Go vs Python | Know Their Differences and Which Should You Learn?
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Go vs Python | Know Their Differences and Which Should You Learn?

Last updated on 28th Dec 2021, Blog, General

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Nirvi (Python developer )

Nirvi is a Python developer with 7+ years of experience in the Hadoop ecosystem, Sqoop, Hive, Spark, Scala, HBase, MapReduce, and NoSQL databases, such as HBase, Cassandra, and MongoDB. She spends most of her time researching technology and startups.

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On most benchmarks, Go beats Python by far. Go even beats Java’s speed, which is widely considered to be significantly faster than Python. If it comes down to needing a program to load software quickly, Go is the way to Go.

    • Introduction to Go vs Python
    • Why use go vs Python?
    • Features of go vs Python
    • Disadvantage of go vs Python
    • What does syntax look like in python and go?
    • Is python faster than Go
    • Error Handling in python and go
    • Does Python or go support concurrency
    • Conclusion

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      Introduction to Go vs Python:

      Go is an open source programming language developed by Google. It is a statically typed compiled language. This language supports concurrent programming and also allows multiple processes to run simultaneously. This is achieved using channels, goroutines, etc. Go has garbage collection, which does memory management itself and allows deferred execution of tasks.

      Python is a high level object-oriented programming language. It has built-in data structures, combined with dynamic binding and typing, making it an ideal choice for rapid application development. Python also provides support for modules and packages, allowing system modularity and code reuse. It is one of the fastest programming languages as it requires very few lines of code. Its emphasis is on readability and simplicity, making it a great choice for beginners.

      Why use go vs Python?

      Here, are the important reasons to use the Go language:

    • This allows you to use static linking to combine all dependency libraries and modules into a single binary file, depending on the type of OS and architecture.
    • The Go language performed more efficiently because of the CPU scalability and concurrency model.
    • The Go language provides support for many libraries and tools, so it does not require any third party libraries.
    • It is a statically, strongly typed programming language with an elegant way to handle errors

    • Why use the Python language?

      Here, the reasons for using the Python language are given:

    • Python is a powerful object-oriented programming language.
    • Uses an elegant syntax, to make the program you write easier to read.
    • Python comes with a large standard library, so it supports many common programming tasks.
    • Runs on a variety of computers and operating systems: Windows, macOS, Unix, OS/2, etc.
    • Very simple syntax compared to Java, C, and C++ languages.
    • Extensive libraries and useful tools for developers
    • Python has its own auto-install shell
    • Python code is easier to write and debug than code in other languages. Therefore, its source code is relatively easy to maintain.
    • Python is a portable language so that it can run on a wide variety of operating systems and platforms.
    • Python comes with many prebuilt libraries, which makes your development work easier.
    • Python helps you simplify complex programming. Since it is intrinsically related to memory address, garbage collection.
    • Python provides an interactive shell that helps you test things before its actual implementation.
    • Python provides database interface to all major commercial DBMS systems.

      Features of go vs Python:

      Features of Go :

      Here, the important features of Go language are:

    • Open-source project
    • Made on google
    • Compiled language
    • Easy concurrency support via goroutine
    • Package management
    • Static typing
    • Powerful standard library features
    • Garbage collection called goland
    • Concurrent support
    • Great library
    • Easy and readable code

    • Features of Python:

      Here, the important features of Python are:

    • Easy to learn, read and maintain
    • It can run on different hardware platforms and use the same interface.
    • You can include low-level modules in the Python interpreter.
    • Python provides an ideal structure and support for large programs.
    • Python provides support for automatic garbage collection.
    • It supports an interactive mode of testing and debugging.
    • It provides high-level dynamic data types and also supports dynamic type checking.
    • Python language can be integrated with Java, C and C++ programming code
    • high performance
    • simple, minimal syntax
    • fast compile time
    • statically linked binaries that are easy to deploy

      Disadvantage of go vs Python:

      Disadvantages of GO:

      Here, there are disadvantages/disadvantages of using GO language:

    • Go is not a common language
    • API integration with Go does not have an officially supported Go SDK.
    • poor library support
    • fragmented dependency management

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      Disadvantages of python:

      Here, there are disadvantages/disadvantages of using Python language:

    • Used in less platforms.
    • Weak in mobile computing, so not used in app development
    • Since Python is dynamic, it shows more errors at run-time
    • lack of professional support

      What does syntax look like in python and go?

