The web development industry is going to be the key aspect for those who are trying to scale their businesses worldwide. Choosing the right programming language is important if you are going to design a website.
Python and Golang are considered the two most advanced programming languages used for web development and machine learning. Both have unique strengths and applications which makes them popular choices for different types of web development and machine learning projects.
This blog provides an in-depth comparison of Go vs Python in terms of web development and machine learning. By going through their strengths, use cases, and performance you can choose the best programming language according to your project requirements.
Overview of Golang vs Python:
Here in this section, you can learn more about the history and key features of both programming languages. So you can find out which one between Python vs Golang is best for the next project.
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1. Go (Golang) : Go is usually known as Golang and it was created in 2007 by Google. It is known for its simplicity, performance, and efficient concurrency model. Golang’s statically typed nature and compilation of machine code allow it to build high-performing and scalable web applications.
- Concurrency : Go’s concurrency model is created around Go routines and channels. This model allows developers to write multiple programs more easily which makes Golang highly suitable to build applications that require high levels of similarity.
- Simplicity : Golang’s syntax is clean and straightforward which focuses on simplicity and readability. This simplicity helps to reduce the excessive load on developers and improves the maintainability of the code.
- Compilation and Deployment : It creates a single binary file without external dependencies which helps to simplify the deployment process in different types of environments.
- Use Cases : Golang is mainly used in web development, system programming, and cloud services.
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2. Python : Python was created by Guido van Rossum in 1991. One of the main reasons behind the popularity of Python is its attention to code readability and simplicity. It prioritizes the developer’s productivity and program readability which makes it a preferable choice among the programmers for different types of applications.
- Easy Learning and Use : Python’s syntax is clean and easy to read, making it an ideal first language for beginners. Its simplicity allows developers to write less code to complete the tasks which can improve the development speed.
- Community and Support : Python has one of the largest and most active programming communities. It means that you can get extensive documentation, tutorials, and community support which are extremely helpful for troubleshooting and learning.
- Versatility : Python’s versatility allows it to be used in different types of industries like web development, automation, scientific computing, and artificial intelligence.
- Use Cases : Python is used for web development, machine learning, data science, automation, scripting, and many more.
Comparison Between Python vs Golang for Web Development
While doing the comparison of Go vs Python for Web development you need to understand the advantages of both programming languages. Golang is a better option to build high-performing and scalable web services. Python’s ease of use functionality makes it one of the best choices for the quick development of complex web applications.
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1. Golang for Web Development:
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Frameworks and Tools :
- Gin : It is a high-performing micro framework for Golang (Go). It is known for its speed and minimalism which provides more than enough functionalities to build different types of web applications. Gin is the best option to build RESTful APIs due to its ease of use.
- Echo : Echo is another high-performing, extensible, and minimalist web framework for Go. It provides API and powerful features like middleware support, routing, and HTTP/2 support to make it a perfect choice for building high-performing web applications.
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Real-World Use Cases :
- Uber : Uber uses Go to handle high-throughput and real-time processing in its geo-fencing service from Go’s concurrency model.
- Dropbox : Dropbox migrated some of its most important backend services to Golang to reduce latency in its file storage systems.
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Frameworks and Tools :
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2. Python for Web Development:
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Frameworks and Tools :
- Django : Django is a high-level Python web framework that is used because of its rapid development and clean design. It provides robust out-of-the-box features like an ORM, authentication, and an admin interface. Django helps developers build complex applications quickly and efficiently.
- Flask : Flask is a micro framework for Python based on Werkzeug and Jinja2. It offers more flexibility and control over components so that developers can choose libraries and tools according to their requirements. Flask is lightweight and modular which makes it perfect to build small and medium-sized applications.
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Real-World Use Cases :
- Instagram : Instagram was built using Django and it uses Python’s capabilities to handle large numbers of users and huge amounts of data efficiently.
- Spotify : It uses Python for data analysis and backend services to utilize its simplicity and different types of available libraries.
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Frameworks and Tools :
Comparison Between Python vs Golang for Machine Learning
When you are doing the comparison of Golang vs Python for machine learning you need to understand specific requirements of your project. Python is one of the best programming languages for machine learning because of its smooth integration with data science tools. Golang can be beneficial in handling certain machine-learning tasks that require efficient data processing and high computational power.
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1. Golang for Machine Learning :
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Libraries and Tools :
- Gorgonia : Gorgonia is a library that can help developers build and train machine learning models in Go. It also provides a flexible and efficient way to create deep learning networks to conduct symbolic computation.
- Gonum : Gonum is a set of numeric libraries for Golang that is designed to make scientific computations easier. It is not only a machine learning library but it provides the foundational tools required to implement machine learning algorithms.
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Example Projects and Use Cases :
- Infrastructure Tools : Golang’s performance and efficiency make it a good choice to develop different types of infrastructure tools that support machine learning workflows like data pipelines and microservices. It is one of the best programming languages used to handle stream processing solutions.
