Likelihood to Recommend 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.
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IDLE is a good option to run small scripts directly on the console, and that's it. It is a good exit when you don't want or need to open a proper IDE like Pycharm.
Read full review Pros 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 Python Software Foundation
Firstly, I would say Python IDLE interface is user friendly. Easy to learn for the beginners. Syntax highlighting is nice features. Smart indent helps a lot. Read full review Cons 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 Python Software Foundation
Too simplistic Could not find source revision management integration support Only basic debugging is available Does not have data-science-specific notebooks (but can be installed separately) Read full review Usability Python Software Foundation
The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.
This IDE allows you to configure the environment, font, size, colors, .....
It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.
Once the IDE is executed you can start programming directly in it.
Read full review Support Rating Python Software Foundation
Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.
In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.
As this IDE is made in Python, the support is the same group of Python developers.
Read full review Alternatives Considered 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 Python Software Foundation
It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer
Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run
Jupyter Notebook on my cloud desktop
Read full review Return on Investment 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 Python Software Foundation
In a short time, we were able to develop several ML models for various teams to make accurate decisions. Beginners can easily understand and adapt to GUI. We could automate several manual validation tasks and so could reduce human intervention. Read full review ScreenShots