Regular Expressions in Python - Lecture Notes

Introduction

• Topic: Working with regular expressions (regex) using Python's re module
• Definition: Regex provides a method to search and match text patterns
• Usage: Can be used across various programming languages, text editors, etc.
• Importance: Useful for searching, modifying, and manipulating text based on patterns

Setting Up

• Importing re module: import re
• Text to Search: Can be a multi-line string containing various text patterns (e.g., lower and upper case letters, digits, URLs, phone numbers, etc.)
• Raw Strings: Strings prefixed with r (e.g., r'string') to avoid special treatment of backslashes

Basic Regex Functions

• Compiling Patterns: re.compile(pattern)
• Finding Matches: pattern.finditer(text) returns an iterator of match objects
• Match Objects: Contains information like span (start and end indices) and group (matched text)
• String Slicing: Using text[span[0]:span[1]] for exact matches

Special Characters & Meta Characters

• Literal Matches: Direct text matches
• Escaping Characters: Use backslash () to escape special characters (e.g., . becomes \.)
• Dot (.): Matches any character except newline
• Digit (\d): Matches a digit (0-9)
• Non-digit (\D): Matches any character except a digit
• Word Character (\w): Matches alphanumeric characters and underscore
• Non-word Character (\W): Matches any character except alphanumeric and underscore
• Whitespace (\s): Matches any whitespace character (space, tab, newline)
• Non-whitespace (\S): Matches any non-whitespace character
• Anchors: ^ (start of string) and $ (end of string)
• Word Boundaries: \b (word boundary), \B (non-word boundary)

Character Sets

• Syntax: Square brackets [ ] to match any one character inside
• Example: [a-z] matches any lowercase letter
• Negation: [^...] matches any character not inside the brackets

Quantifiers

• Asterisk (*): Zero or more
• Plus (+): One or more
• Question Mark (?): Zero or one
• Curly Braces {n}: Exact number
• Curly Braces Range {min,max}: Range of numbers

Practical Examples

• Matching phone numbers using meta characters, character sets, and quantifiers
• Parsing data from text files using regex patterns
• Validation and pattern matching (e.g., URLs, email addresses)

Groups

• Grouping Patterns: Use parentheses ( ) to create groups
• Capture and Reference: Capture parts of the pattern and reference them using backreferences
• Example: Capturing domain and top-level domain in URLs

Substitution

• Substitution Method: pattern.sub(replacement, text)
• Backreferences in Substitution: Use \num where num is the group number

Additional Methods

• findall: Returns a list of all matches
• match: Checks for a match only at the beginning of the string
• search: Searches the entire string for a match

Flags

• Ignore Case: re.IGNORECASE or re.I
• Multi-line Mode: re.MULTILINE or re.M
• Verbose Mode: re.VERBOSE or re.X for readable regex

Conclusion

• Regular expressions are powerful tools for text pattern matching and manipulation
• Practice and familiarity are key to mastering regex
• Future videos will cover advanced topics in regex for deeper understanding

Questions: Feel free to ask questions or request further explanations in the comments or discussion forums.