    • Predefined commands to make commands understandable by the computer. Is there any difference in the syntax of these programming languages? let’s check. Syntax is one of the aspects that affect readability level. Let’s take a look at how static and dynamic typing can change readability, for better or worse.

    • In Python, as a dynamic language, not every function is documented. This sometimes forces you to dig deeper into the implementation, or alas, you have to guess which input parameters are expected. Go, as a statically typed language, hands everything to you regarding the input type. Python syntax is quite dense, but uses a lot of English words. This makes it more understandable and easier. One of the Python principles states: “There must be one obvious way to do this – and preferably only one.” With this mantra in mind, the newly created syntax is probably the easiest and most consistent. Still, you have to keep track – Python syntax changes with each new version of the language.

    • One of the strengths of the Go programming language is its minimal syntax – it has remained almost the same without any major changes in recent years. Thanks to this you have a guarantee that applications written in the old Go language version will still work. This means that developers do not have to learn new paradigms or syntax. What’s more, there is only one standard code format.

    • Everything above points to the strengths of Go, unless you want to write code that isn’t strictly syntax based. The Go programming language leaves no choice for you – you have to be faithful to gofmt. Python helps you – PEP 8. PEP 8 is a guide full of conventions for enhancing and enriching the standard Python library and is considered a formatting standard for Python projects.

      Is python faster than Go:

      In order to properly compare the speed of these languages, some tasks were chosen to show how fast Go and Python can solve them:

      • Mandelbrot – Python 3: 163.32 sec vs Go: 3.73 sec.
      • fannkuch-redux – python 3: 352.29 sec vs go: 8.31 sec.
      • K-nucleotide – Python 3: 46.28 sec vs Go: 7.46 sec.
      • n-body – python 3: 567.56 sec vs go: 6.38 sec.
      • Reverse-complement – Python 3: 7.20 sec vs Go: 1.35 sec.
      • binary-tree – python 3: 48.03 sec vs go: 12.23 sec.
      • phidgets – python 3: 1.28 sec vs go: 1.00 sec.
      • Regex-Dux – Python 3: 1.36 sec vs Go: 3.85 sec.

    • As you can see, Python was faster than Go in only one case. What, like in the n-body case, makes Go 89 times faster than Python? This is not an isolated example – in fancuch-redux, Go is about 43 times faster. The main reason the difference is so obvious is that Go is a compiled language as opposed to interpreted Python.

    • The Go programming language has another advantage: goroutines. These lightweight threads require less RAM and are managed by the Go runtime. Goroutines use fewer resources than traditional threads (such as in Python). Moreover, multithreading in Python cannot be taken literally – Python programs are single-threaded with the possibility of connecting concurrent routines.

    • But speed is not the only important aspect when building an application. Exception handling can be an important factor when choosing the most appropriate programming language for your needs.

      Error Handling in python and go:

      To be specific, we are thinking of exceptions. Exceptions are anything unusual that demands special/separate processing. They are not due to errors in syntax. Handling exceptions guarantees that the program flow is not interrupted when an error occurs.

      How do the Python and Go programming languages ​​deal with exceptions?

    • Exception Handling in Python
    • In Python, you can handle exceptions with three statements:
    • Try
    • Apart from
    • Finally

    • The statements between the try and all except make up a try clause. There are a few possible scenarios when you execute the try clause:

    • No exceptions – After executing the try statement, the except statement is passed, and the try statement terminates.
    • There is an exception – if the exception matches the one named in the exception statement – this clause is executed, the rest of the try statement is discarded.
    • There is an exception, but it does not match the exception mentioned in the exception statement – it is an unhandled exception, and execution has been stopped.
    • In either event the last statement is executed. This is just a cursory explanation of how exceptions are handled in Python – on their official site, you can find a more complicated tutorial.

