From this post I learned that you can concatenate tuples with sum()
:
>>> tuples = (('hello',), ('these', 'are'), ('my', 'tuples!')) >>> sum(tuples, ()) ('hello', 'these', 'are', 'my', 'tuples!')
Which looks pretty nice. But why does this work? And, is this optimal, or is there something from itertools
that would be preferable to this construct?
When it is required to concatenate multiple tuples, the '+' operator can be used. A tuple is an immutable data type. It means, values once defined can't be changed by accessing their index elements. If we try to change the elements, it results in an error.
The Python "TypeError: can only concatenate tuple (not "str") to tuple" occurs when we try to concatenate a tuple and a string. To solve the error, make sure that the values are either 2 tuples or 2 strings before concatenating them.
To concatenate two tuples we will use ” + ” operator to concatenate in python.
the addition operator concatenates tuples in python:
('a', 'b')+('c', 'd') Out[34]: ('a', 'b', 'c', 'd')
From the docstring of sum
:
Return the sum of a 'start' value (default: 0) plus an iterable of numbers
It means sum
doesn't start with the first element of your iterable, but rather with an initial value that is passed through start=
argument.
By default sum
is used with numeric thus the default start value is 0
. So summing an iterable of tuples requires to start with an empty tuple. ()
is an empty tuple:
type(()) Out[36]: tuple
Therefore the working concatenation.
As per performance, here is a comparison:
%timeit sum(tuples, ()) The slowest run took 9.40 times longer than the fastest. This could mean that an intermediate result is being cached. 1000000 loops, best of 3: 285 ns per loop %timeit tuple(it.chain.from_iterable(tuples)) The slowest run took 5.00 times longer than the fastest. This could mean that an intermediate result is being cached. 1000000 loops, best of 3: 625 ns per loop
Now with t2 of a size 10000:
%timeit sum(t2, ()) 10 loops, best of 3: 188 ms per loop %timeit tuple(it.chain.from_iterable(t2)) 1000 loops, best of 3: 526 µs per loop
So if your list of tuples is small, you don't bother. If it's medium size or larger, you should use itertools
.
It works because addition is overloaded (on tuples) to return the concatenated tuple:
>>> () + ('hello',) + ('these', 'are') + ('my', 'tuples!') ('hello', 'these', 'are', 'my', 'tuples!')
That's basically what sum
is doing, you give an initial value of an empty tuple and then add the tuples to that.
However this is generally a bad idea because addition of tuples creates a new tuple, so you create several intermediate tuples just to copy them into the concatenated tuple:
() ('hello',) ('hello', 'these', 'are') ('hello', 'these', 'are', 'my', 'tuples!')
That's an implementation that has quadratic runtime behavior. That quadratic runtime behavior can be avoided by avoiding the intermediate tuples.
>>> tuples = (('hello',), ('these', 'are'), ('my', 'tuples!'))
Using nested generator expressions:
>>> tuple(tuple_item for tup in tuples for tuple_item in tup) ('hello', 'these', 'are', 'my', 'tuples!')
Or using a generator function:
def flatten(it): for seq in it: for item in seq: yield item >>> tuple(flatten(tuples)) ('hello', 'these', 'are', 'my', 'tuples!')
Or using itertools.chain.from_iterable
:
>>> import itertools >>> tuple(itertools.chain.from_iterable(tuples)) ('hello', 'these', 'are', 'my', 'tuples!')
And if you're interested how these perform (using my simple_benchmark
package):
import itertools import simple_benchmark def flatten(it): for seq in it: for item in seq: yield item def sum_approach(tuples): return sum(tuples, ()) def generator_expression_approach(tuples): return tuple(tuple_item for tup in tuples for tuple_item in tup) def generator_function_approach(tuples): return tuple(flatten(tuples)) def itertools_approach(tuples): return tuple(itertools.chain.from_iterable(tuples)) funcs = [sum_approach, generator_expression_approach, generator_function_approach, itertools_approach] arguments = {(2**i): tuple((1,) for i in range(1, 2**i)) for i in range(1, 13)} b = simple_benchmark.benchmark(funcs, arguments, argument_name='number of tuples to concatenate') b.plot()
(Python 3.7.2 64bit, Windows 10 64bit)
So while the sum
approach is very fast if you concatenate only a few tuples it will be really slow if you try to concatenate lots of tuples. The fastest of the tested approaches for many tuples is itertools.chain.from_iterable
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With