Quantifiers (Repetition) in Python Regular Expressions – Detailed Explanation Basic Quantifiers 1. * – 0 or more occurrences (Greedy) Description: Matches the preceding element zero or more times Example 1: Match zero or more digits python import re text = “123 4567 89″ result = re.findall(r’\d*’, text) print(result) # [‘123’, ”, ‘4567’, ”, ’89’, ”] # Matches…

Anchors (Position Matchers) in Python Regular Expressions – Detailed Explanation Basic Anchors 1. ^ – Start of String/Line Anchor Description: Matches the start of a string, or start of any line when re.MULTILINE flag is used Example 1: Match at start of string python import re text = “Python is great\nPython is powerful” result = re.findall(r’^Python’, text) print(result) #…

Special Character Classes Explained with Examples 1. [\\\^\-\]] – Escaped special characters in brackets Description: Matches literal backslash, caret, hyphen, or closing bracket characters inside character classes Example 1: Matching literal special characters python import re text = “Special chars: \\ ^ – ] [” result = re.findall(r'[\\\^\-\]]’, text) print(result) # [‘\\’, ‘^’, ‘-‘, ‘]’] # Matches…

Combined Character Classes Explained with Examples 1. [a-zA-Z0-9_] – Word characters (same as \w) Description: Matches any letter (lowercase or uppercase), any digit, or underscore Example 1: Extract all word characters from text python import re text = “User_name123! Email: test@example.com” result = re.findall(r'[a-zA-Z0-9_]’, text) print(result) # [‘U’, ‘s’, ‘e’, ‘r’, ‘_’, ‘n’, ‘a’, ‘m’, ‘e’, ‘1’, ‘2’,…

Predefined Character Classes Pattern Description Equivalent . Matches any character except newline \d Matches any digit [0-9] \D Matches any non-digit [^0-9] \w Matches any word character [a-zA-Z0-9_] \W Matches any non-word character [^a-zA-Z0-9_] \s Matches any whitespace character [ \t\n\r\f\v] \S Matches any non-whitespace character [^ \t\n\r\f\v] 1. Literal Character a Matches: The exact character…

Basic Character Classes Pattern Description Example Matches [abc] Matches any single character in the brackets a, b, or c [^abc] Matches any single character NOT in the brackets d, 1, ! (not a, b, or c) [a-z] Matches any character in the range a to z a, b, c, …, z [A-Z] Matches any character in the range A to Z A, B, C, …, Z [0-9] Matches…

Complete List of Basic Regular Expression Patterns in Python Character Classes Pattern Description Example [abc] Matches any one of the characters a, b, or c [aeiou] matches any vowel [^abc] Matches any character except a, b, or c [^0-9] matches non-digits [a-z] Matches any character in range a to z [a-z] matches lowercase letters [A-Z] Matches any character in range…

Raw Strings in Python’s re Module Raw strings (prefixed with r) are highly recommended when working with regular expressions because they treat backslashes (\) as literal characters, preventing Python from interpreting them as escape sequences. path = ‘C:\Users\Documents’ pattern = r’C:\Users\Documents’ .4.1.1. Escape sequences Unless an ‘r’ or ‘R’ prefix is present, escape sequences in string and bytes literals are interpreted according…

The re module is Python’s built-in module for regular expressions (regex). It provides functions and methods to work with strings using pattern matching, allowing you to search, extract, replace, and split text based on complex patterns. Key Functions in the re Module 1. Searching and Matching python import re text = “The quick brown fox jumps over the lazy dog” # re.search()…

# Read the original image and write to a new file original_file = open(‘image.jpg’, ‘rb’) # ‘rb’ = read binary copy_file = open(‘image_copy.jpg’, ‘wb’) # ‘wb’ = write binary # Read and write in chunks to handle large files while True: chunk = original_file.read(4096) # Read 4KB at a time if not chunk: break copy_file.write(chunk)…