A regular expression will do the trick with very little code:
import re
...
if re.match("^[A-Za-z0-9_-]*$", my_little_string):
# do something here
[Edit] There's another solution not mentioned yet, and it seems to outperform the others given so far in most cases.
Use string.translate to replace all valid characters in the string, and see if we have any invalid ones left over. This is pretty fast as it uses the underlying C function to do the work, with very little python bytecode involved.
Obviously performance isn't everything - going for the most readable solutions is probably the best approach when not in a performance critical codepath, but just to see how the solutions stack up, here's a performance comparison of all the methods proposed so far. check_trans is the one using the string.translate method.
Test code:
import string, re, timeit
pat = re.compile('[\w-]*$')
pat_inv = re.compile ('[^\w-]')
allowed_chars=string.ascii_letters + string.digits + '_-'
allowed_set = set(allowed_chars)
trans_table = string.maketrans('','')
def check_set_diff(s):
return not set(s) - allowed_set
def check_set_all(s):
return all(x in allowed_set for x in s)
def check_set_subset(s):
return set(s).issubset(allowed_set)
def check_re_match(s):
return pat.match(s)
def check_re_inverse(s): # Search for non-matching character.
return not pat_inv.search(s)
def check_trans(s):
return not s.translate(trans_table,allowed_chars)
test_long_almost_valid='a_very_long_string_that_is_mostly_valid_except_for_last_char'*99 + '!'
test_long_valid='a_very_long_string_that_is_completely_valid_' * 99
test_short_valid='short_valid_string'
test_short_invalid='/$%$%&'
test_long_invalid='/$%$%&' * 99
test_empty=''
def main():
funcs = sorted(f for f in globals() if f.startswith('check_'))
tests = sorted(f for f in globals() if f.startswith('test_'))
for test in tests:
print "Test %-15s (length = %d):" % (test, len(globals()[test]))
for func in funcs:
print " %-20s : %.3f" % (func,
timeit.Timer('%s(%s)' % (func, test), 'from __main__ import pat,allowed_set,%s' % ','.join(funcs+tests)).timeit(10000))
print
if __name__=='__main__': main()
The results on my system are:
Test test_empty (length = 0):
check_re_inverse : 0.042
check_re_match : 0.030
check_set_all : 0.027
check_set_diff : 0.029
check_set_subset : 0.029
check_trans : 0.014
Test test_long_almost_valid (length = 5941):
check_re_inverse : 2.690
check_re_match : 3.037
check_set_all : 18.860
check_set_diff : 2.905
check_set_subset : 2.903
check_trans : 0.182
Test test_long_invalid (length = 594):
check_re_inverse : 0.017
check_re_match : 0.015
check_set_all : 0.044
check_set_diff : 0.311
check_set_subset : 0.308
check_trans : 0.034
Test test_long_valid (length = 4356):
check_re_inverse : 1.890
check_re_match : 1.010
check_set_all : 14.411
check_set_diff : 2.101
check_set_subset : 2.333
check_trans : 0.140
Test test_short_invalid (length = 6):
check_re_inverse : 0.017
check_re_match : 0.019
check_set_all : 0.044
check_set_diff : 0.032
check_set_subset : 0.037
check_trans : 0.015
Test test_short_valid (length = 18):
check_re_inverse : 0.125
check_re_match : 0.066
check_set_all : 0.104
check_set_diff : 0.051
check_set_subset : 0.046
check_trans : 0.017
The translate approach seems best in most cases, dramatically so with long valid strings, but is beaten out by regexes in test_long_invalid (Presumably because the regex can bail out immediately, but translate always has to scan the whole string). The set approaches are usually worst, beating regexes only for the empty string case.
Using all(x in allowed_set for x in s) performs well if it bails out early, but can be bad if it has to iterate through every character. isSubSet and set difference are comparable, and are consistently proportional to the length of the string regardless of the data.
