Tag Archives: Development

Streamlit launches open source machine learning application development framework





Streamlit, a new machine learning startup from industry veterans, who worked at GoogleX and Zoox, launched today with a $6 million seed investment and a flexible new open source tool to make it easier for machine learning engineers to create custom applications to interact with the data in their models. (TechCrunch)




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Swapnil Bhartiya has decades of experience covering emerging technologies and enterprise open source. His stories have appeared in a multitude of leading publications including CIO, InfoWorld, Network World, The New Stack, Linux Pro Magazine, ADMIN Magazine, HPE Insights, Raspberry Pi Geek Magazine, SweetCode, Linux For You, Electronics For You and more. He is also a science fiction writer and founder of TFiR.io.

XFS Gets Cleaned Up In Linux 5.3 Kernel Development Activity


LINUX STORAGE --

While not too eventful on the end-user feature front, the XFS file-system has seen another round of clean-ups with the ongoing Linux 5.3 merge window.

XFS maintainer Darrick Wong characterized the feature work for XFS in Linux 5.3 as “significant amounts of consolidations and cleanups in the log code; restructuring of the log to issue struct bios directly; new bulkstat ioctls to return v5 fs inode information (and fix all the padding problems of the old ioctl); the beginnings of multithreaded inode walks (e.g. quotacheck); and a reduction in memory usage in the online scrub code leading to reduced runtimes.

It’s not immediately exciting for end-users but hopefully will cleanup some open issues and the start of multi-threaded inode walks could help with performance along with the memory reduction work.

The complete list of Linux 5.3 XFS work can be found via this pull request.


Essential Hyperledger Composer tools and administrative, operational, and development commands | Linux.com


Hyperledger tools are very popular for building blockchain and decentralized applications. In particular, Hyperledger Fabric and Hyperledger Composer are the most widely used tools. Hyperledger Fabric Architecture and Components for Blockchain Developers and Installing Hyperledger Fabric on AWS articles are great resources for learning about Hyperledger Fabric. Once you learn about Hyperledger Fabric, you can move on to explore Hyperledger Composer.

Hyperledger Composer is a set of collaboration tools for business owners and developers that make it easy to write chaincode for Hyperledger Fabric and decentralized applications (DApps). With Composer, you can quickly build POC and deploy chaincode to the blockchain in a short amount of time. Hyperledger Composer consists of the following toolsets:

  • A modeling language called CTO: A domain modeling language that defines a business model, concept, and function for a business network definition
     
  • Playground: Rapid configuration, deployment, and testing of a business network
     
  • Command-line interface (CLI) tools: The client command-line tool is used to integrate business network with Hyperledger Fabric

Composer-CLI is the most important tool for Composer deployment; it contains all the essential command-line operations. Other very useful tools include Composer REST server, generator Hyperledger Composer, Yeoman, and Playground. Composer CLI provides many useful tools for developers.

Composer CLI can be used to perform multiple administrative, operational, and development tasks. Here is a summary of the CLI commands:

Command

Description

Examples

composer archive

<subcommand>

Composer archive command.

 

Composer archive list.

 

composer card

<subcommand>

Command for managing business

network cards.

Composer card list.

 

composer generator

<subcommand>

 

Composer generator command to

convert a business network

definition into code.

Composer generator

docs.

 

composer identity

<subcommand>

Composer identity command.

 

Composer identity

issue.

composer network

<subcommand>

Composer network command.

 

Composer network

install.

composer participant

<subcommand>

Composer participant command.

Composer participant

add.

composer report

 

 

Command for creating a report of

the current .Composer

environment

 

Composer report.

 

composer transaction

<subcommand>

Composer transaction command.

 

 

Composer transaction

submit.

The Composer REST server is used to generate a REST interface to a deployed blockchain business network.

Now that you know the essential tools and commands of Hyperledger Composer, the next is to follow this article: Hyperledger Composer Development Environment Requirements and Setup that gives you step-by-step guide for installing Hyperledger Composer development requirements as well as showing you how to configure a business network on Hyperledger Composer.

 


About Authors
This article is written by Matt Zand (Founder of High School  Technology Services) in collaboration with Brian Wu who is a senior blockchain instructor at Coding Bootcamps school in Virginia.

How Machine Learning Will Change Software Development | Linux.com


Artificial intelligence (AI) is not sci-fi anymore; machines have made their way into our lives with ever-increasing importance. Today, humans are teaching machines and machines already affect the way we live, make choices, and get entertained.

There are many ways we already use AI in our everyday lives:

* We ask our devices to perform simple searching tasks, play music, or send messages without touching them.

* We are overwhelmed with sometimes creepy suggestions of things we “want” to buy or lists of movies we will enjoy watching according to some smart algorithms.

