that the Golang development services, as well as the Python services, are both compatible with their respective fields of interest. While one centers on concurrency, the other has the edge on parallelism.
But Golang is the language that is best suited for systems programming. Since it has concurrency on its side, there is no doubt you will be able to find acceptance and use in the fields of cluster computing and cloud computing as well. Apart from that, Golang also has its use in the field of web development due to its ease of use when it comes to libraries. With the help of Golang, you will be able to set up a proper web server easily, and it will just take a few seconds. There are different purposes for both these programming languages, and each one of them fulfills the purpose with credibility.
Code execution is another one of the main factors upon which the popularity of a programming language rests. Python is a language that is typed dynamically, and Golang is the one that is typed statically. While Python uses an interpreter, Golang uses a compiler for the execution. So, what is the difference between a dynamically and a statically types language?
Well, in the case of a dynamically types programming language, the type interface can be implemented with the help of a proper interpreter, and hence there might be the presence of some bugs. However, in the case of a statically types programming language, there is no presence of the bugs because they are caught easily due to the computer-types interface.
So, while there might be some limitations for you in the case of Python, Golang can be executed with finesse, and hence, it is a good idea to hire Golang developers for the proper execution of code. However, Python doesn’t prove to be a bad competitor either as there is uniqueness with the dynamic pattern, which is not found in other programming languages.
For a developer, having a properly functioning library is one of the essential aspects. So, in case having a proper programming language is deemed pretty necessary. Python is the language that stands out in such a case because of the sheer amount of space when it comes to the libraries.
With fantastic packages such as Numpy, it can be a help in dealing with matrix functions and array handling. Scikit and Tensorflow help in Deep Learning, Pandas helps in Data Analysis, and other packages that can help a lot in other essential functions. The library of Python is one of the main reasons why developers tend to choose it in the first place.
However, that doesn’t mean that Golang can be left behind in the case. During the development process of the Golang, Google decided to use the most amazing libraries. When it comes to the comparison, Golang might not go near Python due to the boisterous number of libraries. But when it is a comparison of the usage fields, these two languages are mostly the same. There are amazing libraries for database handling, web development, encryption, and concurrent programming.
We have already seen the pros and cons of both Golang and Python. You will agree with us that both have their awesome features and some drawbacks, but when you have to classify, we have concluded the ideal scenarios when using which programming language will be beneficial to your business:
From the points mentioned above, you can say without a doubt that both these programming languages have their pros and cons when it comes to choosing one. So, did you get the exact reason, which one to choose to level up your business, because Go is safe to use when it comes to building reliable applications, on the other hand, Python is being employed in developing ERP tools to take care of everything from business management to data analytics.
We have Golang, Python and specific Machine Learning engineers to assist you with your ML project. Contact us to know how we can help you with your customized business requirements!
Comparatively, Golang is easy to learn than Python.
Python has expertise in developing AI/ML applications, but Golang is young and has immense potential in AI. There is a huge scope for sure.
Here are some free resources/courses where you can learn ML with Python:
Go is fast in comparison to Python.
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