All generalizations are false (irony intended). One cannot say that try: except: is always faster than regex or vice versa. In your case, regex is not overkill and would be much faster than the try: except: method. However, based on our discussions in the comments section of your question, I went ahead and implemented a C library that efficiently performs this conversion (since I see this question a lot on SO); the library is called fastnumbers. Below are timing tests using your try: except: method, using regex, and using fastnumbers.
from __future__ import print_function
import timeit
prep_code = '''\
import random
import string
x = [''.join(random.sample(string.ascii_letters, 7)) for _ in range(10)]
y = [str(random.randint(0, 1000)) for _ in range(10)]
z = [str(random.random()) for _ in range(10)]
'''
try_method = '''\
def converter_try(vals):
resline = []
for item in vals:
try:
resline.append(int(item))
except ValueError:
try:
resline.append(float(item))
except ValueError:
resline.append(item)
'''
re_method = '''\
import re
int_match = re.compile(r'[+-]?\d+$').match
float_match = re.compile(r'[-+]?\d*\.?\d+(?:[eE][-+]?\d+)?$').match
def converter_re(vals):
resline = []
for item in vals:
if int_match(item):
resline.append(int(item))
elif float_match(item):
resline.append(float(item))
else:
resline.append(item)
'''
fn_method = '''\
from fastnumbers import fast_real
def converter_fn(vals):
resline = []
for item in vals:
resline.append(fast_real(item))
'''
print('Try with non-number strings', timeit.timeit('converter_try(x)', prep_code+try_method), 'seconds')
print('Try with integer strings', timeit.timeit('converter_try(y)', prep_code+try_method), 'seconds')
print('Try with float strings', timeit.timeit('converter_try(z)', prep_code+try_method), 'seconds')
print()
print('Regex with non-number strings', timeit.timeit('converter_re(x)', prep_code+re_method), 'seconds')
print('Regex with integer strings', timeit.timeit('converter_re(y)', prep_code+re_method), 'seconds')
print('Regex with float strings', timeit.timeit('converter_re(z)', prep_code+re_method), 'seconds')
print()
print('fastnumbers with non-number strings', timeit.timeit('converter_fn(x)', prep_code+fn_method), 'seconds')
print('fastnumbers with integer strings', timeit.timeit('converter_fn(y)', prep_code+fn_method), 'seconds')
print('fastnumbers with float strings', timeit.timeit('converter_fn(z)', prep_code+fn_method), 'seconds')
print()
The output looks like this on my machine:
Try with non-number strings 55.1374599934 seconds
Try with integer strings 11.8999788761 seconds
Try with float strings 41.8258318901 seconds
Regex with non-number strings 11.5976541042 seconds
Regex with integer strings 18.1302199364 seconds
Regex with float strings 19.1559209824 seconds
fastnumbers with non-number strings 4.02173805237 seconds
fastnumbers with integer strings 4.21903610229 seconds
fastnumbers with float strings 4.96900391579 seconds
A few things are pretty clear
try: except: is very slow for non-numeric input; regex beats that handilytry: except: becomes more efficient if exceptions don't need to be raisedfastnumbers beats the pants off both in all cases
So, if you don't want to use fastnumbers, you need to assess if you are more likely to encounter invalid strings or valid strings, and base your algorithm choice on that.