There's a similar difference between the regex methods matching all valid characters and searching for invalid characters. Matching performs a little better when checking for a long, but fully valid string, but worse for invalid characters near the end of the string.
[Edit] There's another solution not mentioned yet, and it seems to outperform the others given so far in most cases.
Use string.translate to replace all valid characters in the string, and see if we have any invalid ones left over. This is pretty fast as it uses the underlying C function to do the work, with very little python bytecode involved.
Obviously performance isn't everything - going for the most readable solutions is probably the best approach when not in a performance critical codepath, but just to see how the solutions stack up, here's a performance comparison of all the methods proposed so far. check_trans is the one using the string.translate method.
Test code:
import string, re, timeit
pat = re.compile('[\w-]*$')
pat_inv = re.compile ('[^\w-]')
allowed_chars=string.ascii_letters + string.digits + '_-'
allowed_set = set(allowed_chars)
trans_table = string.maketrans('','')
def check_set_diff(s):
return not set(s) - allowed_set
def check_set_all(s):
return all(x in allowed_set for x in s)
def check_set_subset(s):
return set(s).issubset(allowed_set)
def check_re_match(s):
return pat.match(s)
def check_re_inverse(s): # Search for non-matching character.
return not pat_inv.search(s)
def check_trans(s):
return not s.translate(trans_table,allowed_chars)
test_long_almost_valid='a_very_long_string_that_is_mostly_valid_except_for_last_char'*99 + '!'
test_long_valid='a_very_long_string_that_is_completely_valid_' * 99
test_short_valid='short_valid_string'
test_short_invalid='/$%$%&'
test_long_invalid='/$%$%&' * 99
test_empty=''
def main():
funcs = sorted(f for f in globals() if f.startswith('check_'))
tests = sorted(f for f in globals() if f.startswith('test_'))
for test in tests:
print "Test %-15s (length = %d):" % (test, len(globals()[test]))
for func in funcs:
print " %-20s : %.3f" % (func,
timeit.Timer('%s(%s)' % (func, test), 'from __main__ import pat,allowed_set,%s' % ','.join(funcs+tests)).timeit(10000))
print
if __name__=='__main__': main()
The results on my system are:
Test test_empty (length = 0):
check_re_inverse : 0.042
check_re_match : 0.030
check_set_all : 0.027
check_set_diff : 0.029
check_set_subset : 0.029
check_trans : 0.014
Test test_long_almost_valid (length = 5941):
check_re_inverse : 2.690
check_re_match : 3.037
check_set_all : 18.860
check_set_diff : 2.905
check_set_subset : 2.903
check_trans : 0.182
Test test_long_invalid (length = 594):
check_re_inverse : 0.017
check_re_match : 0.015
check_set_all : 0.044
check_set_diff : 0.311
check_set_subset : 0.308
check_trans : 0.034
Test test_long_valid (length = 4356):
check_re_inverse : 1.890
check_re_match : 1.010
check_set_all : 14.411
check_set_diff : 2.101
check_set_subset : 2.333
check_trans : 0.140
Test test_short_invalid (length = 6):
check_re_inverse : 0.017
check_re_match : 0.019
check_set_all : 0.044
check_set_diff : 0.032
check_set_subset : 0.037
check_trans : 0.015
Test test_short_valid (length = 18):
check_re_inverse : 0.125
check_re_match : 0.066
check_set_all : 0.104
check_set_diff : 0.051
check_set_subset : 0.046
check_trans : 0.017
The translate approach seems best in most cases, dramatically so with long valid strings, but is beaten out by regexes in test_long_invalid (Presumably because the regex can bail out immediately, but translate always has to scan the whole string). The set approaches are usually worst, beating regexes only for the empty string case.
Using all(x in allowed_set for x in s) performs well if it bails out early, but can be bad if it has to iterate through every character. isSubSet and set difference are comparable, and are consistently proportional to the length of the string regardless of the data.
