The way to manage this is to make your code more modular, to factor out subcomponents, to share and have them critiqued separately. For example, in machine learning frameworks, autograd is a separate package for automatic differentiation. I actively post questions and answers for subcomponents on Stack Overflow.
There are still idiots on Github using Python 2 for new projects. These are usually academics who don't actually share any love for technology. Their code will never be used by anyone.
You should be getting ideas from actual open source projects that actually exist, not from imaginary/fake ones. There are numerous serving packages that actually exist and offer ideas.
You will get a lot more ideas from other software that actually do exist. I can easily write a fake blog post with fake thoughts giving you fake ideas, but that's not what you want; you deserve ideas that work.
Uber's software doesn't exist in the public realm, and so there is nothing to learn from it. It is imaginary fluff. I have posted a list of the ones that do actually exist in another comment. And you should've at least got a 1080.
Who cares about this garbage if the tool isn't even open source? There are lots of ML deployment tools that are open source. I know haters will downvote my post, but it's the truth. If I can't actually fork and evaluate a tool, it is hyped up garbage to me.
Meanwhile, here is a list of open source ML deployment packages:
I detest the overall HN commenting community. You may be an exception. They're always downvoting and shadowbanning. I am reluctant to share much useful info here.
https://github.com/tensorflow/adanet looks effectively modular to me, although I wouldn't consider it the epitome of the same. One needs to be able to merge, move, and remove modules too.
I completely agree. For a DataStore in Python, I may often use a Pandas DataFrame or such. For random label-based access it can have an index too.
Unfortunately, when asked to design an OOP architecture in a job interview, if you don't adhere to its religious enterprisy notions, you can risk failing the interview.
It's collisions that trigger a runaway Kessler syndrome. Collisions have happened before and they are a serious concern. Just ask the inhabitants of the space station, for example. Probability dictates that sooner or later, something or someone will run into you. I don't think Starlink is doing all that they can to safeguard their satellites, especially considering that managers were fired for not prioritizing quality over speed.