Indeed, these capabilities of the language are some of its strengths, even if we don't all trust ourselves to use them. The casual programmer doesn't know how or why numpy works, and we don't play with magic methods except out of curiosity. The people who do maintain numpy are using more formal methods to ensure its quality.

In the case of Python, the things that professional caliber programmers can use to extend its functionality, and the things that the rest of us can use to be productive, are the same language and are not hidden from one another. This is not the case in some languages of the past, e.g., you could use objects in Visual Basic but not build them without another language or eventually a special version.