Here are the Git commands which are being covered:
- git config
- git init
- git clone
- git add
- git commit
- git diff
- git reset
- git status
- git rm
- git log
- git show
- git tag
- git branch
- git checkout
- git merge
- git remote
- git push
- git pull
- git stash
Here are the Git commands which are being covered:
localStorage
only supports strings. Use JSON.stringify()
and JSON.parse()
.
var names = [];
names[0] = prompt("New member name?");
localStorage.setItem("names", JSON.stringify(names));
//...var storedNames = JSON.parse(localStorage.getItem("names"));
You can also use direct access to set/get item:
localstorage.names = JSON.stringify(names);
var storedNames = JSON.parse(localStorage.names);
Demo URl
https://stackblitz.com/edit/js-k29afs?file=index.js
Fig.1 |
Step 1: Open CMD command prom and Type sudo su
Step 2 : sudo chmod a+rwx root directory name you want to give permission file
Top Best Web Application Framework is a software framework that you Can Design Best Web Application, Website Which can help you for Your related your business Below you can Top Web Application!
Angular is a TypeScript-based open-source front-end platform that makes it easy to build applications with in web/mobile/desktop. The major features of this framework such as declarative templates, dependency injection, end to end tooling, and many more other features are used to ease the development.
Ruby on Rails, or Rails, is a server-side web application framework Ruby on Rails is an extremely productive web application framework written by David Heinemeier Hansson. One can develop an application at least ten times faster with Rails than a typical Java framework. Moreover, Rails includes everything needed to create a database-driven web application, using the Model-View-Controller pattern.
Websites using Ruby on Rails are GroupOn, UrbanDictionary, AirBnb, Shopify, Github
Django is a Python-based free and open-source web framework that follows the model–template–views architectural pattern. Django is another framework that helps in building quality web applications. It was invented to meet fast-moving newsroom deadlines while satisfying the tough requirements of experienced Web developers. Django developers say the applications are it’s ridiculously fast, secure, scalable, and versatile.
Websites using Django are Disqus, Pinterest, Instagram, Quora, etc.
Websites using Angular are Youtube on PS3, Weather, Netflix, etc.
ASP.NET is a framework developed by Microsoft, which helps us to build robust web applications for PC, as well as mobile devices. It is a high performance and lightweight framework for building Web Applications using .NET. All in all, a framework with Power, Productivity, and Speed.
Websites using ASP.NET are GettyImages, TacoBell, StackOverflow, etc.
Meteor or MeteorJS is another framework that gives one a radically simpler way to build realtime mobile and web apps. Meter is an open source framework for seamlessly building and deploying Web, Mobile, and Desktop Application in JavaScript. It allows for rapid prototyping and produces cross-platform (Web, Android, iOS) code. Its cloud platform, Galaxy, greatly simplifies deployment, scaling, and monitoring.
Websites using Meteor are HaggleMate, WishPool, Telescope, etc.
Websites using Laravel are Deltanet Travel, Neighbourhood Lender, etc.
Express or Expressjs is a minimal and flexible framework that provides a robust set of features for web and mobile applications. It is relatively minimal meaning many features are available as plugins. Express facilitates the rapid development of Node.js based Web applications. Express is also one major component of the MEAN software bundle.
Websites using Express are Storify, Myspace, LearnBoost, etc.
Spring, developed by Pivotal Software, is the most popular application development framework for enterprise Java. Myriads of developers around the globe use Spring to create high performance and robust Web apps. Spring helps in creating simple, portable, fast, and flexible JVM-based systems and applications The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Websites using spring are Mascus, Allocine, etc.
Play is one of the modern web application framework written in Java and Scala. It follows the MVC architecture and aims to optimize developer productivity by using convention over configuration, hot code reloading, and display of errors in the browser. Play quotes itself as “The High-Velocity Web Framework”.
Websites using PLAY are LinkedIn, Coursera, LendUp, etc.
CodeIgniter, developed by EllisLab, is a famous web application framework to build dynamic websites.CodeIgniter is an open-source software rapid development web framework, for use in building dynamic web sites with PHP..
Websites using CodeIgnitor are Bufferapp, The Mail and Guardian, etc. Apart from these 10 frameworks, others like Symphony , Ember.js, Sails.js, React.js are also worth mentioning.
In most cases you will want to use {static: false}
. Setting it like this will ensure query matches that are dependent on binding resolution (like structural directives *ngIf, etc...
) will be found.
Example of when to use static: false
:
@Component({
template: `
<div *ngIf="showMe" #viewMe>Am I here?</div>
<button (click)="showMe = !showMe"></button>
`
})
export class ExampleComponent {
@ViewChild('viewMe', { static: false })
viewMe?: ElementRef<HTMLElement>;
showMe = false;
}
The static: false
is going to be the default fallback behaviour in Angular 9. Read more here and here
The { static: true }
option was introduced to support creating embedded views on the fly. When you are creating a view dynamically and want to acces the TemplateRef
, you won't be able to do so in ngAfterViewInit
as it will cause a ExpressionHasChangedAfterChecked
error. Setting the static flag to true will create your view in ngOnInit.
