Austin based Enthought offers their flagship scientific Python distribution, Canopy. The Canopy Geoscience (or Canopy Geo) variant of the product is a data analysis, exploration and visualization package optimized for geologists & geophysicists, and researchers in petroleum science.
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Microsoft Visual Studio Code
Score 9.3 out of 10
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Microsoft offers Visual Studio Code, an open source text editor that supports code editing, debugging, IntelliSense syntax highlighting, and other features.
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.
As a general workhorse IDE, Microsoft Visual Studio Codee is unmatched. Building on the early success of applications such as Atom, it has long been the standard for electron based IDEs. It can be outshone using IDEs that are dedicated to particular platforms, such as Microsoft Visual Studio Code for .net and the Jetbrains IDEs for Java, Python and others. For remote collaborative development, something like Zed is ahead of VSCode live share, which can be quite flakey.
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.
The customization of key combinations should be more accessible and easier to change
The auxiliary panels could be minimized or as floating tabs which are displayed when you click on them
A monitoring panel of resources used by Microsoft Visual Studio Code or plugins and extensions would help a lot to be able to detect any malfunction of these
Solid tool that provides everything you need to develop most types of applications. The only reason not a 10 is that if you are doing large distributed teams on Enterprise level, Professional does provide more tools to support that and would be worth the cost.
Microsoft Visual Studio Code earns a 10 for its exceptional balance of power and simplicity. Its intuitive interface, robust extension ecosystem, and integrated terminal streamline development. With seamless Git integration and highly customizable settings, it adapts perfectly to any workflow, making complex coding tasks feel effortless for beginners and experts alike.
Overall, Microsoft Visual Studio Code is pretty reliable. Every so often, though, the app will experience an unexplained crash. Since it is a stand-alone app, connectivity or service issues don't occur in my experience. Restarting the app seems to always get around the problem, but I do make sure to save and backup current work.
Microsoft Visual Studio Code is pretty snappy in performance terms. It launches quickly, and tasks are performed quickly. I don't have a lot of integrations other than CoPilot, but I suspect that if the integration partner is provisioned appropriately that any performance impact would be pretty minimal. It doesn't have a lot of bells and whistles (unless you start adding plugins left and right).
Active development means filing a bug on the GitHub repo typically gets you a response within 4 days. There are plugins for almost everything you need, whether it be linting, Vim emulation, even language servers (which I use to code in Scala). There is well-maintained official documentation. The only thing missing is forums. The closest thing is GitHub issues, which typically has the answers but is hard to sift through -- there are currently 78k issues.
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.
Visual Studio Code stacks up nicely against Visual Studio because of the price and because it can be installed without admin rights. We don't exclusively use Visual Studio Code, but rather use Visual Studio and Visual Studio code depending on the project and which version of source control the given project is wired up to.
It is easily deployed with our Jamf Pro instance. There is actually very little setup involved in getting the app deployed, and it is fairly well self-contained and does not deploy a large amount of associated files. However, it is not particularly conducive to large project, multi-developer/department projects that involve some form of central integration.
