Regular Expressions

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Regular expressions, also known as regex or regexp, are a powerful tool used to match patterns in text. In this summary, we'll cover the basics of regular expressions and provide examples using Python's built-in re module.

What is a Regular Expression?

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A regular expression is a pattern that describes a set of strings. It's a way to describe the structure of text data, including characters, sequences, and patterns.

Basic Elements of Regular Expressions

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• Character Classes: [abc] matches any of a, b, or c

Repetition: a matches zero or more as

• Concatenation: ab matches the sequence a followed by b
• Alternation: (a|b) matches either a or b

Common Patterns in Regular Expressions

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• \w: word character (equivalent to [a-zA-Z0-9_])
• \d: digit
• \s: whitespace character
• \D: non-digit character
• \S: non-whitespace character

Example 1: Matching a Phone Number

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python
import re
phone_number = "123-456-7890"
pattern = r"\d{3}-\d{3}-\d{4}"
if re.match(pattern, phone_number):
    print("Phone number matches pattern")
else:
    print("Phone number does not match pattern")

In this example, the regular expression \d{3}-\d{3}-\d{4} matches any string that contains three digits followed by a hyphen, three more digits, and another hyphen, followed by four digits.

Example 2: Finding All Words Containing "e"

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python
import re
text = "Hello world, this is an example sentence."
pattern = r"\b\we\w\b"
words = re.findall(pattern, text)
print(words)  # Output: ['example', 'sentence']

In this example, the regular expression \b\we\w\b matches any word that contains the character e. The \b anchors match word boundaries.

Example 3: Replacing All Occurrences of a Pattern

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python
import re
text = "Hello world, this is an example sentence."
pattern = r"\bexample\b"
replacement = "sample"
new_text = re.sub(pattern, replacement, text)
print(new_text)  # Output: "Hello world, this is a sample sentence."

In this example, the re.sub function replaces all occurrences of the pattern \bexample\b with the string "sample".

Conclusion

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Regular expressions are a powerful tool for text processing in Python. With the basics and examples provided above, you're ready to start using regex patterns to match and manipulate text data.