2017 development of Go language programming

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after 7 years of Go Open source, it has been adopted worldwide. They can make it easier to show data models to others in applications that are readable and available for production environments. Combined with this is the extensive use of Go, and a data specialist creates a "usable and compatible with other programs" program. Any application data scientists using GO build will use the same language in other parts of the company, or at least it is well suited for modern architectures.

This year like dynamic plugins, serverless Go and HTTP/2 What these innovations mean for development

Go 1.8 has just been released and it has several new features, including:

1.HTTP/2 Push

2.HTTP Server Smooth Shutdown

3. Plugins

4. Default Gopath

The impact of these new features depends on how you and the development team use Go. Since Go 1.0 was released in 2012, its simplicity, concurrency, and built-in support have kept it growing, so the answer to what "Go is good for" has been growing.

Here I will provide some ideas, including the new arrivals and other places of the Go world that have attracted me recently. This is not an exhaustive list, so please let me know what you think will happen to Go in 2017.

Go Super deployable + plugin = container, anything?

Version 1.8 has been released, and I've talked to several of them. How adding a dynamic plug-in affects things like containers, a dynamic plug-in is a code that loads a shared library that is not part of a program at compile time. Dynamic plug-ins make it easier for high-concurrency microservices in containers. You can easily load the plugin as an external process, with all the benefits of microservices in the container: protecting your main process won't crash, and nothing will mess up your memory space. Dynamic support for plugins should be the Gospel of using containers in Go.

In the 7 years since Go Open source, it has been adopted worldwide. Daniel Whitenack, a data scientist and engineer who maintains the go kernel for Jupyter, tells me that he has recently done data science and go language training in Siberia, and is "surprised to see that the go community is so active and active." "Another big reason people continue to take go in a project is cross-compiling, and several go experts explained that it was easier in go 1.5. Developers from other languages, such as Python, should find that the ability to build bundled, deployable applications for multiple operating systems on a target platform without VMS is key to working in Go.

With cross-platform support in version 1.8, plus a 15% increase in compilation speed, you can see why Go is a startup's favorite language.

Go Interpreter in development

There are some smart guys working on a Go interpreter, and I'm sure I'll keep an eye on it. As you know, there are several read-eval-print-loop (REPL) solutions that can be used to evaluate expressions to ensure that the code works as you expect, but those methods often mean tolerating some inconvenience, or need to find a suitable use case for you from several scenarios. It's great to have a strong, consistent interpreter, and I'll let you know when I get more information.

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Go's serverless-what would it look like?

Yes, now there's a lot of hype around the serverless architecture (function as a service (FaaS)). But sometimes there are some unpredictable places, so what happens to the serverless of Go? Can we see a serverless service that is natively supported by the Go language this year?

AWS Lambda is the most well-known serverless provider, but Google Cloud Functions has recently been launched. These two FaaS solutions allow you to run code without having to manage the server, your code is stored on a server cluster that someone else manages for you, and only runs when the event is invoked. AWS Lambda currently supports JavaScript, Python, and Java, and can also launch Go, Ruby, and bash processes. Google Cloud Functions only supports JavaScript, but it is likely that Java and Python will soon be supported. Many IoT devices already use the serverless solution, and as go is increasingly being adopted by startups, serverless seems to be a potential growth point, so I'm looking at the development of go in these serverless solutions.

Supported Frameworks

There are already several frameworks that can support AWS Lambdas:

1.λgordon-Create, connect, and deploy AWS Lambdas with Cloudformation

2.Apex-Build, deploy, and manage AWS LAMBDA functions

3.sparta-aws the Go framework for LAMBDA MicroServices

There is also an AWS LAMBDA alternative that supports Go:

Iron.io: Built on Docker and Go; languages unknown; support for Golang, Python, Ruby, PHP, and. NET

Perhaps surprisingly, many people are using Go for data science and machine learning. There are some arguments about whether it is suitable, but based on an annual article like the 2016 end of the Gopher Academy, you will notice that at least 4 of the 30 articles are about machine learning or distributed data processing, and they are coming like us.

My previous view on Go's ease of deployment might be a key reason why data scientists use go: they can more easily show data models to others in applications that are readable and available for production environments. Combined with this is the extensive use of Go (as I mentioned earlier, it is becoming more and more popular!). , and there are data experts who create programs that are "available and fit with other programs." Any application data scientists using GO build will use the same language in other parts of the company, or at least it is well suited for modern architectures.

via:https://medium.com/@sconant/5-THINGS-TO-WATCH-IN-GO-PROGRAMMING-IN-2017-39CD7A7E58E3#.8T4TO5JR1

Author: Susan Conant Translator: GEEKPI proofreading: Jasminepeng

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