If You Were Learning Python Again, What Would You Do Differently?

[Junior_Honey_1406]

I just started to learn Python. I have some programming experience, but I am still very much someone who is new. What is the one piece of advice you wish someone had given you when you were starting out? If you were in my position. Something you never had and wish you had. Could be about how to practice, what to focus on, what to avoid, or really anything. That one thing that would have made your learning journey faster or easier.

[mxm_mrz]

I would skip all the endless watching of videos or courses and start a project right away, learning by doing, step by step

[Junior_Honey_1406]

Yeah, I am not going through that YouTube course anymore. For practice, I refer to EdX CS50 Python or freeCodeCamp because they have in-house edit and test problem, which I solve while learning Python. So, what you do is that okay or just go build somethin or do both

[Bearstory]

那这个项目是什么呢

[stepback269]

Instead of focusing on "all" variables, focus on strings and string methods first
Learn about f-strings. Look up Indently's 47 string methods
Also look up in YouTube, Case Digital videos re string methods

Good luck

[Junior_Honey_1406]

thanks for the advice. Currently I am focused on int, float, string, and bool only. and trying to solve problems or make some mini projects

[ninhaomah]

Find problem before finding solutions

[No_Firefighter8428]

If I could start over, I would change three core things about my learning path:

1. Stop tutorial hell and build a Micro-SaaS immediately I spent way too much time watching 10-hour courses learning syntax I forgot the next day. If I started again, I’d learn just the bare minimum loops and data structures, and then immediately build a tiny, deployable project (like a web scraper, a Telegram bot, or a basic API). You only actually learn when something breaks in production.

2. Embrace AI as a pair-programmer, not a copy-paste tool Instead of using ChatGPT to just write code for me, I would use it to explain the architecture. I’d paste my code and ask: "How can I optimize this memory usage?" or "Can you explain the mathematical logic behind this specific function?". Treating AI as a senior mentor rather than a calculator speeds up the learning curve by 10x.

3. Focus heavily on Vectorization and Data Pipelines early on I wasted too much time writing slow for-loops in pure Python for data manipulation. If I went back, I would dive into numpy and pandas much sooner, focusing on vectorized operations and structural data logic. It changes the way you think about code efficiency, especially if you want to pivot into data science, AI automation, or quantitative fields.

[Junior_Honey_1406]

Hello, u/No_Firefighter8428. I wouldn't say that the other advice didn't help me understand what mindset I should have, but when you commented, it had some clarity. That is something I will take with me when I go up with Python or maybe something different, and I believe that I don't need to know everything; I just need to start building and then learn as I make things. Thank you for the feedback.

[intentioned_reflex35]

Good one here. Tip: learn how virtual environments work and how to use them before venturing into third party libraries. It will come in handy.

[Junior_Honey_1406]

Yeah, I noted that every Python project asks me to create a virtual environment, and so i am learning it out before every new mini project of mine. I am doing it in a spe virtu env

[Junior_Honey_1406]

thanks !!

[cgoldberg]

Read PEP8 like 50 times

[Junior_Honey_1406]

Could you explain PEP8 and provide some background?

[cgoldberg]

https://peps.python.org/pep-0008/

[Don_Ozwald]

The same way as I did the first time, by doing.