There's a similar difference between the regex methods matching all valid characters and searching for invalid characters. Matching performs a little better when checking for a long, but fully valid string, but worse for invalid characters near the end of the string.
[Edit] There's another solution not mentioned yet, and it seems to outperform the others given so far in most cases.
Use string.translate to replace all valid characters in the string, and see if we have any invalid ones left over. This is pretty fast as it uses the underlying C function to do the work, with very little python bytecode involved.
Obviously performance isn't everything - going for the most readable solutions is probably the best approach when not in a performance critical codepath, but just to see how the solutions stack up, here's a performance comparison of all the methods proposed so far. check_trans is the one using the string.translate method.
Test code:
import string, re, timeit
pat = re.compile('[\w-]*$')
pat_inv = re.compile ('[^\w-]')
allowed_chars=string.ascii_letters + string.digits + '_-'
allowed_set = set(allowed_chars)
trans_table = string.maketrans('','')
def check_set_diff(s):
return not set(s) - allowed_set
def check_set_all(s):
return all(x in allowed_set for x in s)
def check_set_subset(s):
return set(s).issubset(allowed_set)
def check_re_match(s):
return pat.match(s)
def check_re_inverse(s): # Search for non-matching character.
return not pat_inv.search(s)
def check_trans(s):
return not s.translate(trans_table,allowed_chars)
test_long_almost_valid='a_very_long_string_that_is_mostly_valid_except_for_last_char'*99 + '!'
test_long_valid='a_very_long_string_that_is_completely_valid_' * 99
test_short_valid='short_valid_string'
test_short_invalid='/$%$%&'
test_long_invalid='/$%$%&' * 99
test_empty=''
def main():
funcs = sorted(f for f in globals() if f.startswith('check_'))
tests = sorted(f for f in globals() if f.startswith('test_'))
for test in tests:
print "Test %-15s (length = %d):" % (test, len(globals()[test]))
for func in funcs:
print " %-20s : %.3f" % (func,
timeit.Timer('%s(%s)' % (func, test), 'from __main__ import pat,allowed_set,%s' % ','.join(funcs+tests)).timeit(10000))
print
if __name__=='__main__': main()
The results on my system are:
Test test_empty (length = 0):
check_re_inverse : 0.042
check_re_match : 0.030
check_set_all : 0.027
check_set_diff : 0.029
check_set_subset : 0.029
check_trans : 0.014
Test test_long_almost_valid (length = 5941):
check_re_inverse : 2.690
check_re_match : 3.037
check_set_all : 18.860
check_set_diff : 2.905
check_set_subset : 2.903
check_trans : 0.182
Test test_long_invalid (length = 594):
check_re_inverse : 0.017
check_re_match : 0.015
check_set_all : 0.044
check_set_diff : 0.311
check_set_subset : 0.308
check_trans : 0.034
Test test_long_valid (length = 4356):
check_re_inverse : 1.890
check_re_match : 1.010
check_set_all : 14.411
check_set_diff : 2.101
check_set_subset : 2.333
check_trans : 0.140
Test test_short_invalid (length = 6):
check_re_inverse : 0.017
check_re_match : 0.019
check_set_all : 0.044
check_set_diff : 0.032
check_set_subset : 0.037
check_trans : 0.015
Test test_short_valid (length = 18):
check_re_inverse : 0.125
check_re_match : 0.066
check_set_all : 0.104
check_set_diff : 0.051
check_set_subset : 0.046
check_trans : 0.017
The translate approach seems best in most cases, dramatically so with long valid strings, but is beaten out by regexes in test_long_invalid (Presumably because the regex can bail out immediately, but translate always has to scan the whole string). The set approaches are usually worst, beating regexes only for the empty string case.
Using all(x in allowed_set for x in s) performs well if it bails out early, but can be bad if it has to iterate through every character. isSubSet and set difference are comparable, and are consistently proportional to the length of the string regardless of the data.
