Python IDLE vs. React (React.js)

Scenarios where python IDLE is well suited 1-Quick scripting and prototyping 2-Education and training 3-small projects utilities 4-exploring python libraries and modules Scenarios where python is less appropriate 1 large scale projects 2 complex debugging and profiling 3 multi language development 4 Advanced code analysis and inspection

React is a JavaScript user interface construction library that works well for:

• Developing web apps with dynamic and complicated user interfaces.
• creating reusable UI elements that may be used in other applications.
• creating single-page applications with dynamic content updates that don't require a page reload.
• The Virtual DOM's effective updating mechanism allows it to handle large volumes of data updates.

React, on the other hand, might be less suitable for:

• Websites that are simple, stagnant, and have no interaction. Other libraries or simple HTML, CSS, and JavaScript may be a better fit in such circumstances.
• Web sockets may be a better choice for applications that need real-time updates, such as chat or gaming apps.
• When creating mobile apps, React Native is a better option.
• Server side rendering only, as React is designed to run on the client side.

• Firstly, I would say Python IDLE interface is user friendly.
• Easy to learn for the beginners.
• Syntax highlighting is nice features.
• Smart indent helps a lot.

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• React is fantastic for building performant user interfaces. Our web app is snappy and great for our customers.
• React has the philosophy of doing one thing and doing it well which is the view layer of the application. This makes it incredibly intuitive and flexible for developers to use.
• React has lead the way in being able to write modular and structured code. It is a drastic improvement since the days of spaghetti jQuery code.
• React has an unmatched community. The amount of tools and libraries available is fantastic, and there plenty of solutions available online for common problems.

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• Too simplistic
• Could not find source revision management integration support
• Only basic debugging is available
• Does not have data-science-specific notebooks (but can be installed separately)

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• Debugging React is challenging. Bugs in react code generate stack traces internal to React and it is often totally unclear how it relates to the code you actually wrote.
• Relating your React elements to corresponding DOM elements is difficult. The intentional separation of virtual and actual DOM also makes it difficult to map the elements to the structures in the DOM. This is partially ameliorated by the use of the React dev tool, which provides a DOM-like view of the React elements, but the tool still does not provide a direct correspondence with the DOM that is often necessary to figure out why something isn't right.
• Because JSX is React-specific and not a language feature, a special compilation process is necessary to convert JSX code to normal JS. Coming from a C++ background, compiling things doesn't bother me, but many JS developers are used to a less structured development.

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The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.

This IDE allows you to configure the environment, font, size, colors, .....

It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.

Once the IDE is executed you can start programming directly in it.

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React is just a bit of a different animal. I was avoiding it for the longest time. I thought for sure I would land on Vue or something else with a more approachable and familiar appearance. But after taking an online course in React, I started realize what people were raving about (and complaining about) and decided to implement it at our office for one of our products.

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Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.

In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.

As this IDE is made in Python, the support is the same group of Python developers.

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Since it's open-source and very popular, the community support for React and related tools and libraries is excellent. There are a lot of people using the same tools, and so issues tend to get fixed quickly and "recipes" are easy to come by. And since it's backed by Facebook, they have a dedicated engineering team working on the progression of React.

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It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run Jupyter Notebook on my cloud desktop

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While this is a widely contested debate with various blog posts and benchmarks all over the place, its really a personal choice to determine what works for the team. Coming from a Angular 1.x background, I decided to try a new framework when Angular 2.x was announced and at that time React is gaining popularity and Vue hasn't taken off yet. Compared to Angular 1.x and Vue (hybrid of React and Angular) that split the logic from the html templates, I loved the way React breaks code into components using the jsx syntax. In my mind, this allows for cleaner components and easier maintenance

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• In a short time, we were able to develop several ML models for various teams to make accurate decisions.
• Beginners can easily understand and adapt to GUI.
• We could automate several manual validation tasks and so could reduce human intervention.

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• Our web applications now run much faster because the whole page doesn't reload
• We spend less time developing UI components because a lot of them are readily available on NPM
• We don't have to optimize apps for multiple browsers since React natively supports it.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info