* We’re already used to the idea of self-driving cars.

* And we can’t ignore the convenience of the new auto-fill and follow-up Gmail features.

Machine Learning on Code

As AI technology matures and the number of use cases grows, you would think that developers would already be using machine learning to automate some aspects of the software development lifecycle. However, Machine Learning on Code is actually a field of research that is just starting to materialize into enterprise products. One of the pioneers of movement is a company called source{d}, which is building a series of open source projects turning code into actionable data and training machine learning models to help developers respect technical guidelines.

With every company quickly becoming a software company, intangible assets such as code represent a larger share of their market value. Therefore companies should strive to understand their codebase through meaningful analytic reports to inform engineering decisions and develop a competitive advantage for the business.

On one hand, managers can use tools like the open source source{d} engine to easily retrieve and analyze all their Git repositories via a friendly SQL API. They can run it from any Unix system, and it will automatically parse their companies’ source code in a language-agnostic way to identify trends and measure progress made on key digital transformation initiatives.

For example, as an engineering manager, you can track the evolution of your software portfolio. You can easily see what programming languages, open source or proprietary frameworks are becoming more popular as part of your development process. With that extra visibility, it becomes a whole lot easier to decide who to hire and develop a set of company-wide best practices

On the other hand, developers can save an incredible chunk of time by training bots to review their code as they submit pull requests (PRs). Once enabled across a large set of repositories, this could automate part of the code review process and enable developers to ship secure and qualitative code faster than ever before.

At the moment it checks for common mistakes, makes sure the style and format of each commits is consistent with the existing code base or highlights hotspots that might need closer attention. That’s huge already and clearly can benefit not only developers but companies as well. Imagine how much time and resources you could save from delegating your code review to a bot capable of working 24/7.

Assisted or automated code review is not the only Machine Learning on Code use case. In the coming years, machine learning will be used to automate quality assurance and testing, as well as bug prediction or hardware performance. For now, you can try source{d} Lookout and install it on your repository. It will listen for PRs, run analyzers and comment results directly on GitHub.

This article was produced in partnership with Holberton School.

Tech Skills Employers Want Now: More Than Development


IT professionals always want to know which skills employers are looking for. They understand that the technology field is changing all the time, so they need to keep their abilities up to date if they want to remain marketable.

The online job posting sites don’t provide a complete picture of the IT job market, but they can provide interesting insight into which skills are trending up or down. Indeed.com recently provided Network Computing with two separate reports about hot IT job skills. The research illustrates how organizations look for different skills depending on whether they are writing job postings or are doing a resume search.

The list below ranks the skills that have recently appeared in job postings on Indeed.com. In other words, these are the capabilities that employers are requesting when they upload listings to the job board:

1. Java

2. Agile

3. JavaScript

4. .NET

5. HTML

6. Python

7. CSS

8. Amazon Web Services

9. C or C++

10. Git

(To compile this list, Indeed calculated the percentage of tech job postings which contain the above skills from October 2017 to April 2018 and ranked those skills in order by % of job postings in which they occur.)

So what do these skills have in common?

Almost all of them are development skills. Seven are programming languages, and Agile and Git are also related to development —   Agile because it is a development methodology and Git because it is a source code version control system. And while you could argue that IT infrastructure professionals might need to know JavaScript, .NET, or Python to do their jobs, really only one skill on that list — Amazon Web Services — is clearly related to infrastructure.

However, a second list Indeed provided to Network Computing told a slightly different story. The table below includes a rank of search terms typed into Indeed’s resume search engine. In other words, when employers go looking for someone to fill a role, these are the skills  they are looking for.

Rank

Search Term

# of resume searches per 1m total

1

Java developer

1,076

2

Java

812

3

UI developer

598

4

Software engineer

568

5

Network engineer

526

6

.net developer

514

7

.net

428

8

DevOps engineer

409

9

Web developer

387

10

Salesforce

377

 

For this list, Indeed calculated the share of searches (per 1 million total) per search phrase in its Resume search engine from November 2017 through January 2018

Clearly, development skills are still highly in demand, but network engineers, which weren’t represented on the other list at all, are way up in fifth place. And DevOps engineers, infrastructure professionals who are knowledgeable in DevOps approaches, came in eighth.

These lists only provide a brief snapshot of the tech job market at a given point in time. However, they do seem to indicate that for infrastructure professionals looking to improve their skills, classes in networking and DevOps might be the way to go.

And if you’re on a job search site and it seems like all the job postings are for developers and software engineers, don’t get discouraged. Even though they might not be placing as many ads for IT infrastructure pros, employers might still be looking for you.



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