There's a similar difference between the regex methods matching all valid characters and searching for invalid characters. Matching performs a little better when checking for a long, but fully valid string, but worse for invalid characters near the end of the string.
[Edit] There's another solution not mentioned yet, and it seems to outperform the others given so far in most cases.
Use string.translate to replace all valid characters in the string, and see if we have any invalid ones left over. This is pretty fast as it uses the underlying C function to do the work, with very little python bytecode involved.
Obviously performance isn't everything - going for the most readable solutions is probably the best approach when not in a performance critical codepath, but just to see how the solutions stack up, here's a performance comparison of all the methods proposed so far. check_trans is the one using the string.translate method.
Test code:
import string, re, timeit
pat = re.compile('[\w-]*$')
pat_inv = re.compile ('[^\w-]')
allowed_chars=string.ascii_letters + string.digits + '_-'
allowed_set = set(allowed_chars)
trans_table = string.maketrans('','')
def check_set_diff(s):
return not set(s) - allowed_set
def check_set_all(s):
return all(x in allowed_set for x in s)
def check_set_subset(s):
return set(s).issubset(allowed_set)
def check_re_match(s):
return pat.match(s)
def check_re_inverse(s): # Search for non-matching character.
return not pat_inv.search(s)
def check_trans(s):
return not s.translate(trans_table,allowed_chars)
test_long_almost_valid='a_very_long_string_that_is_mostly_valid_except_for_last_char'*99 + '!'
test_long_valid='a_very_long_string_that_is_completely_valid_' * 99
test_short_valid='short_valid_string'
test_short_invalid='/$%$%&'
test_long_invalid='/$%$%&' * 99
test_empty=''
def main():
funcs = sorted(f for f in globals() if f.startswith('check_'))
tests = sorted(f for f in globals() if f.startswith('test_'))
for test in tests:
print "Test %-15s (length = %d):" % (test, len(globals()[test]))
for func in funcs:
print " %-20s : %.3f" % (func,
timeit.Timer('%s(%s)' % (func, test), 'from __main__ import pat,allowed_set,%s' % ','.join(funcs+tests)).timeit(10000))
print
if __name__=='__main__': main()
The results on my system are:
Test test_empty (length = 0):
check_re_inverse : 0.042
check_re_match : 0.030
check_set_all : 0.027
check_set_diff : 0.029
check_set_subset : 0.029
check_trans : 0.014
Test test_long_almost_valid (length = 5941):
check_re_inverse : 2.690
check_re_match : 3.037
check_set_all : 18.860
check_set_diff : 2.905
check_set_subset : 2.903
check_trans : 0.182
Test test_long_invalid (length = 594):
check_re_inverse : 0.017
check_re_match : 0.015
check_set_all : 0.044
check_set_diff : 0.311
check_set_subset : 0.308
check_trans : 0.034
Test test_long_valid (length = 4356):
check_re_inverse : 1.890
check_re_match : 1.010
check_set_all : 14.411
check_set_diff : 2.101
check_set_subset : 2.333
check_trans : 0.140
Test test_short_invalid (length = 6):
check_re_inverse : 0.017
check_re_match : 0.019
check_set_all : 0.044
check_set_diff : 0.032
check_set_subset : 0.037
check_trans : 0.015
Test test_short_valid (length = 18):
check_re_inverse : 0.125
check_re_match : 0.066
check_set_all : 0.104
check_set_diff : 0.051
check_set_subset : 0.046
check_trans : 0.017
The translate approach seems best in most cases, dramatically so with long valid strings, but is beaten out by regexes in test_long_invalid (Presumably because the regex can bail out immediately, but translate always has to scan the whole string). The set approaches are usually worst, beating regexes only for the empty string case.
Using all(x in allowed_set for x in s) performs well if it bails out early, but can be bad if it has to iterate through every character. isSubSet and set difference are comparable, and are consistently proportional to the length of the string regardless of the data.
