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 9.1 out of 10
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Microsoft offers Visual Studio Code, a 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.
Microsoft Visual Studio Code is highly recommended for the development of systems and / or complex applications entrusted to work teams under a specific methodology, and its use is also recommended for the maintenance of previously developed applications.
It is not recommended as a learning environment for developers with little experience as the learning curve would be too high
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.
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.
Looking at our current implementation, Microsoft Visual Studio Code is perfect for writing code and performing debug operations. Integration with SVN repository is easy and changes can be tracked effectively. Microsoft Visual Studio Code supports developers to write code productively using syntax check and easy customization. Microsoft Visual Studio Code also provides support for IntelliSense which prompts suggestions for code completion. It is easy to step through code using interactive debugger to inspect the root cause of error quickly.
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.
[Microsoft] Visual Studio Code beats the competition due to its extensibility. Their robust extensions architecture combined with the plethora of mostly free extensions written by the community can't be beaten. The fact that this tool itself is provided by a world-recognized company, Microsoft, free of charge is phenomenal. The goodwill garnered by them is immeasurable. Other tools I've used were missing features or were just too rigid, too complicated, or too unsophisticated for my liking. The fact that VS Code is easy to mold to my will with the right extensions seals the deal.
Positive impact on minimizing time wasted by employees with software installation and setup
Positive impact on reducing spend on software licensing
Positive impact on minimizing time used to manage different applications for different purposes - this performs all of the functions we need in basic coding
