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leftovers

#8: Algorithms

There are plenty of great books that believe it’s impossible to learn
about programming without also learning about algorithms.
The word “algorithm” is used to describe a precise and established
way of solving a particular problem in any programming language.
It’s often useful to think of an algorithm as a recipe.
In the good ol’ days, it was certainly true that every programmer had
to have a good grasp of algorithms in order to get anything of any
worth done. But, luckily for you, this is no longer the case.
Nowadays, with programming technologies such as Python (and
Ruby, Perl, Java, and C#), this is less of an issue because modern
programming languages just do so much for you.

For instance, if you need to sort something in Python, you either
call the sort() method on a object or use the built-in sorted()
function, and the thing you are working with is duly sorted. You are
probably less concerned (and rightly so) with how the sort actually
occurred—that is, with the details of the algorithm used to sort your
data. Was it the quicksort algorithm or the bubblesort? Maybe it was
timsort or something else entirely? Maybe you don’t care, because
calling sort() or using sorted() orders your data in the way you
desire and frees you to move onto some other problem that needs
solving.
You could take the time to write a really cool sort function and learn
lots about algorithms in the process but, let’s face it, life is far too short.
If you want to write your own programming language, you’ll need
to learn lots about algorithms. If all you want to do is use an existing
programming language (like Python), you can worry less about
algorithms and more about writing code, which is precisely how it
should be (in our opinion).

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