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JavaScript is a lightweight, object-oriented scripting language that is used to produce dynamic HTML pages with captivating effects. While JavaScript programming, which runs in the V8 engine or through the node interpreter, has access to a list of objects and methods through the use of Node.js.

Startups are always willing to experiment with new technologies, so every novel technology initially picks up steam and garners attention. However, it is clear that large, well-established companies are switching from years of legacy systems to Node.js. Every few months, a new “game-changing” technology enters the IT market, but they quickly become obsolete, according to developers. This is not the case with Node.js. This is unusual, so let’s examine how Node.js functions and the benefits of implementing this cutting-edge technology in businesses to gain a better understanding.

What Is Node.js?

The simplest way to define Node.js is as a runtime environment for JavaScript that aids in the implementation of JavaScript programming on the server side. It is a precise, cross-platform, open-source JavaScript that facilitates the creation of real-time network applications.

Numerous modules are included with Node.js, which is primarily used for web-based development. It allows for event-driven, non-blocking (asynchronous), and scalable I/O for server-side JavaScript applications. It can run on different operating systems, including Windows, Mac OS, and Linux.

Node.js can be used to create a variety of applications, including REST API servers, command-line programs, and real-time chat programs.

Let’s see some beneficial keypoints of Node.js

Simplicity

Most front-end developers are proficient in JavaScript, which is a widely used programming language. They find it much easier to use Node.js in the backend. Node.js is simple to learn and uses less time when used professionally.

With Node.js, it is easy to share a single language between the client and server sides without switching between the front-end and back-end. The deployment and the code are both in the same location. As a result, when compared to apps that use different languages for both ends, those made in Node.js require fewer files and less code. Even better, sharing and reuse of the code speeds up the development process.

This significant help is especially appreciated at this early stage of your product development. For both sides, you can have a full-stack development team to cut down on resource or hourly costs.

More rapid time to market

Time is a valuable resource for businesses of all sizes, including startups. Startups in particular must be persistent in their efforts to iterate quickly, support testing and deployment, and deliver as quickly as possible while working with smaller budgets.

The main benefit of Node.js is that it helps shorten the time to market. With Node, you can quickly move from the project’s conceptual stage to its finished product. Additionally, simple deployments help you get immediate feedback directly from the production environment.

This scenario is conceivable because the technology is reasonably portable and can significantly shorten the time required to develop an app while maintaining the same features and functionalities.

Large-scale Solutions

Scalability is one of Node’s benefits for both business and development that intend to develop over time. It is used to create compact, quick solutions with improved real-time response that can be scaled up further and allow the addition of new modules to the existing ones.

Load balancing and the ability to handle a large number of concurrent connections enable Node to scale. Additionally, Node’s applications support both vertical and horizontal project scaling.

Because Node.js is explicitly designed for microservices architecture, it is advantageous when creating projects that will grow and scale in the future. Additionally, it is possible to create a separate microservice and scale it covertly for any features and functionalities.

Development & Active Community

It is worthwhile to quickly confirm the viability of the product’s concept with less effort, resources, and upfront investments because project timelines are shorter and project budgets are more constrained. By using this scenario, the product’s viability can be confirmed before investing time and money in its full development. Node.js makes it possible to quickly create an MVP (Minimum Viable Product), a software solution with just enough features to satisfy the product’s target market. The MVP stage is the first step in the process of developing a complete app.

At the same time it has a sizable and extremely active community of programmers who never stop adding to its growth and improvement.

Developers of JavaScript support the programming teams by providing simpler solutions and codes. It is anticipated that many more programmers will be initiated and supported in the future by today’s programmers.

Performance & Extensions

Through Google’s V8 JavaScript engine, Node.js infers the JavaScript code. The JavaScript code is directly converted by the engine into machine code. The code can be efficiently executed faster and easier in this scenario.

Even faster code execution is achieved with an explicit runtime environment because it supports non-blocking I/O operations.

Another interesting thing about Node.js is it’s highly extensible. Because Node.js is so extensible, you can easily adapt it to your needs and add new features. Additionally, it is equipped with built-in APIs for creating HTTP, TCP, and DNS servers. JSON can even be used to provide a means of information exchange between a web server and its users.

Future Prospects for Node.js

Node JS appears to be a significant trend that will continue to grow in 2022. It offers some undeniable benefits that make it the preferred option for developers.

Node JS technology in the front-end industry appears to have a bright future because, at least for the time being, it appears that no front-end upgrade is possible without Node.js.

Node.js encourages users to create everything from microservices to enable the delivery of multipurpose applications. Additionally, it helps synchronize non-web frameworks so they can use serverless structures.

Tags: JavaScript, node.js

Python is an interpreted, high-level object-oriented programming language. It comes with built-in data structures, dynamic typing(a process wherein type checks are done during the runtime), and binding(mapping of different objects with one another), which makes it a top language used for the development of applications. Python syntaxes are simple, easy to read, and easy to learn.

R is a programming language for statistical analysis or computing and graphics. R comes with a wide range of statistical techniques such as linear modeling, non-linear modeling, statistical tests, clustering, etc. One of R’s strengths is the ease at which a plot can be produced, including the mathematical notations and formulas.

R and Python are both excellent choices for data science, but each has advantages and disadvantages. Accordingly, if you’re new to data science, one option may be more appropriate than the other, and if you already know one, learning the other may still be worthwhile.

There is no question that Python and R can handle the majority of data science tasks; however, there are other considerations that may influence your decision. One tool might be more useful for a particular task, might be simpler to learn for some users than for others, might lead to more opportunities in the workforce, and the list goes on.

Making the right decision is important because learning something new is challenging. Before you start learning Python and/or R for data science, you should be aware of the following.

Which background you’re from?

Consider your background when selecting between Python and R if you’re new to data science. Learning a new programming language like Python or R wouldn’t be challenging if you have years of coding experience, but things are different if you have only recently used programs like Excel or SPSS. Let’s examine who makes use of Python and R, as well as their purposes.

