Performance Implications of Python's re.compile
In Python, the re module provides functionality for working with regular expressions. One question that often arises is whether there is a performance benefit in using the re.compile method to pre-compile regular expressions.
Using re.compile vs. Direct Matching
Consider the following two code snippets:
h = re.compile('hello') h.match('hello world')
re.match('hello', 'hello world')
The first snippet pre-compiles the regular expression 'hello' using re.compile() and then uses the compiled pattern to perform the match. The second snippet simply uses the re.match() function directly to perform the match.
Anecdotal Evidence and Code Analysis
Some users report that they have not observed any significant performance difference between using re.compile() and direct matching. This is supported by the fact that Python internally compiles regular expressions and caches them when they are used (including calls to re.match()).
The code analysis of the re module in Python 2.5 reveals that:
def match(pattern, string, flags=0): return _compile(pattern, flags).match(string) def _compile(*key): cachekey = (type(key[0]),) + key p = _cache.get(cachekey) if p is not None: return p # Actual compilation on cache miss if len(_cache) >= _MAXCACHE: _cache.clear() _cache[cachekey] = p return p
This shows that the primary difference between using re.compile() and direct matching is the timing of the compilation process. re.compile() forces the compilation to occur before the match is performed, while direct matching compiles the regular expression internally when the match function is called.
Conclusion
While pre-compiling regular expressions with re.compile() does not appear to offer significant performance gains, it can be useful for organizing and naming reusable patterns. However, it is important to be aware that Python caches compiled regular expressions internally, potentially reducing the perceived benefit of pre-compilation.
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