multiplying str / list / tuple and pitfalls (beginner - intermediate) anthony explains #361

today I talk about some nifty operator overloading in python for multiplication and why you have to be careful with it sometimes!

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[tandavme]

little optimisation trick is to pre-allocate lists when you need to fill them with random values (vs append)
or use comprehensions (sometimes not suitable)
(in order to prevent list resize when it full)

%%timeit
x = [0] * n
for i in range(n): x[i] = random.random()
975 ms ± 9.71 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%%timeit
x = [random.random() for i in range(n)]
913 ms ± 24.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%%timeit
x = []
for i in range(n): x.append(random.random())
1.14 s ± 10.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
(not so much but slower because of list's array resize under the hood)

[bi]

Keep Going My Friend On The Internet 😎👍

[marsma]

Remember one of my first problem solving in Python and got cought by exact problem with multiplying list of objects. I initialize table for board puzzle of sort and do comprehension inside and the multiplication.

It was pain to debug that. Great video as always.

[mfeickert]

Thanks for another nice video! A video topic request: How pip's cache works / pip decides what to cache. I was surprised to learn today that in my pip cache I have 28 JAX wheels but no NumPy or SciPy wheels (I use all 3 extensively across many virtual environments).

$ find ~/.cache/pip/ -iname "jax*" | wc -l
28
$ find ~/.cache/pip/ -iname "numpy*" | wc -l
0

I understand that this may be niche enough to not be interesting enough for a video.

[ItzAnameOk]

Don't mind me. Just here to add a like for the algorithm Gods to see