    • Digging deeper into this topic, you can also find a raise statement. This statement helps to raise the exception – it’s just being coerced to happen. But you should be aware that you should use this statement only in emergency situations. It is not a solution to control program flow.

      • if name == “” {
      • return “”, errors. new(“Name is empty”)
      • ,
      • return “hello” + name, null
      • ,
      • func main() {
      • var error error
      • bridesmaid greeting string
      • Greeting, error = Greeting(“”)
      • if err != null {
      • fmt.Println(err)
      • } Otherwise {
      • fmt.Println(Greetings)
      • ,
      • Greeting, err = Greeting(“Jimmy”)
      • if err != null {
      • fmt.Println(err)
      • } Otherwise {
      • fmt.Println(Greetings)
      • ,
      • ,

      In this scenario, we have a function Greeting that takes a name and returns a Greeting. In case of an empty name it fails and gives an error. The result of the first call would print “Name is empty” and the second would print “Hello Jimmy”. This is a simple example, but it shows the main idea of ​​a multi-value return with no errors. With this pattern, any developer using a function is aware of whether the function can generate an error simply by looking at its signature. With panic/recovery mechanisms, anyone wanting to use the function would need to inspect the underlying implementation.

      Additionally, any error should be handled only once. This means that any time an error occurs it must either be logged, passed on, stored, or handled in-place. Handling an error in this way simplifies the flow and makes code behaviour more predictable because ultimately the error is handled in one place somewhere deep in the code without any side effects.

      One of the most popular complaints about Go (especially from newcomers) is the “if err != nil {…}” pattern. Many say that it clouds the code and makes it difficult to read. However, there are patterns (such as one-line ifs) that can simplify the “if err != nil {…}” waveform.

      Does Python or go support concurrency:

      Concurrency is the ability to execute multiple processes at the same time. One of the advantages of this approach is the time savings, which is not the case when you’re waiting for one task to complete before the next. Python does not natively support concurrency, but provides some solutions to achieve concurrency, such as:

      Threading – A thread is a set of operations that can be executed independently of others.

      asyncio – a dedicated library for writing concurrent code with the help of async/await syntax.

      Multiprocessing – Python supports multiprocessing by sending tasks to different processors.

      The Go programming language is famous for its strong support for the concurrency paradigm. The biggest helpers are goroutines and channels:

      Goroutines – A function that is capable of running concurrently with others.

      Channels – are connectors between goroutines. They enable communication and synchronisation between them.

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    • Go is a very performant language with lots of support for concurrency. It is almost as fast as languages like C++ and Java. Although it takes a bit longer to build things using Go than Python or Ruby, you’ll save a tonne of time optimising the code. We have a small development team at Stream powering feed and chat for over 500 million end users. Go’s combination of a great ecosystem, easy onboarding for new developers, fast performance, solid support for concurrency, and a productive programming environment make it a great choice. Stream still leverages Python for machine learning for our dashboards, sites, and personalised feeds. We won’t be saying goodbye to Python any time soon, but going forward all performance-intensive code will be written in Go.

    • In short, both Python and Golang have their own benefits, depending on the programmer’s skill and ability to scale to a real-world requirement. When it comes to syntax both Python and Golang are very clear and clear and reduce the task of the developer to a great extent. Choosing the appropriate language for your coding can point to the difference between an effective program and a program that requires a lot of maintenance. If speed and scalability is your primary objective for developing tools, then Golang is your right choice. Golang is the language that comes close to the speed of C/C++, plus it is very easy to use, and you can even get rid of manual memory management.

    • But, if you want to generate scripts and tools that run effectively across teams while promoting readability, Python may be the best option for you. The language reads like regular English and can be well understood even by developers who don’t have experience with Python before. By default, indented blocks make the code neater, and support clean coding. And the various libraries available for free reduce the number of lines used within your code.

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