Golang Vs Python: What’s Your Best Pick For AI
Published: 2020-01-29 05:58:19

Python programming language has been gaining popularity over the past few years.
 
Total programming languages worldwide is estimated to be between the range of 256 and above 8,000. However, every developer has their favorite language. But there are only a few numbers of programming languages that top the list when it comes to broad use across various domains and industries.
 
AI programming has gone far beyond one could speculate. Companies dealing with healthcare, real estate, or verticals like e-commerce are now adopting AI in their product development. Before getting into a conclusion, most development team decides which language would be the right pick for the project. Thus, many times choosing the language comes down to Golang and Python. 

However, there are certain parameters to take heed when comparing which programming languages to choose from. Some of the parameters are:

####1.Scalability####

**Golang**

The very first fact that should click out mind should be, Google developed Golang in an attempt to help developers working in Google solve critical problems.  This essentially means the tech giant has hundreds and thousands of developers working on the same software that is hosted on many clusters. Thus, solving problems at a larger scale.
 
**Python**
 
On the other hand, Python does face issues with concurrency but it can still implement parallelism via threads. This simply means that the application will split their task up into smaller subtasks that will be processed in a parallel, but in multiple CPUs and at the same time. 

####2.Performance####

In terms of performance, both Python and Golang are excellent programming languages. But it is said that Google’s compiled language is much faster than the interpreted language such as Python. However, speed is just a primary concern for software development since both these languages are not in much demand on memory and CPU. Also, both Golang and Python follow different kinds of approaches while handling concurrency. 

####3.Applications####

**Golang**

Golang has been used majorly for systems programming. And since the language supports concurrency it is ideal for cloud computing and cluster computing. 

**Python**
 
For every specific programming language, there’s a purpose. In the same manner, Python has been widely used in the field of AI, deep learning, web development, and data analytics. 

####4.Code readability####

**Golang**

Golang comes with strict rules when there’s the involvement of programming. It prevents from developing unnecessary libraries and frameworks. Thus, this gives better code readability by eliminating unnecessary creation of code.  Although Python wins most of the developers’ choice of programming languages, Golang will surely triumph and take a good hit in AI. 


**Python**

For instance, if you’re developing software for your organization or a client, it is evident you’ll be working with a team or perhaps [**several AI engineers**](https://www.artiba.org/blog/the-artificial-intelligence-engineer-career-roadmap-all-you-need-to-know). And at such instances, code readability becomes a huge factor that needs to be taken into consideration. 

Although Python offers fabulous readability. However, at times doing things in ten different ways may lead to a lot of confusion. 

####5.Libraries####

**Golang**

When Go was developed, Google ensures that the libraries should be a part of their inbuilt Go libraries. Although these libraries may not be as robust as Python, the usage of these libraries covers almost every aspect used for AI programming. 

**Python** 

Python has multiple libraries and frameworks and this is one of the biggest advantages. Flask and Django are the two most popular frameworks of Python. However, there are newer libraries that are specifically used in [**AI programming**](https://www.artiba.org/) and machine learning. 

•	Keras and Tensorflow – building deep learning models
•	NumPy – for data cleaning and data manipulation 
•	Scikit-learn – modeling 
•	Caffe – for image processing and classification
•	PyTorch – training deep learning models 
•	Matplotlib – for data visualization 
•	Pandas – data manipulation and data analysis 
•	OpenCV- image processing 

####Summing up####

Both Go and Python have their specific unique features, but it is for you to take the call and choose the language that best fits your preference. However, this also depends on the kind of project you’re working with depending on the end-goal. 

Originally Published: [Golang Vs Python: What’s Your Best Pick For AI](https://worldstrends.siterubix.com/golang-vs-python-whats-your-best-pick-for-ai/)