Here is Stack overflow link https://stackoverflow.com/questions/56359504/how-should-i-use-the-new-static-option-for-viewchild-in-angular-8
So in the list of the highest paying tech jobs, you would have definitely heard about this one - becoming a product manager. A product manager helps to determine parameters around the product and engineering team builds, then leads the development of that product from conception to launch. Some of the skills required for a product manager are:
Product managers are responsible for delivering an operating plan that can help achieve strategic and tactical goals and objectives, building a product portfolio, managing and implementing marketing activities, and contributing to the product strategy and its vision.
The average yearly salary of a product manager is over $100,000.
An Artificial Intelligence (AI) architect develops, manages and oversees AI initiatives within an organization. An AI architect should have deep knowledge in mathematics and statistics. In addition, an AI architect will:
The average yearly salary of an AI architect earns over $110,000.However, you will find various highest paying jobs within the AI domain too. Give it a thorough read here!
Today, there are over 23 million developers globally, and by 2023 it would reach 27.7 million - definitely making it one of the highest-paid tech jobs in the industry! It is difficult to pin down a definition for a full stack developer, but the closest description would be someone who is well-versed in both front-end and back-end development or someone with skills in every stage of development from concept to end product.
Some of the knowledge and skills to become a pro full stack developer is:
A full stack developer might be responsible for designing and building APIs using MEAN stack technologies, ensuring the applications created are responsive and keep to the required standards, making sure the created code has integrity intact, and implementing data security.
The average yearly salary of a full stack developer is $106,000.
Next in the list of highest paying jobs is cloud architect. A cloud architect deploys and oversees an organization’s cloud computing strategy. Some of the skills and knowledge required by a cloud architect include:
A cloud architect typically is responsible for developing cloud architecture, developing a cloud strategy and coordinating the implementation and deployment of it, and ensuring application architecture and deployments in the cloud environment are done properly.
The average yearly salary of a cloud architect is $107,000. However, within the cloud computing field too you will find various job roles and responsibilities, that pay handsome salaries, and you can find about cloud highest paying jobs here!
Next in the list of best paying jobs in technology is a DevOps engineer. It could refer to someone on the development team taking part in the deployment and network operations, or to someone from the operations team working on application development. Some of the skills required of a DevOps engineer include: Coding and scriptingUnderstanding deployment and network operations familiarity with DevOpsDevOps tools like Git and Jenkins Knowledge of Linux or Unix system administration DevOps engineer might be responsible for designing and maintaining a deployment infrastructure, integrating cloud services so that processes can be automated, or shell scripting in PHP/Python and Ruby.The average yearly salary of a DevOps engineer ranges from $95,000 to $140,000.
A blockchain engineer specializes in developing and implementing architecture and solutions using blockchain technology. The worldwide spending on blockchain solutions is expected to reach 15.9 billion by 2023, meaning there will be plenty of demand for blockchain experts, across industries and geographies.
From a birds eye view a blockchain engineer should have solid programming skills and a thorough understanding of the technologies behind Ripple, R3, Ethereum and Bitcoin as well as consensus methodologies and the security protocol stacks, crypto libraries and functions.
The average yearly salary of a blockchain engineer is over $150,000. You can also download the blockchain engineer career guide to know the learning path, top skills and ways to build a successful career in this field, and also get an in-depth understanding of why it is referred as one of the highest paying jobs. Get the guide now.
A software architect optimizes the development process by making design choices and dictating technical standards such as coding, tools and platforms. As part of their role, they identify a customer’s requirements and perform hands-on work to develop prototypes.
Some of the skills required of a software architect include:
The average yearly salary of a software architect is over $114,000. In India, the demand of software architects is at an all time high, and the salaries can range from 24 Lakhs to over 40 Lakhs Rupees annually.
Internet users generate about 2.5 quintillion bytes of data each day. To harness and gain insights from such a huge amount of data, over 97 percent of organizations are investing in Big Data and AI.
Clearly, the next in the list of the highest paying tech jobs is Big Data architect. A Big Data architect plans, designs and manages the entire lifecycle of large-scale developments and deployments of Big Data applications. Some of the skills required of a Big Data architect include:
The average yearly salary of a Big Data architect is $140,000.
One of the most-in demand and best paying jobs in technology today is an IoT solutions architect. The IoT solutions architect is a leadership role of overseeing the strategy behind the development and deployment of IoT solutions. In addition to understanding IoT solutions, one should also have strong programming skills, an understanding of Machine Learning, and knowledge of hardware design and architecture.
An IoT solutions architect is responsible for leading as well as participating in the activities around architecture and design, helping to develop an overall IoT ecosystem engagement based on the IoT Solution Framework, and translating business needs into solution architecture requirements.
And in this highest paying tech job you can earn an average of over $130,000 annually.
A data scientist, without a pinch of doubt, is the highest paying jobs across industries and sectors. There has been a 29 percent increase in demand for data scientists year over year and a dramatic upswing of 344% increase since 2013, and for all the right reasons. A data scientist analyzes and interprets complex data to help organizations make better and more timely decisions. A data scientist should be able to:
The yearly salary of a data scientist can be as high as $150,000, making it the highest paying job role of 2021. However, data science as a field itself, offers various opportunities and salary potential. For instance, data analysts and data architects too are some of the most in demand job roles that are the highest paid tech jobs within the data domain.
