Likelihood to Recommend
I think that if someone asked me for an IDE for Java programming, I would definitely recommend Eclipse as is one of the most complete solutions for this language out there. If the main programming language of that person is not Java, I don't think Eclipse would suit his needs[.]
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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.
Read full review Pros Eclipse organizes imports well and does a good job presenting different programming languages. Eclipse auto formats source code allowing customization and increased readability. Eclipse reports errors automatically to users rather than logging it to the console. Eclipse has coding shortcuts and auto-correction features allowing faster software development. Read full review 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. Read full review Cons While the DB integration is broad (many connectors) it isn't particularly deep. So if you need to do serious DB work on (for example) SQL Server, it is sometimes necessary to go directly to the SQL Server Studio. But for general access and manipulation, it is ok. The syntax formatting is sometimes painful to set up and doesn't always support things well. For example, it doesn't effectively support SCSS. Using it for remote debugging in a VM works pretty well, but it is difficult to set up and there is no documentation I could find to really explain how to do it. When remote debugging, the editor does not necessarily integrate the remote context. So, for example, things like Pylint don't always find the libraries in the VM and display spurious errors. The debugging console is not the default, and my choice is never remembered, so every time I restart my program, it's a dialog and several clicks to get it back. The debugging console has the same contextual problems with remote debugging that the editor does. Read full review Canopy does not support Python 3 There were times the Python shell crashed, and I would have to restart it Some Python libraries are slow. Read full review Likelihood to Renew
I love this product, what makes it one of the best tool out in the market is its ability to function with a wide range of languages. The online community support is superb, so you are never stuck on an issue. The customization is endless, you can keep adding plugins or jars for more functionalities as per your requirements. It's Free !!!
Read full review Usability
It has everything that the developer needs to do the job. Few things that I have used in my day-to-day development 1. Console output. 2. Software flash functionality supporting multiple JTAG vendors like J-LINK. 3. Debugging capabilities like having a breakpoint, looking at the assembly, looking at the memory etc. this also applies to Embedded boards. 4. Plug-in like CMake, Doxygen and PlantUML are available.
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I gave this rating because Eclipse is an open-source free IDE therefore no support system is available as far as I know. I have to go through other sources to solve my problem which is very tough and annoying. So if you are using Eclipse then you are on your own, as a student, it is not a big issue for me but for developers it is a need.
Read full review Alternatives Considered
The installation, adaptability, and ease of usage for Eclipse are pretty high and simple compared to some of the other products. Also, the fact that it is almost a plug and play once the connections are established and once a new user gets the hang of the system comes pretty handy.
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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.
Read full review Return on Investment This development environment offers the possibility of improving the productivity time of work teams by supporting the integration of large architectures. It drives constant change and evolution in work teams thanks to its constant versioning. It works well enough to develop continuous server client integrations, based on solid or any other programming principle. Read full review Its easier to define KPI's with Enthought It is good for reiteration and building on top of existing scripts Its dedicated Python console makes it easier to execute projects. Read full review ScreenShots