I am not sure of historical significance of what OOP is, but even Alan Kay seem to agree that modern definition of OOP is not what he intended[1]. But, for better or worse we are stuck with the principles.
We even have design patterns like Command, to workaround first class functions in "pure" OOPy way.
And for enterprise software development, I like it that way. It can make up a definition it wants and stick to it. I think it is better for a language's ecosystem and culture to have one dominant paradigm than becoming kitchen sink of programming languages.
As a java guy and think python is weird, I don't think this sucks.
But, I also agree that can serve as terrible intro to programming if you start programming right away without understanding the basics of abstractions. But, often when we have tools either designed for a purpose in mind or a dominant paridigm or reaction to existing set of tooling, this can result in understandable yet extreme abstractions.
Java is designed with OOP in mind and it kind of makes sense to have the user to think in terms of lego blocks of interfaces. Every method or class needs to have clear understanding of its users.
public - software handle is for all users
protected - software handle for current and extending classes
default - software is exposed to current package
private - software is restricted to be used in current class alone and nowhere else
So, the beginning of java programming starts with interface exposed to the user or other programmers. Is it weird and extreme. Yes. At least, it is consistent.
Another thing that impedes us sunken cost fallacy. Classic "Simple vs easy" change. Even if a design is comparatively simpler, it is harder to make such change for small feature.
We had a project which is supposed to convert live objects back into code with autogenerated methods. The initial design was using a single pass over the object graph and creating abstractions of HDL and combining method blocks in the same pass.
That is a big hairy code with lot of issues. Simpler would be to handle one problem at a time - method generation in one pass and then convert the methods to HDL. But, getting approval for a deployed app is so hard. Particularly when it is a completer rewrite.
I think I have mentioned this before in HN too. I am not from CS background and just learnt the trade as I was doing the job, I mean even the normal stuff.
We have a project that tries reify live objects into human readable form. Final representation is so complicated with lot of types and the initial representation is less complicated.
In order to make it readable, if there is any common or similar data nodes, we have to compare and try to combine them i.e. find places that can be made into methods and find the relevant arguments for all the calls (kind of).
Initial implementation did the transformation into the final form first, and then started the comparison. So, the comparison have to deal with all the different combinations of the types we have in final representation now, which made the whole thing so complex and has been maintained by generation of engineers that nobody had clear idea how it was working.
Then, I read about hashmap implementation later (yep, I am that dumb) and it was a revelation. So, we did following things:
1. We created a hash for skeleton that has to remain the same through all the set of comparisons and transformation of the "common nodes", (it can be considered as something similar to methods or arguments) and doing the comparison for nodes with matching skeletal hashes and
2. created a separate layer that does the comparison and creating common nodes on initial primitive form and then doing the transformation as the second layer (so you don't have to deal with all types in final representation) and
3. Don't type. Yes. Data is simplest abstraction and if your logic can made into data or some properties, please do yourself a favor and make them so. We found lot of places, where weird class hierarchies can be converted into data properties.
Basically, it is a dumb multi pass decompiler.
That did not just speed up the process, but resulted in much more readable and understandable abstractions and code. I do not know, if this is widely useful but it helped in one project. There is no silver bullet, but types were actual problem for us and so we solved it this way.
> There are some aspects that have some similarity to computation, but also many that are not.
What I have explained is the exact way a chromosome works, it's raison d'etre. I think this cannot be dismissed as some aspect of it. It is its essence.
I did try to ask are we not computers. I tried to imply, in the fundamental level there are striking similarities to computation.
> That’s not to say that computers couldn’t do what the brain does, including consciousness and emotions,
Yes. Fundamental building blocks are simple and physical in nature and follow the computational aspect good enough to serve as nice approximations
> but that wouldn’t have any particular relation to how DNA/RNA and protein synthesis works.
Hmm... transistors are not neural networks so? I am sorry, I am a non native speaker and maybe I am not communicating things properly. I am trying to say, the organic or human is different manifestation of order - one is chemical and other is electronic. We have emotions and consciousness, but we can agree we are made of cells that send electric pulses to each other and primitive in nature. And even emotions and beliefs are physical in nature (Capgras syndrome for example).
I meant to say in the way that there is well defined set of alphabets (A, T, G, C) and each triplet of these alphabet is responsible for specific protein to be created and combination of such protein make each cell what it is. (There are 20 different proteins for humans and we have four alphabets coming in triplets. So, if it was pair or quadreplets responsible for proteins, it would have too much or too little. They are not perfect but given the condition, there is some balance)
A single alphabet change in specific places can cause genetic defects like sickle cell anemia. And activation of which one has to generate protein (execute) is dependent on presence of certain things encoded as proteins again.
And viruses when enter a cell, the cell starts to execute viral genetic material. Even if these are not exactly Turing compatible, do they not mimic many aspects of computation?
Are cells not computers in some way? We are made of cells and cells work with chromosomes. Chromosomes are coded with ATGC pairs and each triplet is capable of creating proteins.
And the activation and deactivation of some triplet happens on response to presence of proteins. So, chromosomes are code and input and output is proteins. So, if our fundamental building blocks are computable in nature, what does it make us?
Thanks a lot. It is really fun. But, I don't have adult company in my neighborhood.
If take "What if I don't became great with this" anxiety out of the equation, it feels just more fun and life seems a little more colorful being a beginner.
> I was decent in math and Bill was brilliant, but I spoke from experience at Wazzu. One day I watched a professor cover the black board with a maze of partial differential equations, and they might as well have been hieroglyphics from the Second Dynasty. It was one of those moments when you realize, I just can’t see it. I felta little sad, but I accepted my limitations. I was OK with being a generalist.
> For Bill it was different. When I saw him again over Christmas break, he seemed subdued. I asked him about his first semester and he said glumly, “I have a math professor who got his PhD at sixteen.” The course was purely theoretical, and the homework load ranged up to thirty hours a week. Bill put everything into it and got a B. When it came to higher mathematics, he might have been one in a hundred thousand students or better. But there were people who were one in a million or one in ten million, and some of them wound up at Harvard. Bill would never be the smartest guy in that room, and I think that hurt his motivation. He eventually switched his major to applied math.
Yeah, but these are also about people who are not even starting off at a field. These are teenagers. It really stood out that they can think where they can make most impact in the world at such an young age.
Excuse me for generalizing the point. That's not fair to do just based on these anecdotes. But, I can also understand their perspective.
Paul continued to be a guitar player all his life and hosted jamming sessions in his home. I started with piano very late in my life and not very regular, but I am just happy to join the fun party.