The programming language R, which was developed by statisticians, is primarily employed for statistical computing. Nevertheless, R is used by more than just statisticians; it is also employed by data miners, bioinformaticians, and other experts who perform data analysis and create statistical software.

On the other hand, Python is a general-purpose language that is used for creating GUIs, games, websites, and other things in addition to data science. Python is used for a wide range of tasks by experts like software engineers, web developers, data analysts, and business analysts.

In conclusion, R would probably be simpler to learn if you’re coming from Excel, SAS, or SPSS, but Python would be simpler to use and get used to if you’ve been coding in other programming languages for a while and have a programming mindset.

Which one is more popular for data science?

Before learning a tool, it’s important to keep its popularity in mind. You don’t want to learn anything that has no practical application, I assure you.

On Google Trends, a quick comparison of the keywords “python data science” (blue) and “r data science” (red) reveals the growth in popularity of both programming languages over the previous five years.

Without a doubt, Python is more widely used for data science than R.

Employers, however, look for different things in Python and R experts when it comes to data science. The most prevalent data science tools and techniques that appear in each set of job postings were identified through a comparison of job postings that contain the terms data science and R (but not python) and data science and Python (but not R).

The wordcloud reveals that while job postings with the terms data science and Python include “machine learning,” “SQL,” “research,” and tools like AWS and Spark, those with the terms data science and R frequently include terms like “research,” “SQL,” and “statistics.”

Which one offers the best tools for data science?

The workflow for data science includes activities like data collection, exploration, and visualization. Despite the fact that both Python and R will do the job, each language’s tools and package offerings have advantages and disadvantages.

Data Collection: R and Python both support a wide range of file formats, including CSV and JSON, and R also enables you to convert files created in Minitab or SPSS into datasets. Both platforms also let you use website data extraction to create your own datasets, but Python has more sophisticated tools like Selenium and full frameworks like Scrapy.

Data Exploration: Take a look at the packages used in both R and Python because this is the step where data scientists spend the majority of their time. While R has a variety of packages designed for data exploration, we typically use Pandas and Numpy to explore datasets in Python. Since a picture speaks a thousand words, check out these straightforward exploratory data analyses carried out in R and Python to learn more about the tools employed.

Data Visualization: Basic graphs can be created in Python using the Pandas library, but for customizable and sophisticated visualizations, you must learn libraries like Matplotlib and Seaborn. The issue is that Python visualizations aren’t the most aesthetically pleasing and can be challenging to learn (and remember their syntax for). R excels at data visualization, in contrast. Many common graphs are already supported by R by default, and it also offers sophisticated tools like ggplot2 to enhance the look and feel of your graphs.

Wrapping Up

You already likely know which tool is best for you at this point, but allow me to share what some of the people I know do.

Some people favor Python over R because of its versatility and flexibility, which enable them to perform powerful data science tasks as well as go beyond them, while others prefer Python over R because of its statistics-oriented strength and excellent visualization capabilities.

For the various job opportunities and tools they offer, learning the other would be worthwhile even if you already know one.

Tags: Python, Python vs r, R

Flutter is a free and open-source mobile UI framework created by Google and released in May. In a few words, it allows you to create a native mobile application with only one codebase. This means that you can use one programming language and one codebase to create two different apps (for iOS and Android).I began as a front-end web developer before switching to Flutter development.

I believe there were some ideas that made it simpler for me to adopt Flutter. Additionally, there were some novel ideas that were unique.

In this article, I want to share my experience and encourage anyone who is having trouble deciding between two ecosystems by demonstrating how concepts can be learned and how they can transfer between ecosystems.

Ideas That Were Transferred

This section highlights similarities between Flutter and front-end web development. It explains the abilities you already possess that will help you if you begin using Flutter.

Implementing User Interfaces (UIs)

You put together HTML elements and give them CSS styling in order to implement a specific UI in front-end web. In Flutter, you create widgets and give them properties to give them UIs.

The Color class in Dart uses “rgba” and “hex,” just like CSS. Like CSS, Flutter measures space and size in pixels. For almost all CSS properties and their values, Flutter provides Dart classes and enums. There are also Column and Row widgets in Flutter. These are display:Flutter flex’s equivalents in CSS. Use the MainAxisAlignment and CrossAxisAlignment properties to set the justify-content and align-items styles. Wrap the affected child widget(s) of the Column/Row in an Expanded or Flexible to change the flex-grow style.

Flutter has a class called CustomPaint that is equivalent to the Canvas API in web development for more complex user interfaces. With CustomPaint, you can use a painter to create any UI you like. CustomPaint is typically used when you need something extremely complex. Additionally, when a widget combination fails, CustomPaint is the preferred option.

Multiple Screen Resolutions Development

Mobile apps run on devices, while websites run on browsers. As a result, you must keep the platform in mind when creating for either platform. The same features (camera, location, notifications, etc.) are implemented differently by each platform.

The responsiveness of your website is something you as a web developer consider. You manage how your website appears on larger and smaller screens by using media queries.

You have the MediaQuery helper class if you are moving over from mobile web development to Flutter. You can get the current device orientation from the MediaQuery class (landscape or portrait). It also provides you with other device information, such as the devicePixelRatio and the current viewport size. You can learn more about the configuration of the mobile device by combining these values. You can use them to alter the appearance of your mobile app across a range of screen sizes.

Working with Debuggers, Editors, and Command Line Tools

There are developer tools in desktop browsers. An inspector, a console, a network monitor, etc. are some of these tools. The web development process is enhanced by these tools. The same is true for Flutter’s DevTools. Among other features, it has a widget inspector, debugger, and network monitor.

