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The first thing the Soundex function checks is whether the input is a non-empty string of letters. What's the best way to do this?
If you answered “regular expressions”, go sit in the corner and contemplate your bad instincts. Regular expressions are almost never the right answer; they should be avoided whenever possible. Not only for performance reasons, but simply because they're difficult to debug and maintain. Also for performance reasons.
This code fragment from soundex/stage1/soundex1a.py checks whether the function argument source is a word made entirely of letters, with at least one letter (not the empty string):
allChars = string.uppercase + string.lowercase if not re.search('^[%s]+$' % allChars, source): return "0000"
How does soundex1a.py perform? For convenience, the __main__ section of the script contains this code that calls the timeit module, sets up a timing test with three different names, tests each name three times, and displays the minimum time for each:
if __name__ == '__main__': from timeit import Timer names = ('Woo', 'Pilgrim', 'Flingjingwaller') for name in names: statement = "soundex('%s')" % name t = Timer(statement, "from __main__ import soundex") print name.ljust(15), soundex(name), min(t.repeat())
So how does soundex1a.py perform with this regular expression?
C:\samples\soundex\stage1>python soundex1a.py Woo W000 19.3356647283 Pilgrim P426 24.0772053431 Flingjingwaller F452 35.0463220884
As you might expect, the algorithm takes significantly longer when called with longer names. There will be a few things we can do to narrow that gap (make the function take less relative time for longer input), but the nature of the algorithm dictates that it will never run in constant time.
The other thing to keep in mind is that we are testing a representative sample of names. Woo is a kind of trivial case, in that it gets shorted down to a single letter and then padded with zeros. Pilgrim is a normal case, of average length and a mixture of significant and ignored letters. Flingjingwaller is extraordinarily long and contains consecutive duplicates. Other tests might also be helpful, but this hits a good range of different cases.
So what about that regular expression? Well, it's inefficient. Since the expression is testing for ranges of characters (A-Z in uppercase, and a-z in lowercase), we can use a shorthand regular expression syntax. Here is soundex/stage1/soundex1b.py:
if not re.search('^[A-Za-z]+$', source): return "0000"
timeit says soundex1b.py is slightly faster than soundex1a.py, but nothing to get terribly excited about:
C:\samples\soundex\stage1>python soundex1b.py Woo W000 17.1361133887 Pilgrim P426 21.8201693232 Flingjingwaller F452 32.7262294509
We saw in Section 15.3, “Refactoring” that regular expressions can be compiled and reused for faster results. Since this regular expression never changes across function calls, we can compile it once and use the compiled version. Here is soundex/stage1/soundex1c.py:
isOnlyChars = re.compile('^[A-Za-z]+$').search def soundex(source): if not isOnlyChars(source): return "0000"
Using a compiled regular expression in soundex1c.py is significantly faster:
C:\samples\soundex\stage1>python soundex1c.py Woo W000 14.5348347346 Pilgrim P426 19.2784703084 Flingjingwaller F452 30.0893873383
But is this the wrong path? The logic here is simple: the input source needs to be non-empty, and it needs to be composed entirely of letters. Wouldn't it be faster to write a loop checking each character, and do away with regular expressions altogether?
Here is soundex/stage1/soundex1d.py:
if not source: return "0000" for c in source: if not ('A' <= c <= 'Z') and not ('a' <= c <= 'z'): return "0000"
It turns out that this technique in soundex1d.py is not faster than using a compiled regular expression (although it is faster than using a non-compiled regular expression):
C:\samples\soundex\stage1>python soundex1d.py Woo W000 15.4065058548 Pilgrim P426 22.2753567842 Flingjingwaller F452 37.5845122774
Why isn't soundex1d.py faster? The answer lies in the interpreted nature of Python. The regular expression engine is written in C, and compiled to run natively on your computer. On the other hand, this loop is written in Python, and runs through the Python interpreter. Even though the loop is relatively simple, it's not simple enough to make up for the overhead of being interpreted. Regular expressions are never the right answer... except when they are.
It turns out that Python offers an obscure string method. You can be excused for not knowing about it, since it's never been mentioned in this book. The method is called isalpha(), and it checks whether a string contains only letters.
This is soundex/stage1/soundex1e.py:
if (not source) and (not source.isalpha()): return "0000"
How much did we gain by using this specific method in soundex1e.py? Quite a bit.
C:\samples\soundex\stage1>python soundex1e.py Woo W000 13.5069504644 Pilgrim P426 18.2199394057 Flingjingwaller F452 28.9975225902
Example 18.3. Best Result So Far: soundex/stage1/soundex1e.py
import string, re charToSoundex = {"A": "9", "B": "1", "C": "2", "D": "3", "E": "9", "F": "1", "G": "2", "H": "9", "I": "9", "J": "2", "K": "2", "L": "4", "M": "5", "N": "5", "O": "9", "P": "1", "Q": "2", "R": "6", "S": "2", "T": "3", "U": "9", "V": "1", "W": "9", "X": "2", "Y": "9", "Z": "2"} def soundex(source): if (not source) and (not source.isalpha()): return "0000" source = source[0].upper() + source[1:] digits = source[0] for s in source[1:]: s = s.upper() digits += charToSoundex[s] digits2 = digits[0] for d in digits[1:]: if digits2[-1] != d: digits2 += d digits3 = re.sub('9', '', digits2) while len(digits3) < 4: digits3 += "0" return digits3[:4] if __name__ == '__main__': from timeit import Timer names = ('Woo', 'Pilgrim', 'Flingjingwaller') for name in names: statement = "soundex('%s')" % name t = Timer(statement, "from __main__ import soundex") print name.ljust(15), soundex(name), min(t.repeat())
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