Python is a high-level, interpreted, general-purpose programming language that supports both object-oriented programming and structured programming. It is quite versatile and offers a lot of functionalities using standard libraries which allows the easy implementation of complex applications.
This is the single, biggest reason why many programmers are learning Python in 2021. I know many of my friends who are bored with their Java programming jobs in investment banks and are learning Python on Udemy to make a career in data science due to the exciting work and high pay.
But, what makes Python a preferred language for data science and machine learning? Wasn't R considered the best for that not too long ago? Well, I think the libraries and frameworks Python offers, e.g. PyBrain, NumPy, and PyMySQL are one of the big reasons. Another reason is diversity. Python experience allows you to do a lot more than R, e.g. you can create scripts to automate stuff, go into web development, and so much more. If you are interested in becoming a Data Scientist in 2019 and looking for pointers, I suggest you check out the Data Science, Deep Learning, & Machine Learning with Python course on Udemy. I have purchased this course and it’s an awesome resource. You can get it for less than $10 sometimes.
This is another reason why programmers are learning Python in 2019. The growth of machine learning in last a couple of years has been phenomenal and it’s rapidly changing everything around us.
Algorithms become more sophisticated every day, the best example being Google’s search algorithms, which can now answer what you are expecting. There are chatbots around to answer your queries and Uber is totally driven by algorithms.
If you are interested in machine learning, and want a pet project or just want to play around it, Python is the only major programming languages which makes it easy.
Though there are machine learning libraries available in Java, you will find more content around Python as the developer community currently preferes Python over anything else for data science and machine learning.
If you are interested in doing web development with Python, I suggest you to further check out the Machine Learning A-Z™: Hands-On Python & R In Data Science course on Udemy.
Good old development is another reason for learning Python. It offers so many good libraries and frameworks, e.g. Django and Flask, which make web development really easy.
A task which takes hours in PHP can be completed in minutes with Python. Python is also used a lot for web scrapping. Some of popular websites on the Internet, like Reddit, are built using Python.
If you are interested in web development using Python I suggest you join the Python and Django Full Stack Web Developer Bootcamp course by Josh Portilla.
This is the single biggest reason for beginners to learn Python. When you first start with programming and coding, you don’t want to start with a programming language which has tough syntax and weird rules.
Python is both readable and simple. It's also easy to setup; you don’t need to deal with any classpath problems like Java or compiler issues like C++.
Just install Python and you are done. During installation, it will also ask you to add Python to the PATH, which means you can run Python from anywhere on your machine.
You need a community to learn a new technology and friends are your biggest asset when it comes to learning a programming language.
Thanks to Google, you can find the solution to any Python related problem in minutes. Communities like StackOverflow also bring many Python experts together to help newcomers.
One of the similarities between Python and Java is the sheer number of open source libraries, frameworks, and modules available to do whatever you want to do. It makes application development really easy.
Just imagine creating a web application without Spring in Java or Django and Flask in Python. It makes your job easier so you can focus on business logic.
Python has numerous libraries for different needs. Django and Flask are two of the most popular for web development and NumPy and SciPy are very popular for data science.
In fact, Python has one of the best collections of machine learning and data science libraries, including TensorFlow, Scikit-Learn, Keras, Pandas and many more.
If you want to learn more about Python machine learning libraries, I suggest you to join the Python for Data Science and Machine Learning Bootcamp course, one of my favorite.
When I first learned about Python, it was due to one of my scripting needs. I was working with an application which received messages over UDP and there was a problem: we were not seeing messages in the log.
I wanted to check if we were receiving any UDP traffic on that box and that port or not but I couldn’t find a handy Unix command to do that.
One of my friends, who sits next to me, was learning Python and he wrote a utility in just 5 minutes to intercept UDP messages using one a Python module.
Obviously, I was impressed with the time it took for him to write such a tool; but that just highlights the power of Python when it comes to writing scripts, tools, and automating stuff.
If you seriously want to know how much Python can help with automation, my favorite place is the Automate boring stuff with Python book, simply awesome book.
One of the things I like about Python is its Swiss Army knife-like nature. It’s not tied to just one discpline, like how R is just for data science and machine learning. Learning Python means you can do many things.
You can create your web applications using Django and Flask. You can do data analysis using NumPy, SciPy, Scikit-Learn, and NLTK.
At a bare minimum, you can use Python to write scripts to automate many of your day to day tasks.
Python is growing really fast and it makes a lot of sense to learn a growing programming language if you are just starting your programming career.
It not only helps you to get a job quickly but it will also accelerate your career growth. In my opinion, for beginners, after simplicity, this should be the most important reason to learn Python.
Python developers are some of the highest paid developers, particularly in the fields of data science, machine learning, and web development.
Average salaries from $70,000 USD to $150,000 USD, depending upon experience, location, and area of speciality.
If you are interested in learning more about high paying technology jobs, I suggest checking my earlier post about 10 highest paid technology jobs for Software Engineers in 2018.
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