Similar IDE support is available. One of the most well-liked IDEs for web development is Visual Studio Code. For VS Code, there are numerous web-related extensions. VS Code is supported by Flutter too. So you don’t need to switch to another IDE while transitioning. For VS Code, there are extensions for Dart and Flutter. Also compatible with Android Studio is Flutter. Flutter DevTools are supported by both VS Code and Android Studio. The Flutter tooling is finished thanks to these IDE integrations.

The majority of JavaScript front-end frameworks include a command-line interface (CLI). Angular CLI, Create React App, Vue CLI, etc. are a few examples. Additionally, Flutter includes a unique CLI. You can build, create, and develop Angular projects using the Flutter CLI. For analyzing and testing Flutter projects, it has commands.

Additional Thoughts On Flutter

A cross-platform tool for creating desktop, mobile, or web applications is called Flutter. Flutter apps have perfect pixelation. No matter the target platform, Flutter uses the same user interface (UI) for all apps. This is so because the Flutter engine is present in every Flutter app. The Flutter UI code is rendered by this engine. Each device has a canvas that you can paint on thanks to Flutter. For the purpose of handling events and interactions, the engine communicates with the target platform.

Flutter works well. It performs at a high level. This is due to the fact that it was created using Dart and makes use of its features.

Flutter is a wise choice for many applications thanks to its many advantages. Cross-platform apps reduce costs and time spent on development and upkeep. Flutter (and cross-platform solutions) might not always be the best option, though.

If you want users to use platform developer tools with your application, avoid using Flutter. Device-specific tools, such as Android developer options, are referred to as platform developer tools here. Developer tools for browsers are also included. If you want browser extensions to communicate with the website, don’t use Flutter for web. Flutter should not be used for websites with a lot of content.

Conclusion

This article reviewed the transferable skills from front-end web development to using Flutter. We also covered key ideas in app development that web developers must understand.

For web developers, Flutter is easier to use because both involve implementing UIs. Starting with Flutter will show you that it offers a positive developer experience. Try out Flutter! Utilize it to create mobile applications, and of course, show off what you create.

Tags: Flutter, web development

After the popularity of its predecessor, Angular 13, Angular 14 is now available. The following notable Google release is the web application framework built on Type-script. With the introduction of stand-alone components, Angular 14 promises to speed up the creation of Angular apps by eliminating the requirement for Angular modules. Improved template diagnosis, stand-alone components, and additional capabilities for typed forms are all brought about by the move from Angular 13 to Angular 14.

The most meticulously thought out pre-planned upgrade by Angular is thought to be version 14. CLI auto-completion, typed reactive forms, standalone components, directives and pipes, and improved template diagnostics are some of the new features in the Angular 14 version.

The Angular team’s deliberate elimination of the requirement for Ng modules, which lowers the amount of boilerplate code needed to launch the application, is the update’s standout feature. Let’s compare Angular13 with the latest Angular14 release before going over the features of Angular14.

In contrast to Angular14

The Angular and Typescript developers found the framework challenging compared to others like React after Angular 13 was released. Additionally, the new Route.title function in the Angular router made adding titles easier in version 13. When adding a title to your page in Angular 14, this is not necessary to be added for any new imports.

Independent Components

Although the Angular 14 modules are optional, the objective is to depart from the current configuration by constructing pipes, directives, and components.

Angular has released RFC to make Ng modules optional on standalone components (Request for Comments). While the Angular 14 update will not make these modules outdated, it will make them temporary in order to maintain compatibility with the current Angular libraries and apps.

It is important to note that before to Angular 14, each component had to be related to a module. If a parent module’s declarations array is not linked with each component, the application will crash.

Completely Typed Forms

Executing strict typing for the Angular reactive forms package is totally fixed by the latest Angular version release. The precisely typed forms will improve a contemporary-driven strategy for Angular to work invisibly with the current forms.

The ease with which users can switch from earlier versions to version 14 is one of the most encouraging features of Angular 14. To retain the current applications while upgrading, the Angular team has included auto migration. Additionally, FormControl, which invokes a specific value it carries and accepts generic type input, is now available for use.

To guarantee that the changes are handled precisely and smoothly, the complexity of the API is often monitored. Additionally, the most recent Angular 14 version won’t interfere with template-based forms.

CLI Auto-Completion for Angular

The Angular CLI auto-biggest completion’s feature is that it helps you become more productive by providing the necessary commands to create modules, directives, and components for your new or current project. The Angular 14 includes several useful commands for you, though.

You don’t have to bother about searching the internet for commands. Here is how to use Angular 14 to accomplish it.

The newest CLI features are delivered by Angular 14, enabling real-time auto-completion in the terminal. You should initially run the ng completion command. The ng command must now be entered, followed by the Tab key to investigate all available options. Enter to select a choice from the list.

Additionally, the ng create command options list offers extra auto-completion options if you are using the most recent version of Angular 14, which is available.

Enhancements to Template Diagnostics

Improved template diagnostics are included in the latest Angular 14 upgrade to protect developers from generic errors through compiler reconciliation to typescript code.

The compiler does not produce any warnings in Angular 13 or earlier versions, and it stops executing if a problem prevents it from doing so.

Some of the potential red flags may stem from more fundamental problems, such as the usage of undesired operators when a variable is not nullable or the syntax for two-way binding. A new private compiler that displays alerts or information diagnostics for user templates also limits the scope of the diagnostic tests.

Accessibility of the Page Title Streamlined

When developing an application, your page title typically clearly displays the contents of your page. The entire process of adding titles was previously coordinated with the new Route.title parameter in the Angular router in version 13. But Angular 14 doesn’t offer the extra imports needed when adding a title to your page.

Internal Improvements

The fact that the Angular14 update allows the CLI to publish little code without lowering its value is one of the version’s most intriguing features. You may connect to protected component members directly from your templates thanks to the built-in improvements. Overall, leveraging the public API surface gives you more control over the reusable parts.

Wrapping Up

That concludes our discussion of the key elements of Angular14’s new features. I’m hoping that this may be useful to you as you work on your current or next Angular14 project.

