In this case block_size actually means character count instead of byte count.Python Dictionaries Access Items Change Items Add Items Remove Items Loop Dictionaries Copy Dictionaries Nested Dictionaries Dictionary Methods Dictionary Exercise Python If.Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Scope Python Modules Python Dates Python Math Python JSON Python RegEx Python PIP Python Try. One more thing: Parsing in unicode should work as long as the passed in stream is producing unicode strings, and if you're using the character classes like \w, you'll need to add the re.U flag to the re.compile pattern construction. With glob, we can also use wildcards (',, ranges) apart from. It is also predicted that according to benchmarks it is faster than other methods to match pathnames in directories. The pattern rules of glob follow standard Unix path expansion rules. I'm kind of surprised recipes like this aren't more readily available on the net! In Python, the glob module is used to retrieve files/pathnames matching a specified pattern. But I've used it for tons of other purposes as well. It also allows you to filter through XML faster as well.
This can be useful in conjunction with quick-parsing a large XML where it can be split up into mini-DOMs based on a sub element as root, instead of having to dive into handling callbacks and states when using a SAX parser. Here is the output: found regex in block of len 46/23: "testing this is a ]]\nanother 2regexx\nmor"įound regex in block of len 46/23: "testing this is a 1regexxx\nanother ]]\nmor"įound regex in block of len 14/23: "\nmore ]]es" Print 'found regex in block of len %s/%s: "%s]]%s"'%(īlock_size,match_('string_escape'), Re_pattern=re.compile(r'\dregex+',re.DOTALL)įor match_obj in regex_stream(re_pattern,t_in,block_size=block_size): T_in=cStringIO.StringIO('testing this is a 1regexxx\nanother 2regexx\nmore 3regexes')īlock_size=len('testing this is a regex') To test / explore, you can run this: # NOTE: you can substitute a real file stream here for t_in but using this as a test import reĭef regex_stream(regex,stream,block_size=128*1024):īlock='%s%s'%(block,new_buffer) You may still be able to break things if you have a lookahead at the end of the regex like xx(?!xyz) where yz is in the next block, but in most cases you can work around using such patterns. It also makes sure that any regex match that eats to the end of the current block is NOT yielded and instead the last position is saved for when either the true input is exhausted or we have another block that the regex matches before the end of, in order to better match patterns like "+" or "xxx$".
You might want to enforce at least 1 match per block as a sanity check in some use cases, but this method will truncate in order to keep the maximum of 2 blocks in memory. The method will make sure to only keep a maximum of 2 blocks in memory. It probably depends more on what you're doing with the matches, as well as the size/complexity of the regex you're searching for. This solution works plenty fast, although I suspect it will be marginally slower than using mmap. Also note you are not restricted by using single-line regexes. Here is a solution that reads 128k blocks at a time and as long as your regex matches a string smaller than that size, this will work. Memory mapped files may not be ideal for your situation (32-bit mode increases chance there isn't enough contiguous virtual memory, can't read from pipes or other non-files, etc). You may have to tweak things in python 3 to handle strings vs bytes but it shouldn't be too painful hopefully.
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