Regex Pattern Matching in Python 3

in

The syntax for regex pattern matching in Python 3 is similar to other popular programming languages like Perl and Ruby, but it provides module-level functions called match(), search(), findall(), sub(), etc., which take an RE string added as the first argument. These functions return either None or a match object instance depending on whether a match was found.

Compilation flags are also available in Python 3’s regex pattern matching feature, allowing you to modify some aspects of how regular expressions work. For example, re.I (IGNORECASE) performs case-insensitive matching while re.L (LOCALE) makes \w, \W, \b, and \B dependent on the current locale instead of the default behavior.

One of the most significant features in Python’s regex pattern matching is named groups. Instead of referring to them by numbers, groups can be referenced by a name using one of the Python-specific extensions: (?P…). Named groups behave exactly like capturing groups and additionally associate a name with a group. The match object methods that deal with capturing groups all accept either integers or strings containing the desired group’s name, allowing you to retrieve information about a group in two ways.

Another useful feature is non-capturing groups: (?:…), where you can replace the … with any other regular expression. Non-capturing groups behave exactly like capturing groups but don’t capture what they match. This syntax is particularly useful when modifying an existing pattern, since you can add new groups without changing how all the other groups are numbered.

However, regex patterns can become lengthy collections of backslashes, parentheses, and metacharacters, making them difficult to read and understand. For such REs, specifying the re.VERBOSE flag when compiling the regular expression can be helpful because it allows you to format the regular expression more clearly. The re.VERBOSE flag has several effects: whitespace in the regular expression that isn’t inside a character class is ignored; comments inside an RE extend from a # character to the next newline, enabling REs to be formatted more neatly.

Here’s an example of how regex pattern matching works:

# Import the regular expression module
import re

# Define a string to search for matches
text = "The quick brown fox jumps over the lazy dog."

# Define a regex pattern to match words with exactly 4 letters
pattern = r'\b\w{4}\b' # \b indicates a word boundary, \w matches any alphanumeric character, {4} specifies the number of characters to match

# Search for a match using the pattern and the text
match = re.search(pattern, text)

# If a match is found, print the matched word
if match:
    print("Found a word:", match.group()) # match.group() returns the matched string

# Output: Found a word: over

This code searches for a word in the given text that has exactly 4 letters using regex pattern matching. If a match is found, it prints out the matched string. The output of this example would be “Found a word: brown”.

SICORPS