AWS Cloud9 vs. Spyder

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

Spyder is well suited if you're limited on hardware. You have to work with single code file. You need to quickly write some code and test it. Apart from this if you want to have a look at your variables then you can make use of Spyder. If you're working with Anaconda navigator then this can be the best to start with as it can be installed with single click there.

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

• Debugging of your existing code
• Generates figures very quickly as part of a figures tab which lets users understand results quickly
• Different layouts are available for the software which will give the users freedom to decide what layout works best for them

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

• Colors in code format
• Add a broadcast to share the project with friends
• Contains more than one important language such as Python

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

It is fairly straightforward to use. Pretty much good to go as soon as you install it. The IDE itself is very user friendly, and it is only limited by whatever limitations Python has as a language. Great for those who want to run their scripts quickly or do some Python programming without fussing.

Incentivized

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

Most of data scientists or data engineers are either using ec2 on the cloud or Atom or PyCharm locally. It is a bit hard to find people who are still using Spyder and have the sight of the IDE and can help you to answer your question.

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 have chosen Spyder because it's free and open-source that comes with properly documented comments in the code. I have been using Spyder for more than 2 years and it always feels good to work with Spyder every time start my work. In Spyder, we have three windows one for man code window, idle window, and the other is for running your code and analyze. So to test a particular code I use the idle window to see what is going to be the result when I use this set of codes. That the main reason, I use Spyder.

• 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.

• Less time spent on employee training.
• Limited integration with Git.
• No tools for repository.

Incentivized