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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IntelliJ IDEA
Score 9.3 out of 10
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IntelliJ IDEA is an IDE that aims to give Java and Kotlin developers everything they need out of the box, including a smart code editor, built-in developer tools, framework support, database support, web development support, and much more.
$19.90
per month
Pricing
Enthought Canopy
IntelliJ IDEA
Editions & Modules
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For Individual Use (Monthly billing)
$19.90
per month
For Organizations (Monthly billing)
$71.90
per month
For Individual Use (Yearly billing)
$199
per year
For Organizations (Yearly billing)
$719
per year
Offerings
Pricing Offerings
Enthought Canopy
IntelliJ IDEA
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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All Products Pack (For Individual Use) – $299 /1st year, $ 239 /2nd year and $ 179 /3d year onwards
All Products Pack (For Organizations) – $979 / year
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.
This is a superb tool if your project involves a lot of backend development, especially in Java/Spring Boot and Kotlin. The support for the front end is great as well, but some developers may prefer to use the GitHub copilot add-on. I especially love using the GitHub copilot add-on. It may be less appropriate if your project requires heavy use of HotSwaps for backend debugging, as sometimes the support for that can be limited.
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.
Unit testing: Fully integrated into IntelliJ IDEA. Your unit tests will run smoothly and efficiently, with excellent debugging tools for when things get tricky.
Spring integration: Our Spring project using Maven works flawlessly in IntelliJ IDEA. I know firsthand that Apache is also easily and readily supported too. The integration is seamless and very easy to set up using IntelliJ IDEA's set up wizard when importing new projects.
Customization: IntelliJ IDEA comes out of the box with a bunch of handy shortcuts, as well as text prediction, syntax error detection, and other tools to help keep your code clean. But even better is that it allows for total customization of shortcuts you can easily create to suit your needs.
VS Code is maturing and has a Scala plugin now. The overall experience with VS Code - for web development at least - is very snappy/fast. IntelliJ feels a bit sluggish in comparison. If that Scala plugin for VS Code is deemed mature enough - we may not bother renewing and resort to the Community Edition if we need it.
There is always room for improvement, but I haven't met any IDE that I liked more so far. Even if it did not fit a use case right out of the box, there is always a way to configure how it works to do just that.
Customer support is really good in the case of IntelliJ. If you are paying for this product then, the company makes sure that you will get all the services adequately. Regular update patches are provided to improve the IDE. An online bug report makes it easier for the developers to find the solution as fast as possible. The large online community also helps to find the various solutions to the issues.
This installs just like any other application - its pretty straight forward. Perhaps licensing could be more challenging - but if you use the cloud licensing they offer its as simple as having engineers login to the application and it just works.
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.
Eclipse is just so old, like a dinosaur, compared to IntelliJ. There are still formats that Eclipse supports better, especially old and/or propriety ones. Still, most of the modern software development needs can be done on IntelliJ, & in a much better way, some of them are not even supported on Eclipse.
