# Dive Into Python

Python from novice to pro

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## Chapter 7. Regular Expressions

Regular expressions are a powerful and standardized way of searching, replacing, and parsing text with complex patterns of characters. If you've used regular expressions in other languages (like Perl), the syntax will be very familiar, and you get by just reading the summary of the `re` module to get an overview of the available functions and their arguments.

## 7.1. Diving In

Strings have methods for searching (`index`, `find`, and `count`), replacing (`replace`), and parsing (`split`), but they are limited to the simplest of cases. The search methods look for a single, hard-coded substring, and they are always case-sensitive. To do case-insensitive searches of a string `s`, you must call `s.lower()` or `s.upper()` and make sure your search strings are the appropriate case to match. The `replace` and `split` methods have the same limitations.

If what you're trying to do can be accomplished with string functions, you should use them. They're fast and simple and easy to read, and there's a lot to be said for fast, simple, readable code. But if you find yourself using a lot of different string functions with `if` statements to handle special cases, or if you're combining them with `split` and `join` and list comprehensions in weird unreadable ways, you may need to move up to regular expressions.

Although the regular expression syntax is tight and unlike normal code, the result can end up being more readable than a hand-rolled solution that uses a long chain of string functions. There are even ways of embedding comments within regular expressions to make them practically self-documenting.