I have data stored in a NumPy array and want to work with it using native Python structures. What’s the simplest and most reliable way to convert a numpy array to list?
Honestly, after working with NumPy for years, I can tell you that the easiest way is just to call .tolist() on the array. It’s like a magic trick for conversion, and here’s how simple it is:
my_list = my_array.tolist()
No headaches, right?
This works whether you’re dealing with a 1D array or a 2D one. It converts everything into native Python lists and sublists. It’s efficient, clean, and totally hassle-free.
Totally agree, @Priyadapanicker
I also use .tolist() all the time, especially when I need to pass NumPy data into functions that expect standard Python structures. It’s reliable and gets the job done without any complications—even with multi-dimensional arrays. It’s kind of like the universal translator between NumPy and Python lists.
Yeah, I can totally relate to the days when I used to manually loop through arrays. Major learning curve there! 
But seriously, once you start using .tolist():
list_version = np_array.tolist()
You realize just how much time it saves, especially when you’re moving data between libraries or preparing it for JSON. It’s such a game-changer when you’re working outside of NumPy and need that native Python list format.