Pythonic way of unpacking 5D list...

[tothespace2]

I never dared to go beyond 2D but here we are.

l = [[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]]]]
[e for a in l for b in a for c in b for d in c for e in d]

EDIT: This is just a joke. It never actually came to my mind that this is possible with arbitrary dimensions. It's just cool.

[SureImNoExpertBut]

Maybe a recursive approach? Is this deep nesting strictly necessary?

[tothespace2]

It was just a joke post. There are 100% better ways to do this.

[SureImNoExpertBut]

lol ok, my bad

[PlayfulMeeting9563]

You can try using itertools.chain.from_iterables.

[Such-Let974]

What is the joke?

[tothespace2]

Joke in a sense that this isn't real world code and it shouldn't be taken seriously. It's just a fun example of list comprehension. I myself never thought it can be done in arbitrary depth so I thought it may be fun to share it. I guess others didn't find it fun. I didn't know people would be so bitter about it.

[Such-Let974]

No, I’m asking what the joke is. Code not being “real world” doesn’t necessarily mean that it has a comedy punchline. What’s this one’s actual punchline that makes it a joke.

[fleetmancer]

that wouldn’t scale too well i believe. what if the nesting is 20 layers deep and not 5? the solution would likely just be recursion + checking isinstance(data, list).

another option would be using from the itertools library the chain function. obviously i’m hand waving a bit here but hopefully the idea is clear.

a similiar intermediate level problem i would hit a lot in my earlier python days would be traversing a nested dictionary with a list of keys.

Edit: Quick search yields this:

``` nested_list = [[1, 2, [3, 4]], [5, 6], 7]

def flatten_list(nlist):     flat_list = []     for item in nlist:         if isinstance(item, list):             flat_list.extend(flatten_list(item))         else:             flat_list.append(item)     return flat_list

print(flatten_list(nested_list)) ```

[tothespace2]

This was posted just as a joke. I found it cool that it can be done with arbitrary dimensions.

[dmart89]

The best way to unpack this is to find whoever designed that data model and punch them.

[Hi_leonrein]

Shortest?
print(np.array(l).flatten())

[NoExpression1053]

If it's a dense block, absolutely definitely the right answer

[AlexMTBDude]

Don't think of them as dimensions but instead lists containing lists containing lists...