IntelliJ IDEA vs. Python IDLE

This is a superb tool if your project involves a lot of backend development, especially in Java/Spring Boot and Kotlin. The support for the front end is great as well, but some developers may prefer to use the GitHub copilot add-on. I especially love using the GitHub copilot add-on. It may be less appropriate if your project requires heavy use of HotSwaps for backend debugging, as sometimes the support for that can be limited.

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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

• Unit testing: Fully integrated into IntelliJ IDEA. Your unit tests will run smoothly and efficiently, with excellent debugging tools for when things get tricky.
• Spring integration: Our Spring project using Maven works flawlessly in IntelliJ IDEA. I know firsthand that Apache is also easily and readily supported too. The integration is seamless and very easy to set up using IntelliJ IDEA's set up wizard when importing new projects.
• Customization: IntelliJ IDEA comes out of the box with a bunch of handy shortcuts, as well as text prediction, syntax error detection, and other tools to help keep your code clean. But even better is that it allows for total customization of shortcuts you can easily create to suit your needs.

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• 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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• Finding if a feature exists or not in IntelliJ IDEA can be challenging.
• For example, if we know how to format a particular file, the command is Ctrl+Alt+Shift+L, but if we don't, then finding it is difficult.
• Setting up a project interpreter and directory structure might not be intuitive at first.
• Git integration can be improved. For example, it isn't easy to rebase using UI in IntelliJ IDEA.

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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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VS Code is maturing and has a Scala plugin now. The overall experience with VS Code - for web development at least - is very snappy/fast. IntelliJ feels a bit sluggish in comparison. If that Scala plugin for VS Code is deemed mature enough - we may not bother renewing and resort to the Community Edition if we need it.

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There is always room for improvement, but I haven't met any IDE that I liked more so far. Even if it did not fit a use case right out of the box, there is always a way to configure how it works to do just that.

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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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Customer support is really good in the case of IntelliJ. If you are paying for this product then, the company makes sure that you will get all the services adequately. Regular update patches are provided to improve the IDE. An online bug report makes it easier for the developers to find the solution as fast as possible. The large online community also helps to find the various solutions to the issues.

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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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This installs just like any other application - its pretty straight forward. Perhaps licensing could be more challenging - but if you use the cloud licensing they offer its as simple as having engineers login to the application and it just works.

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Eclipse is just so old, like a dinosaur, compared to IntelliJ. There are still formats that Eclipse supports better, especially old and/or propriety ones. Still, most of the modern software development needs can be done on IntelliJ, & in a much better way, some of them are not even supported on Eclipse.

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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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• Easier to find bugs and debugs, thus reducing man hours and generating immediate dollar impact.
• Coding time is lessened, which in turn again reduces man hours and generates immediate dollar impact.
• Refactoring code is more innovative and easy here, resulting in more maintainable code.

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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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