What Should I Do With My Python Automation Program?

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Asked By CuriousCoder42 On

Hey everyone! I recently created an automation program using Python along with some libraries like UIAUTOMATOR2 and ADB. The program allows me to schedule tasks for various apps on my phone—like sending messages at a specified time or opening certain apps. It can also control my PC and change phone settings, take screenshots, and even record the screen using voice commands. The challenge I'm facing right now is connecting my phone to my computer, either through USB or wireless debugging, as I need to use UIAUTOMATOR2 to control everything. I made this program a couple of months ago while I was focused on my high school exams and I'm now at a crossroads. I only know the basics of Python and I'm currently learning data science (like NumPy and pandas). Should I invest more time into improving this automation tool, or is it better to focus on something else?

2 Answers

Answered By DevEnthusiast007 On

It's great that you're diving into programming! Honestly, if you find the current project exciting, go for it! Improving your skills through this sort of hands-on experience can be invaluable. But if you feel stuck, it might be wise to put some time into data science and come back to the automation program later with fresh ideas.

PythonPal45 -

That’s solid advice! Balancing your time between projects will help strengthen your overall abilities. Keep experimenting!

Answered By TechGuru88 On

It sounds like you’ve built a really cool project! If you’re struggling with the ADB connection, you might want to look into other frameworks or libraries for Android automation that could simplify the process, like Appium. Also, sharing your code on GitHub could attract feedback and help from others. As for improving your program, if you enjoy working on it, definitely keep refining it, but balance that with your data science studies too!

CodeCrafter21 -

I agree, Appium could be a good alternative! Plus, if you keep learning, both fields could help each other. You can integrate data science concepts into your project later!

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