if those 8 lines of regex have been unit tested and the function is commented to describe "what" the code does, it is entirely the point that you don't need to understand how it works

additionally, the function should be stateless and have no side effects ;)

That's fair. But maybe someone wants to reuse this in another place so they do this:

``` def make_string_filename(s, style="new"): # 2 lines of shared magic if style == "old" # 2 lines of original magic elif style == "new": # different 2 lines of magic ```

When you get here, two totally separate `make_string_filenames()`, each private to the area of code they're relevant to, would be better.

Now the next genius turns up and says that make pizza is at it's core always a n-step domain process.

So now you've dumped it down to an interface with a default implementation which calls the create_dough, add_toppings, bake_pizza interfaces in order, each of which are either passed in callbacks or discovered through reflection.

We can even sprinkle in some custom DSL to "abstract away" common step like putting the product into the oven correctly!

Jr's will never understand when why and what is effectively excecuted at runtime. Honestly, at this point I enjoy working with this kind of code. It's always such a high entertainment value and I get paid by the hour, so whatever

This is discussed in detail in "The Wrong Abstraction" by Sandi Metz

https://sandimetz.com/blog/2016/1/20/the-wrong-abstraction

Quote follows:

----

The strength of the reaction made me realize just how widespread and intractable the "wrong abstraction" problem is. I started asking questions and came to see the following pattern:

1. Programmer A sees duplication.

2. Programmer A extracts duplication and gives it a name. This creates a new abstraction. It could be a new method, or perhaps even a new class.

3. Programmer A replaces the duplication with the new abstraction. Ah, the code is perfect. Programmer A trots happily away.

4. Time passes.

5. A new requirement appears for which the current abstraction is almost perfect.

6. Programmer B gets tasked to implement this requirement. Programmer B feels honor-bound to retain the existing abstraction, but since isn't exactly the same for every case, they alter the code to take a parameter, and then add logic to conditionally do the right thing based on the value of that parameter. What was once a universal abstraction now behaves differently for different cases.

7. Another new requirement arrives. Programmer X. Another additional parameter. Another new conditional. Loop until code becomes incomprehensible.

8. You appear in the story about here, and your life takes a dramatic turn for the worse.

Existing code exerts a powerful influence. Its very presence argues that it is both correct and necessary. We know that code represents effort expended, and we are very motivated to preserve the value of this effort. And, unfortunately, the sad truth is that the more complicated and incomprehensible the code, i.e. the deeper the investment in creating it, the more we feel pressure to retain it (the "sunk cost fallacy"). It's as if our unconscious tell us "Goodness, that's so confusing, it must have taken ages to get right. Surely it's really, really important. It would be a sin to let all that effort go to waste."

Some languages handle massive parameter lists better than other (ex with defaults). There are also design patterns for this type of problem (ex a PizzaBuilder).

100% agree and I just wrote this response and then saw you said it better!

Exactly this. I fixed a problem like this a week ago. I found some duplicated code, factored it out into one place by introducing an abstract base class (Python) and in the process discovered one of the duplicated methods had a logic error leading to returning a slightly smaller integer result.

The code had test coverage, but the test confirmed that it produced the wrong result. I had to fix the test too.

in a sense yes, in a sense no. if you see a function and know its sort of black box properties and its inputs and outputs are well defined, you really don't need to care. however, that applies whether the code is in an external function/module or physically inlined into your code. the sectioning off into separate code is then there to forcefully tell the reader "don't even try to care about the implementation details of this", so in practice your point still applies.

however... real software doesn't work like this. the abstractions that work that way exist for a select few very well understood problems where a consensus has developed long before you're looking at any code.

math libraries would be a typical example. you really don't need to know how two matrices are multiplied if you know the sort of black box properties of a matrix.

but the minute functions, classes, and other ways of abstraction code in a DRY way that you encounter constantly in everyday code, even if they are functionally actually well abstracted (meaning it does an isolated job and its inputs and outputs are well defined), even for simple problems, are typically complex enough that learning their abstract properties can be the same level of difficulty and time investment as learning the implementation itself. on top of practical factors like lack of documentation.

this is also why DRYness as a complicating factor really doesn't factor in once the abstracted code does something so complex that there is no way you could even attempt to understand it in a reasonable amount of time. like implementing a complex algorithm, or simply just doing something that touches too many lines of code. in this case you are left to study the abstract properties of that function or module anyways.

> If I can trust what make_pizza does

You can't, unless it's in a standard library or a core dependency used by millions of people.

That's one of the reasons why functional code is generally easier to read. A lambda defined a few lines above whatever you're reading gives you the implementation details right there while still abstracting away duplicate code. It's the best of both worlds. People who's idea of "functional programming" is to import 30 external functions into a file and compose them into an abstract algorithm somewhere other than where they're defined write code that's just as shitty and unreadable as most Java code.

Not all the time. When the similar code mixes types and the common codepaths are sprinkled multiple times over it you can either have the code there twice, or have an overcomplicated templated common function.

In these cases factorizing may or may not be a good idea.