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In pycharm we can insert a docstring template in any definition of a function by placing the caret in the function name of the definition and hit alt + enter to get to a menu in which one option is to insert a docstring template based on the parameters of the function. The docstring in python can be written for any function and also makes sense outside of package writing. In pycharm we can place the caret inside the name of any function and press ctrl + Q in order to obtain a more well formated pop-up window containing the docstring. In python we can use help(myfunction) or my_function._doc_ to call the docstring associated with a function as console output.
#GOOD IDE FOR R CODE#
Code examples can be copy pasted into the console or can be called via example() In order to generate consistent roxygen2 comments we can use the sinew package which will generate a sensible template from a finished function. This will display nicely as html in an additional viewer window. We can call the documentation of a function using ? for example: ?myfunction(). In R we can only document functions properly when writing a package using roxygen2 comments. This only displays the parameter but we cannot select anything and thus have to type it ourselves. In order to get the parameters of the function we also have to use an additional shortcut Ctrl + P (on windows). pycharm has code completion but it tends to be cluttered with irrelevant object and method names when it does not find anything in the local namespace. spyder’s code completion looks and works exactly like the one of RStdio. You can then select the parameter from the list In python code completion is done by packages like jedi which seems to be what all the IDEs are using however code completion feels a bit different. When you are defining the parameters of a function and you hit Tab RStudio will show you a list of all parameters of the function that you have not defined yet. When you are typing a function it automatically displays the function documentation and which parameters the function is accepting. Git integration is pretty straight forward with more options than in RStudio Code CompletionĬode completion in RStudio is pretty straight forward if you press Tab your namespace is sensibly searched for variables and functions that you might be typing. This requirement is fullfilled by all IDEs. Here we will walk through the features mentioned above and see how they are implemented in pycharm Ploting and interactive variable exploration
#GOOD IDE FOR R PROFESSIONAL#
The professional version offers a scientific mode that also mimicks the RStudiointerface to some degree and that provides a decent project structure. The multi-purpose IDE pycharm however seems to support also the other features that RStudio is capable of.
![good ide for r good ide for r](https://codingclubuc3m.rbind.io/post/2020-02-11_files/figure-html/unnamed-chunk-34-1.png)
There are a couple of python IDE that mimick the RStudio or the Matlab interface such as spyder and rodeo they support plotting and interactive variable exploration and have great code completion but they lack git and markdown support.
![good ide for r good ide for r](https://visualstudio.microsoft.com/wp-content/uploads/2016/06/InteractiveWindow.png)
Python on the other hand has not been primarily developed for data science applications but has some great add-onn packages that can be used for scientific computation. It has been developed just like R especially for maintaining a data-centric workflow. R has with RStudio one obvious candidate for the best IDE to use with R.
#GOOD IDE FOR R SERIES#
In this series of notebooks I would like to document how my best-practices from using R can be carried over to the python universe.