Oracle Java SE vs. Python IDLE

Oracle Java SE is well suited to long-running applications (e.g. servers). Java Swing (UI toolkit) is now rather outdated, lacking support for modern UI features. JavaFX, the potential replacement for Swing, has now been separated out of Java core. Ideally, there would be a path to migrate a large application incrementally from Swing to JavaFX, but due to different threading models and other aspects, it is difficult. At this point, it is probably better to use an embedded web browser (e.g. JxBrowser) to provide a modern UI in HTML/Javascript and keep just the business logic in Java.

Incentivized

IDLE is a good option to run small scripts directly on the console, and that's it. It is a good exit when you don't want or need to open a proper IDE like Pycharm.

Incentivized

• Plenty support built into the tool and IDE like Maven, Ant, Eclipse, IntelliJ.
• Strong object-orientation language and clear project structure.
• Wrapper underlines hardware and memory management so the developers can focus on business and implementation.
• It offers a huge library and framework support from third-parties and the community.

Incentivized

• 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.

Incentivized

• Commercial Licensing in 2019. Oracle will charge commercial organizations using Java SE for upgrading to the latest bug fixes and updates. Organizations will now need to either limit their implementation of Java SE or may need to drop it altogether.
• Slow Performance. Due to the all of the abstraction of the JVM, Java SE programs take much more resources to compile and run compared to Python.
• Poor UI appearance on all of the major GUI libraries (Swing, SWT, etc.). Through Android Studio, it is easy to get a native look/feel for Java apps, but when it comes to desktops, the UI is far from acceptable (does not mimic the native OS's look/feel at all).

Incentivized

• 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)

Incentivized

The language is fluent and has good support from a number of open source and commercial IDEs. Language features are added every 6 months, although long-term service releases are only available every 3 years. It would be nice if some of the older APIs were depreciated with more pressure to move to the new replacement APIs (e.g. File vs. Path), but transitions to new features are generally well implemented.

Incentivized

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.

Incentivized

Java is such a mature product at this point that there is little support from the vendor that is needed. Various sources on the internet, and especially StackOverflow, provide a wealth of knowledge and advice. Areas that may benefit from support is when dealing with complex multithreading issues and security libraries.

Incentivized

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.

Incentivized

Chose to go with Java instead of Python or C++ due to the expertise on the ground with the technology, for its ease of integration with our heterogeneous setup of production servers, and for the third party library support which we've found was able to address some challenging aspects of our business problem.

Incentivized

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

Incentivized

• The different versions make it harder to work with other companies where some use newer versions while some use older versions, costing time to make them compatible.
• Licenses are getting to be costly, forcing us to consider OpenJDK as an alternative.
• New features take time to learn. When someone starts using them, everyone has to take time to learn.

Incentivized

• 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.

Incentivized