The Handlers implement behavior, sure. But from the perspective of the `app` object, the handler function objects are state. You can tell, because `app` is an instance of the Flask class and the Handlers are added to the instance by way of a function call.
So, Handlers are functions that "handle something", but they are also part of the app object's state, not its behavior.
Handlers are functions that are part of the app object's state, which alters the app's behavior.
In the majority (possibly overwhelming majority) of the cases this is true. The purpose of Handlers and similar Publisher/Subscriber patterns is effectively to change application behavior when they are configured.
But that's missing the GP's forest for the trees (pun intended). Liu Cixin's work popularized the theory and phrasing by a massive amount both in comparison to the works that came before and as well as after.
The core point seems to be the flippant assignment of origination irrespective of the scale of contributions.
How is that not just as flippant an “assignment of origination”? Regardless of how Liu Cixin might have written the most popular treatment of the theory, he did not come up with it, and stood on the shoulders of many others who developed the idea over decades. I have no problem with giving him credit for popularizing the idea but calling it “Liu Cixin’s Dark Forest” is going too far.
Everyone knows the real originator of the Dark Forest theory was Chet, more specifically his cat.
(For those who haven't read Xtreme Programming, Chet would stumble into meetings that had degenerated into unproductive fingerpointing, and exclaim "Woops! My fault. WTF are we gonna do to fix it?", Even if he had nothing to do with it
Everything. Bad. Is. Chet's. Fault.
Also, anything good, is solely the work of Chet's cat.
Embracing this truth has greatly simplified my life.
If Chet did not, in fact, have a cat, then I must have fallen into another alternate universe again. Replace the animal in question with whatever you deem most appropriate.
I've been experimenting a lot with using Jupyter Notebooks (http://jupyter.org/) to get many features of literate programming.
The tooling can be a bit clunky -- though JupyterLab and some plugins can go a long way. Importing notebooks into other notebooks or modules is still kind of weird even with the `ipynb` library.
However, on the otherside of it all, you have a collection of documents that contain documentation, code, and tests, all side by side and storable with proof of past execution.
I'll take this arrangement over someone's unit test and CI suite every day of the week.
Landscaping is a perfect example of how an individual can instantaneously create value in the economy. Banks can create currency, but individuals can magically create value.
How? Decide you want your yard to look different. On a whim. Just decide you want a hill over there with a ring of bushes on top. Congratulations, you have created demand. Pay a local crew to have it done, money flows into the economy, everybody eats.
For greater effect, manufacture a cultural preference so that entire country clubs of people at a time decide that all hills need bonzai trees at their crest -- have all the clubbers pay all the landscaping crews.
Python's organic growth and adoption is more of an OpenCola model.