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Libraries and Tools :
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2. Python for Machine Learning :
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Libraries :
- TensorFlow : TensorFlow is developed by Google and it comes with a whole ecosystem of tools, libraries, and community resources. It allows researchers and developers to build and deploy ML-powered applications. TensorFlow provides support for different types of tasks like image recognition, natural language processing, and neural network training.
- PyTorch : PyTorch is developed by Facebook’s AI lab. Its dynamic computational graph makes it a favorite choice among researchers and developers for developing deep learning models.
- Scikit-Learn : This library is built on NumPy, SciPy, and Matplotlib. It provides simple and efficient tools for data mining and data analysis. Scikit-learn can be used by everyone and it is reusable in different types of contexts like implementing machine learning algorithms in Python.
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Example Projects and Use Cases :
- Google : It uses TensorFlow for different types of ML tasks like image recognition, language translation, and recommendation systems.
- Facebook : Facebook has used PyTorch for its AI research and development in neural networks and deep learning applications.
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Libraries :
Comparison Between Python vs Golang in Tabular Form
Here you can go through a detailed comparison between Golang vs Python and determine which programming language is perfect for you.
Feature | Golang (Go) | Python |
Developed By | Python Software Foundation | |
Type | Statically Typed | Dynamically Typed |
Syntax | Simple like C | Easy to read |
Performance | High similar to C/C++ | Moderate because it is slower than compiled languages. |
Garbage Collection | Yes | Yes |
Compilation | Compiled | Interpreted |
Error Handling | Explicit error handling | Exceptions |
Use Cases | System programming, backend services, cloud services. | Web development, data science, scripting automation. |
Learning Curve | It is hard to learn. | It is easy to learn. |
Community Support | Golang has a constantly growing community of developers. | Python already has a large and diverse community of developers. |
Cross-Platform | Yes | Yes |
Package Management | ‘go mod’ | ‘pip’ |
Tooling | Excellent with built-in tools like ‘go fmt’, ‘go test’ | Excellent with tools like ‘pytest’, ‘black’, ‘flake8’ |
Memory Management | Automatic but has manual options. | Automatic |
Deployment | Compiled binaries and easy deployment. | It requires an interpreter and virtual environments. |
Documentation | Detailed | Detailed |
Community Resources | Gophers Slack, Go Forum, Golang Bridge. | Python.org, PyPI, Stack Overflow, and other online courses. |
Notable Companies | Google, Dropbox, Docker, Uber. | Google, NASA, Instagram, Spotify. |
Extensibility | Limited because of the language’s simplicity. | Highly extensible that comes with C/C++ integration. |
Syntax Features | Strict and clean | Flexible that uses indentation for block limits. |
When Should You Choose Golang for Development?
Now that you have gone through the comparison of Golang vs Python, let’s understand when you should choose the Golang programming language for development.
- High-Performing and Simultaneous Applications : Go’s ability to handle multiple tasks simultaneously without affecting performance makes it a more suitable choice for building real-time systems, high-traffic servers, and performance-focused applications.
- Microservices Architecture : Golang’s simplicity and ability to create standalone binaries without dependencies simplify the development of microservices and improve their scalability.
- System-Level Programming : Because of Golang’s performance and control over system resources you can easily do system-level programming and build infrastructure tools.
When Should You Choose Python for Development?
Ultimately the choice between Go vs Python depends upon the specific requirements of your project. See when you should choose Python for development.
- Quick Prototyping and Development : Python’s different types of libraries and frameworks allow quick development making it one of the best choices for startups and projects with tight deadlines.
- Machine Learning and Data Science : Its ecosystem for machine learning and data analysis includes libraries like TensorFlow and Scikit-learn making it the perfect programming language to handle data-driven projects.
How Seven Square can help to Choose the best programming language between Go and Python?
At Seven Square, we have a team of developers and consultants who understand your specific project requirements and suggest whether Python or Golang is best for you. Our developers provide advice following real-world use cases and the industry’s development protocols.
It is important to choose the right programming language for long-term success. We evaluate the ease of maintainability and community support for both Go and Python to ensure that your choice stays relevant in the future.
Our experts evaluate each language’s compatibility with the latest technological trends like cloud computing, microservices, and artificial intelligence. You can connect with a web development company if you don’t want to do programming by yourself and suggest ideas for a web solution.
Do You Want to Optimize Your Website’s Performance with Go Or Python?
If you are ready to start your next project and need guidance or if you want to understand Go and Python more deeply then don’t hesitate to reach out to us. Our experienced developers can help you to make the best choice according to your requirements.
FAQs
Golang is slightly better than Python in terms of execution speed. But Python’s simplicity allows a faster development procedure that can be done by the developers.
If you are working on a small and simple machine learning project then Python is the best choice for you. But if you are working on a large and complex machine learning project then you should go for Golang (Go).
Golang is considered much easier to learn in comparison to Python.
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