Python regular expression cheat sheet

Sharon 185 Published: 08/19/2024

Python regular expression cheat sheet

I'd be delighted to provide you with a comprehensive Python regular expression (regex) cheat sheet!

Pattern Syntax

Python regex patterns are defined using the re module, which provides several functions for searching and manipulating text:

re.compile(pattern): Compiles a pattern into a regex object. re.search(pattern, string): Searches for the first occurrence of the pattern in the given string. re.match(pattern, string): Searches for the pattern at the beginning of the given string.

Basic Patterns

Literal: Matches any literal character (e.g., ., [, (, etc.).

Example: r'.`` matches a dot (.`)

Wildcard: Matches any single character (except newline).

Example: r'*' matches zero or more of the preceding character

Set Characters: Matches any character in the specified set.

Example: r'[abc]' matches either 'a', 'b', or 'c'

Range: Matches any character within a specified range.

Example: r'[0-9]' matches any digit (0-9)

Escape Characters: Escapes special characters, making them literal.

Example: r'(' matches the opening parenthesis (()

Special Patterns

Dot (.): Matches any single character (except newline).

Example: r'abc.def' matches 'abc.' followed by any single character

Star (*): Matches zero or more of the preceding pattern.

Example: r'a.*' matches 'a' followed by zero or more characters

Plus (+): Matches one or more of the preceding pattern.

Example: r'a+' matches 'a' repeated one or more times

Question Mark (?): Matches zero or one of the preceding pattern.

Example: r'a?' matches either an 'a' or no 'a'

Curly Braces ({}) and (^): {n,m}: Matches exactly n to m occurrences. {n,}: Matches at least n occurrences. ^{pattern}: Matches the start of a string.

Example: r'a{2,3}' matches 'a' repeated between 2 and 3 times

Alternation (|): Matches either pattern A or B.

Example: r'(abc|def)' matches either 'abc' or 'def'

Groups (()): Defines a capturing group.

Example: r'(abc)+(' matches 'abc' repeated one or more times

Lookarounds: Matches the pattern only if preceded/followed by another specific pattern. (?=pattern) : Positive lookahead. (?!pattern) : Negative lookahead. (?<=pattern) : Positive lookbehind. (?<!pattern) : Negative lookbehind.

Example: r'Hello (?=w+)' matches 'Hello' followed by one or more word characters

Flags

re.IGNORECASE: Makes the pattern case-insensitive.

Example: re.compile(r"hello", re.IGNORECASE).search("HELLO")

re.MULTILINE: Treats the string as multiple lines (when using '^' and '$').

Example: re.compile(r"^hello$", re.MULTILINE).search("hello worldnhello again")

re.DOTALL: Allows '.' to match newline characters.

Example: re.compile(r".*hello.*", re.DOTALL).search("Hello, World!nhello friend!")

Common Tasks

Validation: Verifies a string matches a pattern.

Example: re.match(r"[a-zA-Z]+", "Hello") returns the first match

Replacement: Replaces parts of a string matching a pattern.

Example: re.sub(r"old", "new", "old is gold") replaces 'old' with 'new'

Splitting: Splits a string into substrings based on a delimiter.

Example: re.split(r"W+", "Hello, World!")) splits the string by non-alphanumeric characters

Finding: Finds all occurrences of a pattern in a string.

Example: re.findall(r"[a-zA-Z]+", "Hello, World! 123 abc") returns all matches

Substitution: Substitutes parts of a string matching a pattern.

Example: re.subn(r"(d+)", lambda x: str(int(x.group(1)) + 1), "abc123def456")) replaces numbers with incremented values

Conclusion

This comprehensive Python regex cheat sheet covers the basics, special patterns, and flags. Familiarize yourself with these concepts to master the art of text manipulation in Python!

What is the difference between regex and re in Python?

I'd be happy to explain the difference between regex (regular expressions) and re in Python.

Regular expressions, commonly abbreviated as regex, are a powerful way of describing patterns in strings. They're used to match, search, and validate text data according to certain rules or constraints. Regex allows you to define complex patterns using various syntax elements such as characters, sets, ranges, and quantifiers. You can use regex for tasks like extracting information from text files, filtering data, validating email addresses, and more.

On the other hand, re is a Python module that provides support for regular expressions. It's part of the Python Standard Library and offers an interface to work with regex patterns. The re module allows you to compile, match, and manipulate strings using regex.

So what's the difference between regex and re? Well, regex refers specifically to the syntax and rules used in pattern matching, while re is a module that implements these regex capabilities within Python.

Here are some key differences:

Syntax: Regex syntax is used to define patterns for matching text data. In contrast, the re module follows Python's own syntax conventions. You use Python-specific constructs like variables, lists, dictionaries, and more when working with re. Compilation: When using regex in non-Python contexts, you usually need to compile the pattern before searching or validating text data. However, if you're using the re module within Python, it automatically compiles the pattern for you when you call its functions like re.search() or re.compile().

Matching: The core task of regex is matching text against a defined pattern. When working with the re module in Python, you can use various methods like re.search(), re.match(), or re.findall() to find matches within text. Substitution: Another important function of regex is substitution: replacing parts of a string based on specific patterns. The re module also provides functions like re.sub() and re.subn() for this purpose, allowing you to substitute strings based on your regular expressions. Flags and options: Depending on the regex flavor or library being used, some features may be available or not. Python's re module, however, follows specific rules regarding flag usage. For instance, if you set re.IGNORECASE, all matches become case-insensitive within the scope of that pattern. Error handling: In Python, exceptions can occur when dealing with regex patterns, such as when there are invalid characters or when no match is found. The re module handles these errors in a specific way: it raises exceptions like re.error and re.error.

In summary, regex refers to the general concept of pattern matching and validation using specific syntax rules. The re module, part of Python's Standard Library, provides an interface for working with regex patterns within Python. It offers functions for compilation, matching, substitution, flag usage, and error handling.

If you're new to both regex and the re module, I hope this clarification helps!