There's a similar difference between the regex methods matching all valid characters and searching for invalid characters. Matching performs a little better when checking for a long, but fully valid string, but worse for invalid characters near the end of the string.
There are a variety of ways of achieving this goal, some are clearer than others. For each of my examples, 'True' means that the string passed is valid, 'False' means it contains invalid characters.
First of all, there's the naive approach:
import string
allowed = string.letters + string.digits + '_' + '-'
def check_naive(mystring):
return all(c in allowed for c in mystring)
Then there's use of a regular expression, you can do this with re.match(). Note that '-' has to be at the end of the [] otherwise it will be used as a 'range' delimiter. Also note the $ which means 'end of string'. Other answers noted in this question use a special character class, '\w', I always prefer using an explicit character class range using [] because it is easier to understand without having to look up a quick reference guide, and easier to special-case.
import re
CHECK_RE = re.compile('[a-zA-Z0-9_-]+$')
def check_re(mystring):
return CHECK_RE.match(mystring)
Another solution noted that you can do an inverse match with regular expressions, I've included that here now. Note that [^...] inverts the character class because the ^ is used:
CHECK_INV_RE = re.compile('[^a-zA-Z0-9_-]')
def check_inv_re(mystring):
return not CHECK_INV_RE.search(mystring)
You can also do something tricky with the 'set' object. Have a look at this example, which removes from the original string all the characters that are allowed, leaving us with a set containing either a) nothing, or b) the offending characters from the string:
def check_set(mystring):
return not set(mystring) - set(allowed)
There are a variety of ways of achieving this goal, some are clearer than others. For each of my examples, 'True' means that the string passed is valid, 'False' means it contains invalid characters.
First of all, there's the naive approach:
import string
allowed = string.letters + string.digits + '_' + '-'
def check_naive(mystring):
return all(c in allowed for c in mystring)
Then there's use of a regular expression, you can do this with re.match(). Note that '-' has to be at the end of the [] otherwise it will be used as a 'range' delimiter. Also note the $ which means 'end of string'. Other answers noted in this question use a special character class, '\w', I always prefer using an explicit character class range using [] because it is easier to understand without having to look up a quick reference guide, and easier to special-case.
import re
CHECK_RE = re.compile('[a-zA-Z0-9_-]+$')
def check_re(mystring):
return CHECK_RE.match(mystring)
Another solution noted that you can do an inverse match with regular expressions, I've included that here now. Note that [^...] inverts the character class because the ^ is used:
CHECK_INV_RE = re.compile('[^a-zA-Z0-9_-]')
def check_inv_re(mystring):
return not CHECK_INV_RE.search(mystring)
You can also do something tricky with the 'set' object. Have a look at this example, which removes from the original string all the characters that are allowed, leaving us with a set containing either a) nothing, or b) the offending characters from the string:
def check_set(mystring):
return not set(mystring) - set(allowed)
There are a variety of ways of achieving this goal, some are clearer than others. For each of my examples, 'True' means that the string passed is valid, 'False' means it contains invalid characters.
First of all, there's the naive approach:
import string
allowed = string.letters + string.digits + '_' + '-'
def check_naive(mystring):
return all(c in allowed for c in mystring)
Then there's use of a regular expression, you can do this with re.match(). Note that '-' has to be at the end of the [] otherwise it will be used as a 'range' delimiter. Also note the $ which means 'end of string'. Other answers noted in this question use a special character class, '\w', I always prefer using an explicit character class range using [] because it is easier to understand without having to look up a quick reference guide, and easier to special-case.
import re
CHECK_RE = re.compile('[a-zA-Z0-9_-]+$')
def check_re(mystring):
return CHECK_RE.match(mystring)
Another solution noted that you can do an inverse match with regular expressions, I've included that here now. Note that [^...] inverts the character class because the ^ is used:
CHECK_INV_RE = re.compile('[^a-zA-Z0-9_-]')
def check_inv_re(mystring):
return not CHECK_INV_RE.search(mystring)
You can also do something tricky with the 'set' object. Have a look at this example, which removes from the original string all the characters that are allowed, leaving us with a set containing either a) nothing, or b) the offending characters from the string:
def check_set(mystring):
return not set(mystring) - set(allowed)
There are a variety of ways of achieving this goal, some are clearer than others. For each of my examples, 'True' means that the string passed is valid, 'False' means it contains invalid characters.
