Regular expressions in python-markdown2 (part 2)

This article is a look into the performance of one of the regular expressions used in the python-markdown2 Python module for converting Markdown syntax to HTML. It was initially written for pure fun, and in celebration of its own pointlessness, but eventually the changes proposed here made it upstream in pull request 207.

Replace tabs with spaces

This snippet of code replaces tab characters with a predefined number of spaces. It is a Python port of the Perl code mentioned by Bart Lateur in a post about turning tabs to spaces in Perl.

A detour to Perl

The initial post in that thread was replacing tabs like this:

#!/usr/bin/perl -pi
s/\t/    /;

That code misses one point: if there is any string before a tab, it will simply add four spaces after that string. However, that is not how tabs work. What should happen is that enough spaces should be added, until the length of the initial string plus the newly added spaces, add up to the next multiple of four. So, the suggested substitution in Perl becomes:

s/(.*?)\t/$1.(' ' x (4-length($1)%4))/ge;

There are two flags used there: g applies the substitution for all matches of the left pattern ((.*?)\t). Without that flag, only the first match would be processed. The second flag, e, forces the substitute ($1.(' ' x (4-length($1)%4))) to be evaluated as an expression itself. Without this flag, the second part would be handled as a raw string.

Back to Python

Here is the Python code, cleaned up a little:

import re

_detab_re = re.compile(r'(.*?)\t', re.M)
def _detab_sub(match):
    g1 =
    return g1 + (' ' * (DEFAULT_TAB_LENGTH - len(g1) % DEFAULT_TAB_LENGTH))

def _detab(text):
    if '\t' not in text:
        return text
    return _detab_re.subn(_detab_sub, text)[0]


The _detab_re object is a compiled Regular Expression object, built with the same pattern as the one used in the Perl example, and with the multiline flag enabled (re.M). You can test this out at RegExr. The subn() method of that object is called in the last line. It takes two parameters: the _detab_sub() function, and the text to be processed. For every match of the pattern, _detab_sub() is called, and the matched string is passed to the _detab_sub() function for processing. Finally, subn() returns a tuple with the text with the pattern substituted, and the number of substitutions that happened. From that result, only the text is kept, with that subn()[0], which seems a bit redundant, since the sub() method would do that without requiring the [0] subscription.

No regular expressions please

Here is a Python snippet that does the same thing as the previous one, without using regular expressions:


def _detab_no_re_sub(l):
    if '\t' not in l:
        return l
        g1 = l.split('\t', 1)[0]
        output = g1
        output += (' ' * (DEFAULT_TAB_LENGTH - len(g1) % DEFAULT_TAB_LENGTH))
        output += l.split('\t', 1)[1]
        return _detab_no_re_sub(output)

def _detab_no_re(text):
    if not '\t' in text:
        return text
    output = []
    for line in text.splitlines():
    return '\n'.join(output)


In the previous article on regular expressions in python-markdown2 I dismissed the difference between a substring substitution with re.sub() versus str.replace() as being negligible, but in this case it seems that it is more substantial. This simple example already indicates some difference:

text = '''
We are
in Kansas
        any more!

%timeit _detab(text)
100000 loops, best of 3: 6.14 us per loop

%timeit _detab_no_re(text)
100000 loops, best of 3: 3.82 us per loop

To test a larger example, I took this version of the source code of bzip2 which uses three spaces for indentation, and made some substitutions in it:

# Change some spaces in the beginning of lines with tabs:
sed -i 's/^   /\t/' bzip2.c 
sed -i 's/^\t   /\t\t/' bzip2.c
# Lines with tabs:
grep -c '\t' bzip2.c 
# Total lines:
wc -l bzip2.c 
6998 bzip2.c

Timing test with this file:

text = file('bzip2.c').read()

%timeit _detab(text)
10 loops, best of 3: 90.1 ms per loop

%timeit _detab_no_re(text)
100 loops, best of 3: 11 ms per loop

That is significant difference, not using regular expressions makes the process about 8 times faster.


Based on this article, and on the previous one, I would prefer to use other methods for substring replacements than regular expressions.