With Angular14, creating apps is now simple and rapid. Thanks to the stand-alone components, using ng modules is not required. The Angular developer community aims to support web developers in getting improved versions of the Typescript-based framework while also enabling them to keep up with the demands of other online ecosystems and users.

We advise switching to Angular14 if you are familiar with the most recent Angular improvements and features.

Tags: angular, angular 14

Data scientists, data engineers, and application developers now have better programmability thanks to new updates from Snowflake, a provider of data clouds.

This week at its yearly user conference, Snowflake Summit 2022, in Las Vegas, the company made the update public.

With the release of Snowpark for Python, which is currently in public preview, and a native integration with Streamlit for quick application development and iteration, both of which are currently under development, Snowflake’s most recent innovations put Python in the spotlight. Along with making data stored in open formats and on-premises accessible in the Data Cloud, Snowflake is also streamlining access to more data with new improvements for working with streaming data.

These improvements make it simpler for data professionals and developers to build and collaborate with data quickly while utilizing Snowflake’s platform’s speed, simplicity, consistent governance, and security.

Increasing Python’s Use in Machine Learning and Application Development

These improvements make it simpler for data professionals and developers to build and collaborate with data quickly while utilizing Snowflake’s platform’s speed, simplicity, consistent governance, and security.

Data scientists, data engineers, and application developers now have access to a rich programming environment with Snowpark, the developer framework for Snowflake, allowing them to create scalable pipelines, applications, and machine learning (ML) workflows directly within Snowflake using their preferred languages and libraries. By facilitating seamless access to Python’s rich ecosystem of open-source packages and libraries in the Data Cloud, Snowflake is expanding what users can create with Snowpark for Python.

Snowpark for Python runs on the same Snowflake compute infrastructure as Snowflake pipelines and applications written in other languages thanks to a highly secure Python sandbox. As a result, developers can expect the same scalability, elasticity, security, and compliance benefits from Snowpark for Python as they have come to expect from Snowflake. Developers now have the exceptional chance to consolidate their Python-based data processing in Snowflake using Snowpark, streamlining and modernizing their data processing architecture.

Along with Snowpark for Python, other updates include:

• With the help of Python and Snowpark’s DataFrame APIs for Python, users can create pipelines, machine learning models, and applications directly in Snowsight, the Snowflake user interface. Development is sped up by code auto-complete and the quick productization of custom logic.
• With the help of Snowflake’s Streamlit Integration, which is still under development, users will be able to build interactive applications, securely share them with business teams to iterate, and work together to increase the impact of development.
• The currently under development Large Memory Warehouses gives users the ability to safely carry out memory-intensive operations, like feature engineering and model training on sizable datasets, using well-liked Python open-source libraries accessible through the Anaconda integration.
• SQL Machine Learning gives SQL users the ability to incorporate ML-powered predictions into their routine business intelligence and analytics to increase decision quality and speed, starting with time-series forecasting, which is currently in private preview.

Python is a well-liked choice among developers due to its robust syntax and extensive ecosystem of open-source packages. Thanks to Snowflake’s ongoing partnership with Anaconda, more Python packages are now seamlessly accessible in Snowflake, and all code is run in a highly secure sandboxed environment. As a result of Snowflake’s Python developments, the Snowpark Accelerated program has also continued to expand, with more partners using Python to increase the Data Cloud’s functionality in their preferred language.

In order to support machine learning (ML) and artificial intelligence (AI) solutions that make use of data in the Allegis Enterprise Data Platform on Snowflake, Allegis Group, a global talent solutions company, depends on Snowpark.

Joe Nolte, AI & MDM Architect, Allegis Group, said: “At its core, Snowpark is all about extensibility, and Snowpark for Python provides us with the tools we need to work with data effectively in our programming language of choice.”

“Snowpark is becoming our preferred framework for data science and application development, providing our teams with a seamless experience to easily collaborate with data and bring everyone onto the same platform for accelerated time-to-value.”

For developers to work more productively, to create more accurate ML models, and to offer more potent applications, they need quick and easy access to the right data. The upgrades to Snowflake let teams to experiment more quickly and with access to more data, resulting in improved programming capabilities and more insightful user experiences.

New innovations include:

• With Snowpipe Streaming, which is currently in private preview and allows for the serverless ingestion of streaming data, and Materialized Tables, which are currently under development and make declarative transformation of streaming data simple, Streaming Data Support aims to do away with the distinctions between streaming and batch pipelines.
• The currently under development Iceberg Tables in Snowflake, which will allow users to work with Apache Iceberg, a well-liked open table format, in external storage while utilizing the platform’s simplicity, performance, and consistent governance. This will streamline overall data management and increase architectural flexibility.
• With Snowflake’s External Tables for On-Premises Storage, customers can access their data in on-premises storage systems like Dell Technologies, Pure Storage, and others to take use of the Data Cloud’s elasticity without relocating that data. This feature is currently in private preview.

Christian Kleinerman, senior VP of product, Snowflake, said: “We are heavily investing in Python to make it easier for data scientists, data engineers, and application developers to build even more in the Data Cloud, without governance trade-offs.

“Our latest innovations extend the value of our customers’ data-driven ecosystems, enabling them with more access to data and new ways to develop with it directly in Snowflake. These capabilities, paired with Snowflake’s best of class data security and privacy, are changing the way teams experiment, iterate, and collaborate with data to drive value.”

Tags: Python, snowflake, snowpark

A career as a developer in any sector is pretty challenging. The profession can appear even more daunting when you are a junior developer. The lack of formal training about real-world software development scenarios during college days leaves the developers to learn on their own. Hence, they make many novice mistakes that stick for a long time. Without proper guidance, the initial habits can slow down the junior developer’s career progression.

Everyone makes several of these beginner’s mistakes during the initial phases of their career. If you are passionate about making it big in your development sector, here is a list of the top ten common mistakes you need to be aware of as a junior developer.

