I've been programming only in Python for a while now. I got a certificate that required digging into the language enough to do the code in your head. I code pro

I've been programming only in Python for a while now. I got a certificate that required digging into the language enough to do the code in your head. I code projects in VS Code. I've enjoyed it, esp library availability. I do warn people that it's not as easy or intuitive as advertized. I've often been bitten by unexpected errors. I think a survey of these might be worthwhile. One was typing or conversion errors. Some conversions, like int-to-str in a string concantenation, seem pretty obvious. That isnumeric() didn't consider negative numbers as numbers was a surprise. Sometimes it's consistency. I've often alternated between lists and sets in applications. I prefer to keep most data as a list but use sets for uniqueness checks or redundancy filtering. Despite being collections, one uses .append() and one uses .add(). Little differences not only add confusion: I have to modify my codebase if mixing or switching them which can become a type error later in another spot. Another were common operations usually in one place were split across two. That happened with time vs datetime and filesystem operations which might take two modules. I've considered making a wrapper that turns all those into one thing with internal redundancy removed. There might be a reason others haven't done that, though. Another issue was distribution. I can do straightforward building of console apps for two platforms. That's reliable. If worried about reliable, Python apps seemed easier to deliver as a Flask site than distribute my utilities as standalone. Nikita was really impressive, though, in terms of the work that must have went into it. In my case, I also missed the ability to easily make linked lists in C to build trees. I wanted to build a C-like tree in Python but it couldnt do self-referential structures IIRC. Since that app requirements were C-like, and performance was no issue, I actually simulated a C-like heap in Python, ported a C tree to it, and build the tool on that. I also got a use-after-free in Python of all things lol. Anyway, I was surprised there was a data structure C could do but a high-level, GC, reflective language couldn't. There might be a trick for this others know about but I figure they just wrap C code for those things. On the positive side, the debugging experience with Python was so much better than some beginner languages. I'm grateful for the work people put into that. I also love that there are easy to use accelerators, from JIT's to the C++ generator. I was wanting an acceleratable subset with metaprogramming when Mojo appeared. I might try it for toy problems. I gotta try to stay in idiomatic-ish Python for now, though, since it's for career use.