To be honest, what can be done with Python can also be done with Perl or Ruby. I am not working in areas, where there is much better library support for Python than for Perl or Ruby. And I like Perl and Ruby very much and I am somewhat skeptical about Python. But there are some points that make it worth knowing Python in addition to Perl and Ruby, not instead of them.
I strongly recommend using real programming languages like Perl, Ruby, Python and you can add some more instead of Bash scripts, where a certain complexity is exceeded. Try reading the pure bash scripts that are used to start Maven, Tomcat or other useful software. Often there is a CMD-script as well, that is the real pure horror. Python serves this purpose well enough, the other two of course as well.
It is always good to learn new languages once in a while, because they extend our horizon and help us even to be better with our more preferred languages. And why not challenge the preferences…
There is a good point in allowing for a tool box of languages, not „only Java“ or „only C#“ or „only C“ or even „only Perl“, whatever you like… Combining a useful toolbox of several languages is the right way to go. This would be the case with a toolbox containing A and B, where A ∈ { C, C++, Java, C#, F#, Scala, Clojure, …} and B ∈ { Perl, Perl6, Ruby, Lua, Python,…}. Usually it is a good idea to make it slightly larger, but it is also good to find a consensus on which set of languages to concentrate. I would for example discourage using sed and awk, because they can quite easily be replaced by Perl and limit bash to very trivial scripts. There are some cases in which the awk or sed scripting is a bit shorter than it is with doing the same in Perl or Ruby, but this does not justify maintaining the extra knowledge, while Perl on top of Java does justify this a lot. So the toolbox should be big enough to cover everything, but it does not have to be too redundant and there can be preferences what tool is recommended to use for a certain class of purposes, if this recommendation is reasonable. This makes it easier to maintain each others code. Now there are many projects, where the spot of B is taken by Python. So in order to be a good team player it might be useful to be able to work with the python scripts, write in this language and contribute instead of spending too much time talking about why Perl or Ruby or Lua or whatever is better. Which it might be. Or which might be more a matter of taste. Here is what big sites are using as A, B, C,….
Now out of these scripting languages, Python is for sure a successful contender. This results in good libraries, but also in higher likelyhood of Python occupying the spot B.
Now we have tools like Jenkins, Kubernetes, Docker, Cloud computing, Spark and simply certain Linux distributions, which might come along with their preferred set of scripting languages that are well supported for performing certain tasks. This can be delegated to one or two guys in the team or kept to a minimum, but this might become a factor of increasing importance. It might force us to have multiple „Bs“ or multiple „As“.
And there are certain areas, where Python is simply strong and has become the language of choice. It seems to have become the successor of Fortran for many if not most numerical calculation areas, even though there will probably always be a niche for powerful compiled languages like Fortran and C for the ultimative performance. But so the library is written in C with Python bindings and we get most of the performance as well. Also Data Science seems to mostly opt for Python as the general purpose language besides R and SQL and SAS. Even Bioinformatics, which was a stronghold of Perl for many years is now preferring Python… Yes, it does hurt someone who likes Perl, but it is true… So to be able to work in many interesting areas, it is useful to know some Python. So I started learning it. I am using a Russian translation of the book Programming Python.
I might write a bit more about the language, once I have some more experience with it.
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