Focusing on Code Instead of the Big Picture

It’s easy to get bogged down in the details when you’re starting out. But it’s important to remember that code is only a small part of the development process. Focusing on the big picture will help you understand the overall goal of your project and help you make better decisions. To come up with good solutions, you need to spend time thinking. You have to remember that the author of React did not come up with the idea for the framework in a day. You have to focus on your target and follow up on whatever you need to get to that target.

Not Knowing Their Self Worth

When developers are fresh out of their institutions or when they are out in the market looking for a job, they most likely have no idea about their worth. Depending on individuals, they either overestimate their capability or underestimate it. In either case, not knowing is not helpful to get the right start to their career.

Developers who overestimate their capabilities tend to have high expectations from their first job. They feel they are doing the company a favor. This mindset reflects in the interviews and, later, in their work.

Again, developers who underestimate their abilities tend to take the very first offer they get. They do not try to find out if they are paid as per the market standard. They also prefer not to ask what kind of work they will be offered or whether the work culture is flexible and a good fit for them.

It is not always easy to negotiate during your first job search. Circumstances can compel you to start earning as early as possible. If that is the case, surely you can latch on to the first software job you get. Once you start making money, you can further your career in your own time and money. You can also find out if a position is suitable for you by doing a bit of research on the internet. Learn about the company culture from the reviews provided by employees on various sites.

Not Reading Documentation

Junior developers rarely read documentation, or they only read it superficially. They often skip it and start working on a subject or solving their problem. But the fact is that documentation is an important source of information. And you need to read it in-depth if you want to be a successful developer.

Documentation can help you learn the syntax and usage of a language or library, as well as how to use a tool or library properly. It can also help you understand the API for a particular software system. So, be sure to read the documentation.

Not Asking Questions

A common mistake junior developers often make is they do not ask questions proactively. Some developers are shy in asking questions. Others might be hesitant because they think their query might be a silly on.

Whichever might be the reason, they need to overcome the hurdle to be successful in their career. They should ask questions every time they do not understand. People will be more than happy to explain when they are on the topic.

Sometimes, the question will not have a straightforward answer. People might give their opinion based on their knowledge. If you are not satisfied, you can ask someone else to confirm your understanding. The idea is to clear out any doubt as quickly and as confidently as possible.

Lacking of Practice

Junior developers often underestimate the importance of practice. It’s not enough to just learn the theory — you also need to practice what you have learned.

Practice makes a man perfect, and the more you practice, the better you will become at your work. Try to find opportunities to practice your skills, whether it’s through tutorials, exercises, or projects. No one is born as a great developer. They become one by working hard and practicing‌.

They should practice according to their field of work. If you are a software developer, work hard on your problem-solving skills, programming languages, and accuracy and attention to details. These sometimes may seem very easy for you, but if you want to develop these skills, then you have to practice them. Everything takes practice!

Conclusion

This list summarizes experiences shared by other developers over the year and my experience as well. As a unique individual, your experiences might vary from others. If you remain vigilant and stay away from these mistakes, you can achieve a great start as a developer. Hence, understand the mistakes and take action based on your situation. I am sure, armed with the above knowledge and perseverance, you can achieve the professional and personal goals you set for yourself.

Tags: Development

Python is a very popular programming language today and often does not need an introduction. It is widely used in various business sectors, such as programming, web development, machine learning, and data science. Given its widespread use, it’s not surprising that Python has surpassed Java as the top programming language. In this article, you will discover the top ten reasons why you should learn Python.

What is the Python

Python is a high-level, object-oriented programming language with built-in data structures and dynamic semantics. It supports multiple programming paradigms, such as structures, object-oriented, and functional programming, which was created by Guido van Rossum. It is an interpreted, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. Python is dynamically typed and garbage-collected. It supports different modules and packages, which allows program modularity and code reuse.

Python was initially started as a successor for the ABC programming language. According to the LaTeX-based early Python documentation (1991), the goal of Python was to offer a better programming language for scripting by filling the gap between C and traditional Shell scripting languages. The issue is that you can’t access C-based operating system APIs natively in Bash. On the other hand, writing Shell scripts in C is indeed more time-consuming than Bash. Python became one of the most popular languages because of the simple syntax, full-featured standard library, rich open-source library ecosystem, and advanced frameworks. New features like type hints and impressive open-source libraries/frameworks make Python suitable for enterprise apps.

Better Practical Alternative

A lot of tech companies do a series of interviews to find top engineering candidates. These interviews usually include technical, HR, and management, etc. In technical interviews, interviewers often ask candidates to write pseudocodes for various algorithmic challenges. Pseudocodes are good, but they come with a small problem. Pseudocodes typically don’t have a standard syntax, so candidates often tend to borrow some syntax from their favorite languages. As a result, candidates write various pseudocodes for one technical problem.

What if we have a standard pseudocode syntax? How about pseudocode syntax, which actually works as a programming language? Writing the Python code is undoubtedly more productive than writing traditional pseudocodes. Almost all on-site development interviews typically test candidates’ analytical skills — not how many fancy syntaxes they know in a specific programming language, so using Python in technical interviews saves everyone’s time.

Usability & Flexibility

Programmers initially used Python on personal computers for various general-purpose scripting requirements like automation. Later, programmers started writing GUI apps and web apps with Python. Now, Python programmers can use the Kivy. Again, not only is Python easy to learn but also, it’s flexible. Over 125,000 third-party Python libraries exist that enable you to use Python for machine learning, web processing, and even biology. Also, its data-focused libraries like pandas, NumPy, and matplotlib make it very capable of processing, manipulating, and visualizing data — which is why it’s favored in data analysis. It’s so accommodating, it’s often called the “Swiss Army Knife” of computer languages.

Career & Earning Potential

Going hand-in-hand with lightning speed growth, Python programming is in high demand for jobs. Based on the number of job postings on one of the largest job search platforms, LinkedIn.com, Python ranks #2 in the most in-demand programming languages of 2020.

