Python ShortsPython Pro Tip: Want to use R/Java/C or Any Language in Python?Python provides a basic and simple way to handle such requirements where we have to switch to and fro between multiple languagesRahul AgarwalBlockedUnblockFollowFollowingMay 1Python is great.
But the field is getting/will get language agnostic with time.
And a lot of great work is being done in many other languages.
While I still treat Python as a primary language, I never hesitate to move to a different language if it gets the work done.
The fact is that every language has evolved in such a way that it has built its stronghold in certain areas.
For example, Some people may find it easier to use R for regression, or Plot in R using ggplot(Though I sincerely feel Python has come a long way in the visualization department.
)Sometimes it is because a particular library is written in Java/C and someone hasn’t yet ported it to Python.
But is there a better way to handle this constant nuisance?I like Python because I understand it well now.
It is easy for me to do so many things in Python as compared to doing it in R or Java or Scala.
Why do I have to code my data preparation steps in R if I just want to use the Linear Regression package in R?Or why do I have to learn to create charts in Java if I only want to use the Stacknet package?Now Python and R have many wrappers.
How can I use R in Python or How I can use Python in R?.rpy2 and reticulateThese packages are all well and good, and they may solve some problems.
But they don’t address the generic problem.
Every time I want to switch from one language to another I need to learn a whole new package/library.
Not scalable at all.
In this series of posts named Python Shorts, I will explain some simple constructs provided by Python, some essential tips and some use cases I come up with regularly in my Data Science work.
This post is about utilizing a particular package/library from another language, while not leaving the comfort of coding in our primary language.
The Problem StatementI will start with a problem statement to explain this.
Let’s say I had to create a graph using R, but I wanted to prepare my data in Python.
It is a generic problem any data scientist can potentially face.
Do something in one language and then move to another language to do some other thing.
Can I do this without leaving my Jupyter notebook?.Or my Python Script?The SolutionHere is how I could accomplish this.
It might seem hacky to some but I love hacks.
import pandas as pddata=pd.
csv")data = preprocess(data)data.
system command provides me with a way to access my shell using Python.
And the shell is a potent tool at your disposal.
You can run almost any language on the shell.
The corresponding Rscript that will run in python would look something like:data<-read.
png")I can then maybe load the png file and show it in my Jupyter notebook using something like a markdown hack.
png "Title")For R users, who don’t want to leave the comfort of R, R also has a system command analogous to os.
system that you can use to run Python code in R.
system in Python provides us a way to do each and everything in Python by letting us call shell commands from Python.
I have used it in plenty of my projects where I have used this concept to send e-mails using Mutt.
Or to run some Java program or to fiddle around.
It seems like a hacky way, but it works and is generalized enough that you don’t have to learn a new library anytime you want to do something with any other language and get it integrated with Python.
If you want to learn more about Python 3, I would like to call out an excellent course on Learn Intermediate level Python from the University of Michigan.
Do check it out.
I am going to be writing more beginner friendly posts in the future too.
Let me know what you think about the series.
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As always, I welcome feedback and constructive criticism and can be reached on Twitter @mlwhiz.