First of all, there's the naive approach:
import string
allowed = string.letters + string.digits + '_' + '-'
def check_naive(mystring):
return all(c in allowed for c in mystring)
Then there's use of a regular expression, you can do this with re.match(). Note that '-' has to be at the end of the [] otherwise it will be used as a 'range' delimiter. Also note the $ which means 'end of string'. Other answers noted in this question use a special character class, '\w', I always prefer using an explicit character class range using [] because it is easier to understand without having to look up a quick reference guide, and easier to special-case.
import re
CHECK_RE = re.compile('[a-zA-Z0-9_-]+$')
def check_re(mystring):
return CHECK_RE.match(mystring)
Another solution noted that you can do an inverse match with regular expressions, I've included that here now. Note that [^...] inverts the character class because the ^ is used:
CHECK_INV_RE = re.compile('[^a-zA-Z0-9_-]')
def check_inv_re(mystring):
return not CHECK_INV_RE.search(mystring)
You can also do something tricky with the 'set' object. Have a look at this example, which removes from the original string all the characters that are allowed, leaving us with a set containing either a) nothing, or b) the offending characters from the string:
def check_set(mystring):
return not set(mystring) - set(allowed)
If it were not for the dashes and underscores, the easiest solution would be
my_little_string.isalnum()
(Section 3.6.1 of the Python Library Reference)
If it were not for the dashes and underscores, the easiest solution would be
my_little_string.isalnum()
(Section 3.6.1 of the Python Library Reference)
If it were not for the dashes and underscores, the easiest solution would be
my_little_string.isalnum()
(Section 3.6.1 of the Python Library Reference)
If it were not for the dashes and underscores, the easiest solution would be
my_little_string.isalnum()
(Section 3.6.1 of the Python Library Reference)
As an alternative to using regex you could do it in Sets:
from sets import Set
allowed_chars = Set('0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_-')
if Set(my_little_sting).issubset(allowed_chars):
# your action
print True
As an alternative to using regex you could do it in Sets:
from sets import Set
allowed_chars = Set('0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_-')
if Set(my_little_sting).issubset(allowed_chars):
# your action
print True
As an alternative to using regex you could do it in Sets:
from sets import Set
allowed_chars = Set('0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_-')
if Set(my_little_sting).issubset(allowed_chars):
# your action
print True
As an alternative to using regex you could do it in Sets:
from sets import Set
allowed_chars = Set('0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_-')
if Set(my_little_sting).issubset(allowed_chars):
# your action
print True
pat = re.compile ('[^\w-]')
def onlyallowed(s):
return not pat.search (s)
pat = re.compile ('[^\w-]')
def onlyallowed(s):
return not pat.search (s)
pat = re.compile ('[^\w-]')
def onlyallowed(s):
return not pat.search (s)
pat = re.compile ('[^\w-]')
def onlyallowed(s):
return not pat.search (s)
Regular expression can be very flexible.
import re;
re.fullmatch("^[\w-]+$", target_string) # fullmatch looks also workable for python 3.4
\w: Only [a-zA-Z0-9_]
So you need to add - char for justify hyphen char.
+: Match one or more repetitions of the preceding char. I guess you don't accept blank input. But if you do, change to * .
^: Matches the start of the string.
$: Matches the end of the string.
You need these two special characters since you need to avoid the following case. The unwanted chars like & here might appear between the matched pattern.
