I have a list (array) with mixed
a = ["x", "2", "y"]
b = ["x", 2, "y"]
print ":".join(a)
print ":".join(b)
The first join works, but the second one throws a TypeError exception
I came up with this, but is this the Python solution?
print ":".join(map(str, b))
BTW in the end I just would like to write this string to a file, so if there is a specific solution for that, I'd appreciate that too.
First convert the list of integer into a list of strings( as join() works with strings only). Then, simply join them using join() method.
Summary: To extract numbers from a given string in Python you can use one of the following methods: Use the regex module. Use split() and append() functions on a list. Use a List Comprehension with isdigit() and split() functions.
Using the str. We can also use the str. format() function for concatenation of string and integer.
Your solution works nicely and is probably one of the fastest ways to do this for small to medium sized lists, but it creates an unnecessary list (in python2.x). Usually that's not a problem, but in a few cases, depending on the object b
, it could be an issue. Another which is lazy in python2 as well as python 3 is:
':'.join(str(x) for x in b)
Some timings for python 2.7.3:
$ python -m timeit -s 'b = ["x", 2, "y"]' '":".join(map(str,b))'
1000000 loops, best of 3: 1.66 usec per loop
$python -m timeit -s 'b = ["x", 2, "y"]' '":".join([str(x) for x in b])'
1000000 loops, best of 3: 1.49 usec per loop
$ python -m timeit -s 'b = ["x", 2, "y"]' '":".join(str(x) for x in b)'
100000 loops, best of 3: 3.26 usec per loop
$python -m timeit -s 'from itertools import imap; b = ["x", 2, "y"]' '":".join(imap(str,b))'
100000 loops, best of 3: 2.83 usec per loop
Some timings for python3.2:
$ python3 -m timeit -s 'b = ["x", 2, "y"]' '":".join(map(str,b))'
100000 loops, best of 3: 2.6 usec per loop
$ python3 -m timeit -s 'b = ["x", 2, "y"]' '":".join([str(x) for x in b])'
100000 loops, best of 3: 2.08 usec per loop
$ python3 -m timeit -s 'b = ["x", 2, "y"]' '":".join(str(x) for x in b)'
100000 loops, best of 3: 3.39 usec per loop
Note that if you let the loop get a lot bigger, the differences become less important:
python2.7.3:
$ python -m timeit -s 'b = list(range(10000))' '":".join(str(x) for x in b)'
100 loops, best of 3: 4.83 msec per loop
$ python -m timeit -s 'b = list(range(10000))' '":".join([str(x) for x in b])'
100 loops, best of 3: 4.33 msec per loop
$ python -m timeit -s 'b = list(range(10000))' '":".join(map(str,b))'
100 loops, best of 3: 3.29 msec per loop
python 3.2.0
$ python3 -m timeit -s 'b = list(range(10000))' '":".join(str(x) for x in b)'
100 loops, best of 3: 6.42 msec per loop
$ python3 -m timeit -s 'b = list(range(10000))' '":".join([str(x) for x in b])'
100 loops, best of 3: 5.51 msec per loop
$ python3 -m timeit -s 'b = list(range(10000))' '":".join(map(str,b))'
100 loops, best of 3: 4.55 msec per loop
*all timings done on my MacbookPro, OS-X 10.5.8 intel core2duo ....
Notes,
map
is faster for a larger list. map
is probably slower for the small list as you need to look up the function whereas the list comprehension cannot be "shadowed", so no lookup needs to be performed. There may be another turn-around point for HUGE lists where the time it takes to build the intermediate list becomes significant.If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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