AWS Cloud9 vs. Codeanywhere vs. Spyder

When I am working with a large team of developers. Also, when a security policy, you are not allowed to install any app on your laptop. Cloud 9 is well integrated with Cloud commit. So we don't have to spend time in configurations.

Incentivized

If you're looking for a VS Code-like online environment with containers to spin up a dev environment or execute code and scripts it is a good fit. The environments are very customizable, and, all said and done, the price is fair. If you're looking for a remote code editor that allows you to connect via SFTP/SSH and edit the remote files, it isn't quite as seamless as it used to be. I still haven't found any all-cloud alternative, but it could be better.

Incentivized

Spyder is an open-source Python IDE designed for the movement of data science work. Spyder comes with an Anaconda package manager distribution, so depending on your setup you may have installed it on your machine.

Spyder includes most of the "standard IDE" features you can expect, such as a strong syntax code editor, Python code rendering, and an integrated text browser.

Spyder is used when we want to develop a code that is useful and able to explore proper documentation of the code that has been written. We use Spyder to perform data-related operations like filtration, cleaning, and enhancing the data qualities. There some cases where it is less appropriate like working in an environment, creating dashboards of data visualizations and plots.

• It provides an extremely intuitive and easy-to-use interface, so adapting to it does not take much time.
• It contains the most common programming languages.
• It allows the export of files, either directly to the repository or to the team where you want it.
• It is housed in the cloud so you can work with it from anywhere.
• Allows you to share code or work on them with others in real-time.
• Does not require installation.

• Run development containers with backend and frontend access.
• Allow for multiple users to collaborate and share containers and connections.
• Manage multiple connections to different servers.

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• Provides wider screen to read and write code and flexibility to adjust size as per requirement.
• While running the code it provide the variable overview and memory overview
• Lightweight and easily available in Anaconda Navigator
• Multiple compilation options are available
• Works well for data analytics, Django, Flask and Fast API frameworks

Incentivized

• Confusing documentation - AWS's documentation remains quite confusing, and the layout of other services/settings that you have to use with Cloud9 can be a bit of a handful.
• Sometimes slow - As the size of a project increases, the editor gets increasingly slower, and starts slowing down the browser overall.
• Long setup process - The setup for Cloud9 can be hard and tough, especially since the documentation is quite hard to understand.

Incentivized

• Since some updates a couple of years ago, using Codeanywhere as a remote code editor rather than a container-based development environment has been more cumbersome and difficult.
• The modular nature of connections and containers seems like a good idea, but they don't always work properly.
• It's difficult sometimes to share a connection or container together with a collaborator.

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.

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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

[AWS] Cloud9 offers specific features not available in the competition: Code collaboration using the chat features is the highlight which sets it apart. [The] code completion feature makes [it] very similar to the offline IDE like eclipse. It's much easier to use compared to Codeanywhere. It provides terminal access to EC2 instances and hence other amazon services.

Incentivized

I've used CodeTasty, which is much more of a straight remote code editor, but their dev team is entirely unresponsive, and I became uncomfortable storing credentials with them, so I pulled everything from them and went back to Codeanywhere. VS code is similar but not fully online. While I know that they've released a fully online version, I haven't had the time or wherewith-all to make it work in the capacity I need. Codeanywhere is still the best solution I've found.

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I think Spyder doesn't stack up as well as other IDEs due to its many limitations. But it is available for free and that is one advantage it has over its competitors

Incentivized

• We save time since we do not need to configure files or our equipment.
• We have the most appropriate tools for software development in one place.
• We can work from anywhere so if that day we could not get to our office or something we can do from home.
• We can code with a single browser.

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• Helped me make mission critical edits remotely and on-the-fly.
• Spent a bit of time figuring out the change in user interfaces.

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• It has helped me learn python quickly
• The ability to generate figures quickly and interact with them is helpful

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