This Python code shown above, when executed, generates itself, shown below. This is what's called a quine. It is the kind of self-replicating system which is fascinating both philosophically and technically. The term quine was introduced by Douglas Hofstadter in his book, "Geitel, Escher, Bach." The idea of quines is echoes of self-replication in biological cells, where the cell contains data in the form of DNA and code in the form of biological processes which replicate that DNA.

In the same way, the computational self-replication of a quine contains two elements. One is the code that performs the replication, and two is the data that contains all the raw materials for performing the replication process. So like I said, most quines have a data part and a code part.

So let's look at this elegant Python quine. The data part is the string of the program, and the code part is the print statement that prints that program. So let's look at a basic example of the structure. The string is test%r, or %r is the repper function that returns a printable representation of the object that's passed.

So when we execute this command of assigning the string to the variable s, and then print the string s, after passing itself to itself in a repper version of itself, and so the output of this code is test%r, with the test%r in quotes, which is the repper version of the argument.

Now we can move back to our quine with the same exact structure of a string, but this time the string contains also the print statement with a double percent sign, which when printed, results in a single percent sign. So this code, once again, after you pass the repper version of the string to itself, results in a print of the entirety of the code.

The recursive nature of this self-replicating piece of code has the beauty and the power that echoes the process of biological cell replication. I should briefly mention that there's a lot of ways of creating quines. The one I showed is the one I believe is the most elegant. There's also cheating ways of creating quines, which is, first of all, an empty program in many programming languages, including Python, is a quine itself.

Nothingness, in a way, is forever effectively replicating itself. Also another obvious way is to put the code of the program into a file and then to print the contents of the file in which the code resides. Now this is actually officially considered to be cheating and not allowed to be in a quine.

The quine has to be self-sustained. Now let me wrap up this video with the idea of an intron, which is code that you can inject within a quine that will replicate as part of the replication procedure, but does not actually contribute directly to the function of the quine. So it rides along for free, like a virus or a non-functional part of the genome in a DNA, without directly contributing to the replication of the code.

Now this particular piece of code does more than just provide an intron. It takes the input from the user and adds that as an intron into the quine. Now the exact function is used here for brevity. So let's run this code. When we run it, it's waiting for the user input.

If we just press enter, it generates the code itself, so it's a proper quine. If we run it again and provide input, like we live in a simulation, what you see is that the variable T now has a we live in a simulation string attached to it, and the entire program remains a proper quine.

So if we copy it and run this program, it waits for the input. Now if we keep the same input, it generates the quine again successfully. Now we can run the same kind of quine with the we live in a simulation, and instead provide a new text, 42. The resulting output is a quine as well with a variable T now assigned the number 42.

Now to me, quines and introns make me think about the source code of our own life here on Earth. And so I hope you may find this interesting and beautiful as I do. I may very well make a few more videos about quines, like multi-quines, polygon quines, quine relays, and other things that I find interesting in the space of computer science, mathematics, physics, artificial intelligence, machine learning, and even psychology, history, philosophy, biology, chemistry, and so on.

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