I cannot count how many times CSV "format" has caused problems for me..
In my country the decimal separator is comma, instead of punctuation.
This causes problems when importing and exporting with this "format".
Just few weeks ago I had fun times working with API returning CSV in unknown encoding. Hopefully they will never make changes (you cannot always trust headers). Ah and i do love when CSV is missing headers and someone adds data into middle.
Of course some of these issues can be avoided by doing the things "right". Sadly you cannot trust this in real life. People write ugly structures in JSON, but at least you can validate results..
I have same way of estimating tutorials and similar content. There are quite many people posting videos without real understanding what they are teaching..
I am an engineer/developer and practically work solo in many projects.
Last year I started using the Docker at work. Before docker, all services were installed manually on physical/VM server machines.
Getting my head around Docker took some time, but I feel that it was time well spent.
I started with composes, but moved to docker swarm (single node) for having configs/secrets. Currently I manage everything with the Portainer, that allows me to control all the swarms and services with relatively easy way.
After the working stack is created and tested on the development server, installing it Into one or multiple production servers is quite easy. Depending of the case ugrading services is relatively safe as you can rollback to previous images if you or someone else messed up.
The nicest thing for me, is that all dependencies are inside the image. No need to worry about conflicting versions or setting up same thing multiple times. Sadly you still need to be aware of any security related issues that might exist within the image and maintain them. But this same issue does exist outside of Docker as well.
However, if you don't understand or think what you are doing, it is still possible to screw yourself in many ways. But I feel that this is always possible in our field, no matter what tools you are using.
While the Docker is not a silver bullet, it has made my life a bit less stressful. And I think it is important to understand what you're setting up and how you are doing it. Personally I would not want to go back to my old workflow.
Ps.
Sadly the swarm is deemed by many to be dead. It is relatively easy to manage by a single person and I am not getting the same feeling from alternative solutions, such as Kubernetes.
While there are issues within Python side, I think it is quite unfair to use numpy as an example.
My reasoning is that the numpy project is meant for scientific and prototyping purposes, but many times people are using it as an shortcut and include the whole thing into their project.
That being said, the quality in these packages does vary depending on who developed them. But I think this is a problem that exists with all languages where publishing packages is relatively straightforward.