Codeanywhere is a Cloud IDE with the features of a Desktop IDE. Codeanywhere enables users to set up a workflow in any way desired. The features needed for coding tasks are built into Codeanywhere, including support for debugging, syntax highlighting, intelligent code completion, snippets, code refactoring, and embedded Git. Languages included are popular programming ones such as C, C#, C++, CSS, HTTP, Java, JavaScript, PHP, Python, Ruby, SQL.
$6
per month 1 container
Enthought Canopy (discontinued)
Score7 out of 10
N/A
Enthought Canopy Geoscience (or Canopy Geo) variant of the product was a data analysis, exploration and visualization package optimized for geologists & geophysicists, and researchers in petroleum science. The product is discontinued.
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Enthought Canopy is best suites for scripting data analytical concepts. It has a wide range of data analytical libraries and also is good for data visualization. I would not recommend using Enthought Canopy only as an IDE, there may be better options available. If you're looking for a good data simulation & visualization package, Canopy it is.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Providing scientific libraries, both open source and Enthought's own libraries which are excellent.
Training. They provide several courses in python for general use and for data analysis.
Debugging tools. Several IDEs provides tools for debugging, but I think they are insufficient or too general. Canopy has a special debugging tool, specially design for python.
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Before Canopy with its python we were working with Matlab. We decided for Canopy against Matlab for two reasons: First, we believe that python together with NumPy or SciPy can achieve the objectives with less code and therefore less training, and second the prizes are much lower than matlab which is most robust, expensive and less intuitive. It's clear we are making the comparison with python and it has nothing to with canopy. But with Canopy you feel you have all those tools close together without the problem of configuration, besides a lot of personalized libraries that complements a typical python environment.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
