I am currently in the midst of transitioning from R, my preferred programming language, over to Python. While the syntax of the languages is similar, I was quickly overwhelmed with the choices of Integrated Development Environments (IDEs) and text editors for Python. Choosing an IDE is a deeply personal choice and the one you choose depends on your skill level and programming needs. I have tried out many different IDEs, and, for the purpose of making a smooth, intuitive, transition from R to Python, the best one for me was Spyder (Scientific Python Development Environment). In this blog post, I will give an overview of the Spyder environment and step through some of its functionalities.
The easiest way to install Spyder is through a Python Scientific Distribution found here. There are three options, but I chose to install Anaconda which gives you the core Python language, over 100 main Python libraries, and Spyder. It is an incredibly efficient way to get everything you need in just one download and works for both Windows and Mac. Once this is installed, you can open Spyder immediately.
The first aspect that I like about Spyder is how similar it looks to RStudio and Matlab, as shown in Figure 1. This made the transition very easy for me. As shown in Figure 2, the Spyder environment is comprised of a collection of panes which can be repositioned by dragging if a different format is more intuitive to the user. To see which panes are open, click View->Panes. The most useful panes will already be open by default. You can choose to keep either the console or the IPython console. This is a matter of preference and I chose to use the regular console.
At the top of the screen is your directory, which, by default, is set to the folder which contains Anaconda. You can change it to your preferred location on your computer by clicking the folder icon next to the drop down arrow.
The leftmost pane is the editor which is where code can be written. The Spyder editor has features such as syntax coloring and real-time code analysis. By default, a temporary script, temp.py, will be open. Go ahead and save this in your current directory. Make sure that the file shown in the gray bar matches your directory (shown in Figure 3).
Let’s write a simple script to test out the environment (shown in Figure 4).
Click the green arrow at the top of the screen to run the script. A box will pop up with Run Settings. Make sure the working directory is correct and click “Run.” If you just want to run a certain section of the script, you can highlight that section and click the second green arrow with the blue and orange box.
The results from the script will appear in the console, which is my bottom right pane. The user can also execute a command directly in this console.
Object Inspector/Variable Explorer/File Explorer
The last major aspect of the environment is the top right pane, which is a comprised of three tabs. The first tab is the object inspector, which is analogous to RStudio’s “help” tab. You can search for information on libraries, functions, modules, and classes.
The second tab is the variable explorer, which is the same as RStudio’s “Environment” tab. This tab conveniently shows the type, size, and value of your variables. The results from our test script are shown in Figure 7.
Finally, the last tab is a file explorer which lists out all of the files and folder in your the current directory.
Debugging with Spyder
The Python debugger, pdb, is partly integrated into Spyder. The debugging tools are located in blue, adjacent to the green “run” buttons. By double-clicking specific lines in the code, the user can set breakpoints where the debugger will stop and results from the debugger are displayed in the console.
Those are the main components of Spyder! As you can see, it is a fairly uncomplicated and intuitive IDE. Hopefully this overview will make the transition from R or Matlab to Python much easier. Go forth and conquer!