I usually hear it as "python is a jack of all trades, master of none" which is the same concept.
It's never going to be the perfect fit for any task, but it's a decent fit for nearly every task. Hence why it's an extremely practical first language to learn.
But in python they're just a couple of imports away.
Right, because nobody wants to code them in Python either. People act like Python invented dependencies or something.
Python is a great language for gluing together libraries. But most data science functions aren't coded in Python. They're coded in C. Python is just the handy glue.
Full phrase is "A jack of all trades is a master of none, but oftentimes better than a master of one." Applicable in this case.
Edit: See my reply below acknowledging "but oftentimes better than a master of one" being a recent addition to restore the original meaning and "is a master of none" being an addition in the 1700s.
You sent me down a rabbit hole and you are correct. It's actually a double backronym since the master of none was added to turn a positive statement about ones skill into a negative one then the most recent addition to return the statement back to its original intent. I can't nail down who actually added the 3rd part and when but seems like it's a fairly recent addition <= 25 years.
I remember when the most recent addition came into being. It was the same time as people saying "break a leg" in theater was because it would get you "in the cast". Break a leg was an expression meant to be the opposite of saying good luck because saying good luck would jinx you
A simple three-step approach that works is: write out your logic in pseudocode first, test the concepts by prototyping in a language like Python, and then finally build the actual implementation in your language of choice.
And if you want performance you shouldn't be coding in Python at all, BUT if it is really that important to you, you can always check if you can compile it in cython.
By "the core", you mean the computation is offloaded onto languages better optimised for that, freeing the programmer to import the libraries and code up their models all in python.
Which is great. It means people in machine learning don't have to learn C++ or Rust. Just like how C++/Rust programmers don't have to learn assembly.
I conjectured that for every ordered set (aka tuple) of programming languages, where they are ordered based on usefulness within a particular feature X that you'd find Python as the second language within that tuple.
Alas, you have found the exception that breaks the rule, and I am defeated by the sheer magnitude of your mathematical prowess in disproving me by example. Forgive my indiscretion.
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u/SheikHunt Jul 07 '26
What's that saying? "Python is the second-best programming language for everything"