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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Sublime Text
Score 9.2 out of 10
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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.
My CMS has a small window in which I can edit custom HTML/CSS. It can be expanded some, but not as much as I would like. It also displays all code as dark text on a white background. On a page where I am doing extensive custom coding, it is helpful to see it in a larger window and in a color-coded display so that I don't have to strain my eyes as hard. Especially when I'm trying to scan for specific elements and target issues and so that I don't have to scroll endlessly in a tiny window.
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.
This is a programmers tool. As such a lot of the features and benefits are lost on a non-technical user. To get the most out of the tool you need to have a basic crash course in how it works and what it can do. The documentation and community are good, but it takes a bit of time to get up to speed.
Never had to use their customer support before. There is ample documentation online so it's straightforward to find a solution to any problem you might encounter. For example, I needed to convert a string of HTML code to a properly formatted HTML file to "modify." Easy to do when there are so many users of the product who have needed to do that same thing before.
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.
We've used both Notepad++ and Atom; both are great but nothing really beats the Sublime Text UI; super intuitive and friendly and does everything you need without overwhelming you with stuff you don't. Other options are free, but for our organization, it was well worth the small license cost for the persistent use of a great product.
Sublime Text has helped me to focus on specific tasks, cutting out the clutter that many other IDEs have. As such, it has helped me be a more productive employee because I don't get dazed by hundreds of buttons. I can focus on just the code.
Sublime Text is so affordable that it's a no-brainer to have an extra tool in your toolset.
The Search features of Sublime Text are so useful that it has saved me a great amount of time compared to using Find & Replace menus in Xcode, Android Studio, or Eclipse.