One day, a friend introduced me to Python, calling it a "friendly programming language for beginners." I remember spending my first few hours writing simple scripts, and though it was challenging, I was hooked. For the first time, I could see the immediate result of my efforts, and it felt incredibly empowering. At 23, I made a bold decision. I started teaching myself programming in earnest while still juggling my other responsibilities. I took online courses, read books, and spent hours practicing. I made countless mistakes and encountered errors that felt insurmountable, but I learned to see them as puzzles to solve. By the time I turned 24, I landed my first job as a junior developer. It wasn’t an easy journey, but it was one of the most rewarding experiences of my life. Programming taught me not only technical skills but also how to think critically and approach problems methodically.

That's nice.

I'm very grateful for having programming as interest too. It's cheap, it's limitless, you can do it everywhere and it pays well. In general I do like programmers, that's also a plus.

I discovered qbasic myself on a old computer and my dad had programming experience in gw basic. Those factors together was my start.

I just made an ipython environment and made ipython execute under pipx when I type `python` in shell. Now, I have by default my favorite libraries available and rpc clients to my web services. I only have to type `vic.get_spammers()` to get a list of all spammers on devRant for example. By default i've included pathlib and pathlib.Path, pprint as pp, os, sys. No import errors for me anymore while typing in the CLI. And it is so cool that the CLI remembers history. So with a few times `arrow up` i can see the lines of my previous session and can execute them again.

Do you use IPython as well?

@yulia I’ve used IPython occasionally, especially when I’m working on data analysis or need a quick interactive Python environment. I also find myself switching between IPython and Jupyter notebooks depending on the task. Jupyter is great for more exploratory work, while IPython is great for a fast iterative workflow.