Delving Deeper

Regular Expressions

Pattern Syntax

Regular expressions support more powerful patterns than simple literal text strings. Patterns can repeat, can be anchored to different logical locations within the input, and can be expressed in compact forms that do not require every literal character to be present in the pattern. All of these features are used by combining literal text values with meta-characters that are part of the regular expression pattern syntax implemented by re.

# re_test_patterns.py

import re


def test_patterns(text, patterns):
    """Given source text and a list of patterns, look for
    matches for each pattern within the text and print
    them to stdout.
    """
    # Look for each pattern in the text and print the results
    for pattern, desc in patterns:
        print("'{}' ({})\n".format(pattern, desc))
        print("  '{}'".format(text))
        for match in re.finditer(pattern, text):
            s = match.start()
            e = match.end()
            substr = text[s:e]
            n_backslashes = text[:s].count('\\')
            prefix = '.' * (s + n_backslashes)
            print("  {}'{}'".format(prefix, substr))
        print()
    return


if __name__ == '__main__':
    test_patterns('abbaaabbbbaaaaa',
                  [('ab', "'a' followed by 'b'"),
                   ])

The following examples will use test_patterns() to explore how variations in patterns change the way they match the same input text. The output shows the input text and the substring range from each portion of the input that matches the pattern.

$ python3 re_test_patterns.py

'ab' ('a' followed by 'b')

  'abbaaabbbbaaaaa'
  'ab'
  .....'ab'