Python vs TensorFlow.js


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Decisions about Python and TensorFlow.js

1. Type safety and inferred types

Go is type safe by default, which allows you to right more reliable code and have better developer tooling, plus with the := operator, you can initialize a variable without having to define its type because it automatically gets its type from the initial value.

2. Performance

There isn't much to be said here, but on most counts go beats both Python and Node.js on performance.

3. Documentation

I'm not talking about the Go language itself, although it does have good docs. I'm talking about Go's auto generated documentation tool, which allows people to document their packages easily and works amazingly with Go's type system.

4. Compiles to binary

If you are making a local program for somebody and they don't want to download the Go compiler, you can make Go into a native binary.

5. Built for the web

Go has built in Http libraries to rival Express.js and has a HTML/Text templating system.

6. Great Concurrency

Go utilizes Goroutines to help developers utilize multiple threads easily.


Go is an excellent choice for any system code, especially http networking and web backends.

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Kyle Harrison
Web Application Developer at Fortinet · | 17 upvotes · 105.6K views

Node continues to be dominant force in the world of web apps, with it's signature async first non-blocking IO, and frankly mind bending speeds. PHP and Python are formable tools, I chose Node for the simplicity of Express as a good and performant server side API gateway platform, that works well with Angular.

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Octavian Irimia

Both PHP and Python are free but when it comes to web development PHP wins for sure. There is no doubt that Python is a powerful language but it is not optimal for web. PHP has issues... of course; but so does any other language.

Another reason I chose PHP is for community - it has one of the most resourceful communities from the internet and for a good reason: it evolved with the language itself.

The fact that OOP evolved so much in PHP makes me keep it for good :)

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Pros of Python
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    What is Python?

    Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

    What is TensorFlow.js?

    Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
    What companies use Python?
    What companies use TensorFlow.js?

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    What tools integrate with Python?
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    What are some alternatives to Python and TensorFlow.js?
    Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!
    R Language
    R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
    Scala is an acronym for ‚ÄúScalable Language‚ÄĚ. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.
    A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
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