Python is the tool, bioinformatics is the project. If you wanted to use a sewing machine to make a dress, you would read its manual, familiarize yourself with all the buttons, take a peek under the hood, then start right away on the dress. You would inevitably come across a situation you weren't prepared for: thread getting looped, internal parts jamming, the wrong needle tearing holes. When that happens you see if there's a quick fix at hand, if not you ask a friend or search online for clues.
It's the same for using Python for bioinformatics. Go through the excellent official Python tutorial[0]. You won't remember everything, but you want to build some subconscious memory and muscle memory. After that, dove straight into your bioinformatics project. You will inevitably get stuckany times, there are no programmers who don't! At that point you'll need to do some research just as we all do, and you'll likely learn something new about Python in the process. The key is to let the bioinformatics motivate the Python, not the other way around.
[0] https://docs.python.org/3/tutorial/index.html