As Python is the second-highest paid computer language, you can expect an average salary of USD 110,026 per year. Nothing to cry about! If you can land a job with Selby Jennings, you’ll earn the most. The average salary there is USD 245,862. Amazing!

Python Security

The Python Software Foundation and the Python developer community take security vulnerabilities ‌seriously. A Python Security Response Team has been formed that does triage on all reported vulnerabilities and recommends appropriate countermeasures. To reach the response team, send an email to security at python dot org. Only the response team members will see your email, and it will be treated confidentially.

The PSRT mailing list is tightly controlled, so you can have confidence that your security issue will only be read by a highly trusted cabal of Python developers. If for some reason you wish to further encrypt your message to this mailing list (for example, if your mail system does not use TLS), you can use our shared OpenPGP key, which is also available on the public key servers.

Incredibly supportive community

While programming is often misinterpreted as a solo-sport, one of the greatest tools a programmer will ever have is the support of their community. Thanks to online forums, local meet-ups, and the open source community, programmers continue to learn from and build on the success of their predecessors. GitHub is where developers store project code and collaborate with other developers. With over 1.5M repositories on GitHub and over 90,000 users committing or creating issues in these repositories, Python has the second largest GitHub community.

In addition to online communities, Python User Groups are places where developers can meet others working with Python to share resources and solutions and cheesy Python jokes.

Conclusion

Now that you know the reasons to learn Python Programming, and how it can give you a career boost, the next step is simple. You just have to learn the code and start utilizing it. Python has become the language of choice for AI researchers, who have produced numerous packages for it. Reusing, recycling and improving other programmers’ code is fundamental to being a successful programmer, which is why Python’s robust programming communities help make it a solid programming language to learn.

Tags: Development, programming language, Python

The Windows Subsystem for Linux (WSL) is a feature of the Windows operating system that enables you to run a Linux file system, along with Linux command-line tools and GUI apps, directly on Windows, alongside your traditional Windows desktop and apps. You can now preview Windows Subsystem for Linux (WSL) support for running Linux GUI applications (X11 and Wayland) on Windows in a fully integrated desktop experience. Now we have 2 different WSL here. In this article, let’s try to see how both WSL 1 WSL 2 are different from each other.

Comparing features

As you can tell from the comparison table above, the WSL 2 architecture outperforms WSL 1 in several ways, with the exception of performance across OS file systems, which can be addressed by storing your project files on the same operating system as the tools you are running to work on the project.

WSL 2 is only available in Windows 11 or Windows 10, Version 1903, Build 18362 or later. Check your Windows version by selecting the Windows logo key + R, type winver, select OK. (Or enter the ver command in Windows Command Prompt). You may need to update to the latest Windows version. For builds lower than 18362, WSL is not supported at all.

WSL 2 enables Linux GUI applications to feel native and natural to use on Windows.

• Launch Linux apps from the Windows Start menu
• Pin Linux apps to the Windows task bar
• Use alt-tab to switch between Linux and Windows apps
• Cut + Paste across Windows and Linux apps

You can now integrate both Windows and Linux applications into your workflow for a seamless desktop experience.

What’s new in WSL 2

WSL 2 is a major overhaul of the underlying architecture and uses virtualization technology and a Linux kernel to enable new features. The primary goals of this update are to increase file system performance and add full system call compatibility.

WSL 2 architecture

VM experience is often slow to boot up, isolated, consumes a lot of resources, and requires your time to manage it. WSL 2 does not have these attributes. WSL 2 provides the benefits of WSL 1, including seamless integration between Windows and Linux, fast boot times, a small resource footprint, and requires no VM configuration or management. While WSL 2 does use a VM, it is managed and run behind the scenes, leaving you with the same user experience as WSL 1.

Integration of Linux kernel

The Linux kernel in WSL 2 is built by Microsoft from the latest stable branch, based on the source available at kernel.org. This kernel has been specially tuned for WSL 2, optimizing for size and performance to provide an amazing Linux experience on Windows. The kernel will be serviced by Windows updates, which means you will get the latest security fixes and kernel improvements without needing to manage it yourself. The WSL 2 Linux kernel is open source.

Increased file IO performance

File intensive operations like git clone, npm install, apt update, apt upgrade, and more are all noticeably faster with WSL 2.

The actual speed increase will depend on which app you’re running and how it is interacting with the file system. Initial versions of WSL 2 run up to 20x faster compared to WSL 1 when unpacking a zipped tarball, and around 2-5x faster when using git clone, npm install and cmake on various projects.

Full system call compatibility

Linux binaries use system calls to perform functions such as accessing files, requesting memory, creating processes, and more. Whereas WSL 1 used a translation layer that was built by the WSL team, WSL 2 includes its own Linux kernel with full system call compatibility. Benefits include:

• A whole new set of apps that you can run inside of WSL, such as Docker and more.
• Any updates to the Linux kernel are immediately ready for use. (You don’t have to wait for the WSL team to implement updates and add the changes).

How to install WSL and update to WSL 2

Before installing any Linux distributions on Windows, you must enable the “Windows Subsystem for Linux” optional feature.

Open PowerShell as Administrator and run:

dism.exe /online /enable-feature /featurename:Microsoft-Windows-Subsystem-Linux /all /norestart

To only install WSL 1, you have to restart your machine and move on to install your Linux distribution of choice. You can download it from the Windows store.

To update to WSL 2, you must have a running Windows 10, updated to version 2004, Build 19041 or higher.Before installing WSL 2, you must enable the “Virtual Machine Platform” optional feature.

Open PowerShell as Administrator and run:

dism.exe /online /enable-feature /featurename:VirtualMachinePlatform /all /norestart

Restart your machine to complete the WSL install and update to WSL 2.

To activate WSL 2 you need to update the kernel component. You can do it by visiting here and install the update by following the steps.

