AWS Cloud9 vs. Python IDLE

AWS Cloud9 is great for product engineering and coding where you must take time to pair program and code in a specific isolated environment. It is entirely cloud based so there's no worry about saving and data consistency. It is all hosted on the Amazon Web Services cloud. It is less appropriate for more general workflows that don't require a specific cloud instance.

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

• Great, fast interface - There is a large list of shortcuts that make development on this IDE an experience that can sometimes even compare to something native.
• Integrated debugging/troubleshooting - AWS Cloud9 has integrated debugging tools that are quite well-designed.
• Lambda integrations - Cloud9 allows you to instantly run and maintain Lambda functions. It's probably the best IDE for developing on AWS Lambda.

Incentivized

• The best thing is the debug that incorporates.
• Friendly graphic environment.
• Provide keyword auto-fill.
• Color the command syntax automatically.
• Very configurable.

Incentivized

• According to the project that is being executed it can become slow.
• It does not have the basic text manipulators.
• Shared terminals sometimes take a while to display.

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 interface for Cloud9 needs some improvement. It is simply not as powerful and intelligent as a local text editor would be and thus it lacks the capabilities of fast filling when coding. Otherwise, I think it has a fair interface that they have tried mimicking an IDE.

Incentivized

1-Ease of use: python IDLE is relatively ease to use,especially for developers familiar with python. Its simple and intuitive interface makes it easy to navigate and find basic features 2- learnability:python IDLE is relatively easy to learn especially for developers with prior experience with python or other programming Languages 3- efficiency: Python IDLE efficiency is limited by its basic feature set and lack of advanced tools.while it’s great for rapid prototyping and small scale developers

Customer support is managed by the Cloud support team. I won't be able to comment on details, but it's fast.

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

S3 is a great service for storing unstructured data. It is cheap and us an user we don't have to care about scaling. Amazon S3 is a managed service. We use it for avery simple projects in our organization.

Incentivized

I chose python IDLE for its simplicity and ease of use, which made it ideal for rapid prototyping and small scale development future sets: while python IDLE offers a basic set of features, including syntax highlighting, auto completion and basic debugging tools Performance :python IDLE is relatively lightweight and doesn’t require significant system resources, making it an excellent choice for older machines or resources constrained environment

• This software has been really useful for our company since thanks to the fact that you can work together with other colleagues in the same code, it is much easier to advance in the development of projects and thus be able to make your delivery in a much shorter time.
• Because it provides all the necessary tools to develop projects, there is a great saving of time and costs.
• It is easy to use so any user can use it and this makes it possible to streamline each project much faster and more if you do not necessarily have to be in the company to advance in them, and this is thanks to the fact that it can be used from anywhere with internet access.

• 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