Python: Efficient unrolling/flattening list of tuples and single floats-CodePudding

I have a list of tuples and single floats

v = [(1., 2., 3.), (4., 5.), 6., 7.]

Now I want to flatten it with the good old list comprehension

[item for sublist in v for item in sublist]

But an error occurs as single floats are not iterable. What is the most efficient way to unroll this mixed list? I tried to go through the list and use isininstance() but once again, the list is not iterable.

EDIT: time comparisons so far

numpy approach with hstack: 6.49 µs ± 100 ns per loop
hasattr approach: 398 ns ± 2.11 ns per loop
collections approach: 804 ns ± 1.27 ns per loop

CodePudding user response：

You can use hasattr to check if the object is iterable (has a __iter__ method):

out = [item for sublist in v
       for item in (sublist if hasattr(sublist, '__iter__') else [sublist])]

output: [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]

An alternative would be to use collections.abc:

from collections.abc import Iterable
    
out = [item for sublist in v
       for item in (sublist if isinstance(sublist, Iterable) else [sublist])]

Note that in both cases, strings are considered iterable, you might want to check for this specific case depending on your data.

CodePudding user response：

With numpy you can use hstack():

v = [(1., 2., 3.), (4., 5.), 6., 7.]
v = np.hstack(v)

# Output
array([1., 2., 3., 4., 5., 6., 7.])

CodePudding user response：

The more-itertools package has a function specifically for this problem -

from more_itertools import collapse
v = [(1., 2., 3.), (4., 5.), 6., 7.]
print(list(collapse(v))
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0]

It works with strings too -

x = [('ab', 'cd'), 'e', ['f', 'gh']]
print(list(collapse(x))
['ab', 'cd', 'e', 'f', 'gh']