You can check the WSL version assigned to each of the Linux distributions you have installed by opening the PowerShell command line and entering the command (only available in Windows Build 19041 or higher): wsl -l -v

wsl --list --verbose

To set a distribution to be backed by either version of WSL please run:

wsl --set-version <distribution name> <versionNumber>

Make sure to replace <distribution name> with the actual name of your distribution and <versionNumber> with the number ‘1’ or ‘2’. You can change back to WSL 1 at any time by running the same command as above but replacing the ‘2’ with a ‘1’.

If you want to make WSL 2 your default architecture you can do so with this command:

wsl --set-default-version 2

Conclusion

Due to the limitations in WSL1 Microsoft re-invented the WSL1 and introduced WSL2 which is available in Windows 10 version 2004 update. Instead of using a compatibility layer which converts Linux system calls to windows system calls, WSL2 offers its own isolated Linux kernel running on a thin version of the Hyper-V hypervisor. And this gives WSL2 much more opportunity to handle things better than WSL1. Hopefully this guide and informations will help you to understand why WSL2 is a better choice over WSL1.

Tags: Windows Subsystem for Linux, WSL1, WSL2

File compression is a key technology for digitization, as it can sustainably relieve the resources of network-based infrastructures. AVIF (AV1 Image File Format) is a modern image file format specification for storing images that offer a much more significant file reduction when compared to other formats like JPG, JPEG, PNG, and WebP. Compared to JPEG, AVIF compresses files more efficiently and provides higher image quality. Major global corporations in the digital industry are interested in the implementation of the new image format.

What is AVIF?

AVIF or AV Image Format is an open and royalty-free image format based on the AV1 codec, and similar to AV1 – AVIF provides a very high compression rate. Being royalty-free makes it one of the best among its peers.

A consortium of leading digital economy players was founded in 2015, tasked with the improvement of image file compression. The Alliance for Open Media (AOMedia), whose members include Amazon, Cisco, Facebook, Google (including YouTube), Mozilla, Microsoft, Netflix, Intel, AMD, Tencent and Apple, focuses on data traffic online. Because images use up over half of the average bandwidth of a website, improved image compression not only benefits the performance of individual websites, but the overall performance of the web is optimized because smaller files accelerate data traffic, reduce energy consumption, and use less storage space.

For the new technology to become established as a standard, it should not incur any licensing fees and should be freely usable as an open source format. In March 2018, AOMedia published the specification of a new free video codec. Since then, a final first version of AOMedia Video 1 (AV1 for short) has been officially launched.

The industrial consortium’s efforts have resulted not only in a license-free, open video codec for moving images, but also in the AV1 Image File Format (AVIF) for still images. AVIF combines the efficient compression algorithms of the AV1 video codec with the container technology of the HEIF format (High Efficiency Image File), which has been used by Apple for some time now. It is a static image format developed by Alliance for Open Media (AOMedia) in conjunction with Google, Cisco, and Xiph.org from an extraction of the keyframes of the video format AV1.

Advantages of AVIF

AVIF offers many advantages. Among its major ones are:

• AV1 and AVIF formats are open source codecs. There are no additional costs for using AOMedia technology. This doesn’t just benefit the big players, but the entire open source community.
• The fact that AVIF is free of charge is a major advantage over the HEIF format, which is currently still a preferred format for Apple.
• The AVIF format meets the requirements of a modern image format by combining high image quality (especially for HDR images with greater color depth than 8 bits) and many functions (similar to HEIF, the format is superior to the JPEG format in this regard).
• Compared to the established JPEG format, AVIF currently reduces the image size by an average 50 percent (similar to the comparably efficient HEIF format). In addition, AVIF is more efficient than its competitor WebP, which has failed to establish itself.
• Highly efficient AVIF compression reduces the load times of websites, conserves network bandwidth, and reduces data streams for video-on-demand, cloud, and web space providers.
• Many AVIF advantages extend beyond its online use. Image archives, photographers, printers, etc. can also benefit from the format’s development to receive higher resolution images that relieve available resources.

With these advantages, there lies a single disadvantage, which is its availability in the market. AVIF is a fairly new image format; though it’s gaining a lot of praise worldwide, AVIF still lacks browser support. Browsers are a primary medium for most images that we see in everyday life. Hence browser compatibility is crucial.

Current support for AVIF

Compared to the popular JPEG format, which has been around since the early 1990s, AVIF is a relatively new file format for static images. The newcomer has yet to prove itself in practical tests. It is therefore difficult to reliably predict the future of the image format. However, due to its many advantages, the chances of a nationwide implementation are high.

The video-on-demand provider Netflix is an important pioneer in the application of the new technology. The streaming specialist is currently testing the AVIF format in order, for example, to convert the platform’s user interface from SDR to HDR (e.g., to improve previews). A gradual introduction of the format is planned, whereby it is used for a continuously increasing number of content and platforms.

Browsers and operating systems are also getting used to the new technology. Even with Windows adopting AVIF to save space in their systems and giving a push to increase the importance of this format, content providers still have to rely on JavaScript if they want to use this image format. In addition, although AVIF has been recently adopted and rolled out in Google Chrome as well, it still doesn’t enjoy complete universal cross browser availability as Firefox and Safari still have to give support for it.

Conclusion

AVIF has all the prerequisites to establish itself successfully and define a new image standard online to replace JPEG. Once the remaining technical hurdles are resolved (e.g., slow and resource-guzzling coding processes), the multifunctional image format and the AV1 video codec offer high quality. Finally, this is also an important step towards sustainability, as AVIF conserves energy, and network and storage resources. Although AVIF has the backing of big top tech companies and some of them like Netflix, Google and Microsoft have already implemented this format. Currently, AVIF looks like a future car packed with extraordinary features, but people are still skeptical about involving it in their lives.