&&&PATTERN&&PATTERN
Regular expression can be very flexible.
import re;
re.fullmatch("^[\w-]+$", target_string) # fullmatch looks also workable for python 3.4
\w: Only [a-zA-Z0-9_]
So you need to add - char for justify hyphen char.
+: Match one or more repetitions of the preceding char. I guess you don't accept blank input. But if you do, change to * .
^: Matches the start of the string.
$: Matches the end of the string.
You need these two special characters since you need to avoid the following case. The unwanted chars like & here might appear between the matched pattern.
&&&PATTERN&&PATTERN
Well you can ask the help of regex, the great in here :)
code:
import re
string = 'adsfg34wrtwe4r2_()' #your string that needs to be matched.
regex = r'^[\w\d_()]*$' # you can also add a space in regex if u want to allow it in the string
if re.match(regex,string):
print 'yes'
else:
print 'false'
Output:
yes
Hope this helps :)
Well you can ask the help of regex, the great in here :)
code:
import re
string = 'adsfg34wrtwe4r2_()' #your string that needs to be matched.
regex = r'^[\w\d_()]*$' # you can also add a space in regex if u want to allow it in the string
if re.match(regex,string):
print 'yes'
else:
print 'false'
Output:
yes
Hope this helps :)
You could always use a list comprehension and check the results with all, it would be a little less resource intensive than using a regex: all([c in string.letters + string.digits + ["_", "-"] for c in mystring])
You could always use a list comprehension and check the results with all, it would be a little less resource intensive than using a regex: all([c in string.letters + string.digits + ["_", "-"] for c in mystring])
Here's something based on Jerub's "naive approach" (naive being his words, not mine!):
import string
ALLOWED = frozenset(string.ascii_letters + string.digits + '_' + '-')
def check(mystring):
return all(c in ALLOWED for c in mystring)
If ALLOWED was a string then I think c in ALLOWED would involve iterating over each character in the string until it found a match or reached the end. Which, to quote Joel Spolsky, is something of a Shlemiel the Painter algorithm.
But testing for existence in a set should be more efficient, or at least less dependent on the number of allowed characters. Certainly this approach is a little bit faster on my machine. It's clear and I think it performs plenty well enough for most cases (on my slow machine I can validate tens of thousands of short-ish strings in a fraction of a second). I like it.
ACTUALLY on my machine a regexp works out several times faster, and is just as simple as this (arguably simpler). So that probably is the best way forward.
Here's something based on Jerub's "naive approach" (naive being his words, not mine!):
import string
ALLOWED = frozenset(string.ascii_letters + string.digits + '_' + '-')
def check(mystring):
return all(c in ALLOWED for c in mystring)
If ALLOWED was a string then I think c in ALLOWED would involve iterating over each character in the string until it found a match or reached the end. Which, to quote Joel Spolsky, is something of a Shlemiel the Painter algorithm.
But testing for existence in a set should be more efficient, or at least less dependent on the number of allowed characters. Certainly this approach is a little bit faster on my machine. It's clear and I think it performs plenty well enough for most cases (on my slow machine I can validate tens of thousands of short-ish strings in a fraction of a second). I like it.
ACTUALLY on my machine a regexp works out several times faster, and is just as simple as this (arguably simpler). So that probably is the best way forward.
You could always use a list comprehension and check the results with all, it would be a little less resource intensive than using a regex: all([c in string.letters + string.digits + ["_", "-"] for c in mystring])
You could always use a list comprehension and check the results with all, it would be a little less resource intensive than using a regex: all([c in string.letters + string.digits + ["_", "-"] for c in mystring])
use a regex and see if it matches!
([a-z][A-Z][0-9]\_\-)*
use a regex and see if it matches!
([a-z][A-Z][0-9]\_\-)*
use a regex and see if it matches!
([a-z][A-Z][0-9]\_\-)*
use a regex and see if it matches!
([a-z][A-Z][0-9]\_\-)*
Source: Stackoverflow.com