Tags: AVIF

After a long time, Bootstrap v5.2.0-beta1 was released last week. This version of bootstrap is the biggest release update till now and is being billed as the framework’s most significant release since Bootstrap 5.0 two years ago. This version features a redesigned document, all components of CSS Variable, responsive offcanvas, new helpers and utilities, improved buttons and inputs, and many underlying improvements. Builders are offering CSS variables for all components and new helpers and utilities in the latest planned upgrade to the Bootstrap web development framework. Let’s look at some major changes in Bootstrap 5.2.0.

Redesigned documents

The development team rewrites the whole home page, To better show Bootstrap All functions of. Changes include simplifying the navigation bar, Cancel sub navigation, and changing the sidebar to always show links to each page to improve discoverability. It also shows Updated Quick Start Guide. It is now through CDN Use Bootstrap Step-by-step guide.

The updated navigation bar also has a new version selector, which starts from v5.2.0 And higher. On any page, click versions and view options to navigate to previous minor versions of the same page. When a page does not exist in the old version, you will see the disabled version in the drop-down list. Official expression, it currently has no plans to link pages across major versions.

Document search is now powered by the latest version of Algolia DocSearch Provide support , Brings improved design. You can even display your recent searches.

Design adjustment

In order to cooperate with the redesign of documents, the development team made some detailed border radius updates for the buttons and input methods. Components now have improved theming and CSS variables for real-time customization. Color-mode support will be added soon, starting with dark mode.

It is easier to modify custom components. Here are two examples:

New.text-bg-color helpers have been added. Developers can now use the.text-bg-* helpers to set background colour with contrasting foreground colour instead of setting individual.text-* and.bg-* utilities.

Font-weight utilities have been expanded to include.fw-semibold for semibold fonts.

Component CSS variables

With this release, all components now include CSS variables to enable real-time customization, easier theming, and (soon) color mode support starting with dark mode. Every component page has been updated to include a reference guide of the relevant CSS variables.

--#{$prefix}btn-padding-x: #{$btn-padding-x};
--#{$prefix}btn-padding-y: #{$btn-padding-y};
--#{$prefix}btn-font-family: #{$btn-font-family};
@include rfs($btn-font-size, --#{$prefix}btn-font-size);
--#{$prefix}btn-font-weight: #{$btn-font-weight};
--#{$prefix}btn-line-height: #{$btn-line-height};
--#{$prefix}btn-color: #{$body-color};
--#{$prefix}btn-bg: transparent;
--#{$prefix}btn-border-width: #{$btn-border-width};
--#{$prefix}btn-border-color: transparent;
--#{$prefix}btn-border-radius: #{$btn-border-radius};
--#{$prefix}btn-box-shadow: #{$btn-box-shadow};
--#{$prefix}btn-disabled-opacity: #{$btn-disabled-opacity};
--#{$prefix}btn-focus-box-shadow: 0 0 0 #{$btn-focus-width} rgba(var(--#{$prefix}btn-focus-shadow-rgb), .5);

Values for virtually every CSS variables are assigned via Sass variable, so customization via CSS and Sass are both well supported. Also included for several components are examples of customizing via CSS variables.

New _maps.scss

Bootstrap v5.2.0-beta1 introduces a new Sass file with _maps.scss that pulls out several Sass maps from _variables.scss to fix an issue where updates to an original map were not applied to secondary maps that extend it. It’s not ideal, but it resolves a longstanding issue for folks when working with customized maps.

For example, updates to $theme-colors were not being applied to other maps that relied on $theme-colors (like the $utilities-colors and more), which created broken customization workflows. To summarize the problem, Sass has a limitation where once a default variable or map has been used, it cannot be updated. There’s a similar shortcoming with CSS variables when they’re used to compose other CSS variables.

This is also why variable customizations in Bootstrap have to come after @import “functions”;, but before @import “variables”; and the rest of the import stack. The same applies to Sass maps—you must override the defaults before they get used. The following maps have been moved to the new _maps.scss:

• $theme-colors-rgb
• $utilities-colors
• $utilities-text
• $utilities-text-colors
• $utilities-bg
• $utilities-bg-colors
• $negative-spacers
• $gutters

New helpers and utilities

• Added a new .text-bg-{color}helpers. Now you can use .text-bg-* helpers To set the background color with a contrasting foreground color, Instead of setting up a separate .text-* and .bg-* utilities.
• Expanded font-weightutilities, Include for semibold fonts Of .fw-semibold.
• Expanded border-radius utilities , Includes two new sizes ：.rounded-4 and .rounded-5, To provide more options.

Responsive offcanvas

Offcanvas component now has responsive variations. The original .offcanvas class remains unchanged—it hides content across all viewports. To make it responsive, change that .offcanvas class to any .offcanvas-{sm|md|lg|xl|xxl} class.

Coming soon: Dark mode!

Much of the work they have done in v5.2.0-beta1 has been in support of adding dark mode to Bootstrap. Yes, it’s finally coming in their next minor release!

They have also mentioned “We’re adding tons of new global CSS variables, cleaning up docs styles, and better supporting overall customization”.

Coming In V5.3.0

There’s lots to look forward to in their next minor release, though they’ll likely have some bug fixes along the way.

• Dark mode! As mentioned above, they’re actively working to bring more nuanced color options and color modes to Bootstrap.
• An attribute toggle plugin to programmatically toggle classes and attributes by only writing HTML.
• CSS variables for forms!
• CSS variables for forms!
• Sticky headers for tables
• Mixins and functions for modifying the utilities API.
• An option for “always floating” floating forms.

Conclusion

More advancements in this direction are expected as Version 5 development progresses. Version 5.2.0 includes investments in helpers and utilities to make it easier to modify custom components. The project website provides access to Bootstrap v5.2.0-beta1. You can Head to https://getbootstrap.com to get the latest release. Hopefully the next update will be beneficial to those who have been wanting the above mentioned features.

Tags: Bootstrap, Bootstrap 5.2