learn-python/contrib/advanced-python/regular_expressions.md

## Regular Expressions in Python
Regular expressions (regex) are a powerful tool for pattern matching and text manipulation. 
Python's re module provides comprehensive support for regular expressions, enabling efficient text processing and validation.
Regular expressions (regex) are a versitile tool for matching patterns in strings. In Python, the `re` module provides support for working with regular expressions.

## 1. Introduction to Regular Expressions
A regular expression is a sequence of characters defining a search pattern. Common use cases include validating input, searching within text, and extracting 
specific patterns.

## 2. Basic Syntax
Literal Characters: Match exact characters (e.g., abc matches "abc").
Metacharacters: Special characters like ., *, ?, +, ^, $, [ ], and | used to build patterns.

**Common Metacharacters:**

* .: Any character except newline.
* ^: Start of the string.
* $: End of the string.
* *: 0 or more repetitions.
* +: 1 or more repetitions.
* ?: 0 or 1 repetition.
* []: Any one character inside brackets (e.g., [a-z]).
* |: Either the pattern before or after.
* \ : Used to drop the special meaning of character following it
* {} : Indicate the number of occurrences of a preceding regex to match.
* () : Enclose a group of Regex

Examples:
```bash
1. `.`
import re
pattern = r'c.t'
text = 'cat cot cut cit'
matches = re.findall(pattern, text)
print(matches)  # Output: ['cat', 'cot', 'cut', 'cit']

2. `^`
pattern = r'^Hello'
text = 'Hello, world!'
match = re.search(pattern, text)
print(match.group() if match else 'No match')  # Output: 'Hello'

3. `$`
pattern = r'world!$'
text = 'Hello, world!'
match = re.search(pattern, text)
print(match.group() if match else 'No match')  # Output: 'world!'

4. `*`
pattern = r'ab*'
text = 'a ab abb abbb'
matches = re.findall(pattern, text)
print(matches)  # Output: ['a', 'ab', 'abb', 'abbb']

5. `+`
pattern = r'ab+'
text = 'a ab abb abbb'
matches = re.findall(pattern, text)
print(matches)  # Output: ['ab', 'abb', 'abbb']

6. `?`
pattern = r'ab?'
text = 'a ab abb abbb'
matches = re.findall(pattern, text)
print(matches)  # Output: ['a', 'ab', 'ab', 'ab']

7. `[]`
pattern = r'[aeiou]'
text = 'hello world'
matches = re.findall(pattern, text)
print(matches)  # Output: ['e', 'o', 'o']

8. `|`
pattern = r'cat|dog'
text = 'I have a cat and a dog.'
matches = re.findall(pattern, text)
print(matches)  # Output: ['cat', 'dog']

9. `\``
pattern = r'\$100'
text = 'The price is $100.'
match = re.search(pattern, text)
print(match.group() if match else 'No match')  # Output: '$100'

10. `{}`
pattern = r'\d{3}'
text = 'My number is 123456'
matches = re.findall(pattern, text)
print(matches)  # Output: ['123', '456']

11. `()`
pattern = r'(cat|dog)'
text = 'I have a cat and a dog.'
matches = re.findall(pattern, text)
print(matches)  # Output: ['cat', 'dog']

```

## 3. Using the re Module

**Key functions in the re module:**

* re.match(): Checks for a match at the beginning of the string.
* re.search(): Searches for a match anywhere in the string.
* re.findall(): Returns a list of all matches.
* re.sub(): Replaces matches with a specified string.
* re.split(): Returns a list where the string has been split at each match.
* re.escape(): Escapes special character
Examples:
```bash
import re

# Match at the beginning
print(re.match(r'\d+', '123abc').group())  # Output: 123

# Search anywhere
print(re.search(r'\d+', 'abc123').group())  # Output: 123

# Find all matches
print(re.findall(r'\d+', 'abc123def456'))  # Output: ['123', '456']

# Substitute matches
print(re.sub(r'\d+', '#', 'abc123def456'))  # Output: abc#def#

#Return a list where it get matched 
print(re.split("\s", txt)) #['The', 'Donkey', 'in', 'the','Town']

# Escape special character
print(re.escape("We are good to go"))  #We\ are\ good\ to\ go
```

## 4. Compiling Regular Expressions
Compiling regular expressions improves performance for repeated use.

Example:
```bash
import re

pattern = re.compile(r'\d+')
print(pattern.match('123abc').group())  # Output: 123
print(pattern.search('abc123').group())  # Output: 123
print(pattern.findall('abc123def456'))  # Output: ['123', '456']

```

## 5. Groups and Capturing
Parentheses () group and capture parts of the match.

Example:
```bash
import re

match = re.match(r'(\d{3})-(\d{2})-(\d{4})', '123-45-6789')
if match:
    print(match.group())   # Output: 123-45-6789
    print(match.group(1))  # Output: 123
    print(match.group(2))  # Output: 45
    print(match.group(3))  # Output: 6789
```

## 6. Special Sequences
Special sequences are shortcuts for common patterns:

* \A:Returns a match if the specified characters are at the beginning of the string.
* \b:Returns a match where the specified characters are at the beginning or at the end of a word.
* \B:Returns a match where the specified characters are present, but NOT at the beginning (or at the end) of a word.
* \d: Any digit.
* \D: Any non-digit.
* \w: Any alphanumeric character.
* \W: Any non-alphanumeric character.
* \s: Any whitespace character.
* \S: Any non-whitespace character.
* \Z:Returns a match if the specified characters are at the end of the string.

Example:
```bash
import re

print(re.search(r'\w+@\w+\.\w+', 'Contact: support@example.com').group())  # Output: support@example.com
```
## 7.Sets
A set is a set of characters inside a pair of square brackets [] with a special meaning:

* [arn]	: Returns a match where one of the specified characters (a, r, or n) is present.
* [a-n] : Returns a match for any lower case character, alphabetically between a and n.
* [^arn] : Returns a match for any character EXCEPT a, r, and n.
* [0123] : Returns a match where any of the specified digits (0, 1, 2, or 3) are present.
* [0-9]	: Returns a match for any digit between 0 and 9.
* [0-5][0-9] : Returns a match for any two-digit numbers from 00 and 59.
* [a-zA-Z] : Returns a match for any character alphabetically between a and z, lower case OR upper case.
* [+] : In sets, +, *, ., |, (), $,{} has no special meaning, so [+] means: return a match for any + character in the string.

## Summary
Regular expressions (regex) are a powerful tool for text processing in Python, offering a flexible way to match, search, and manipulate text patterns. The re module provides a comprehensive set of functions and metacharacters to tackle complex text processing tasks.
With regex, you can:
1.Match patterns: Use metacharacters like ., *, ?, and {} to match specific patterns in text.
2.Search text: Employ functions like re.search() and re.match() to find occurrences of patterns in text.
3.Manipulate text: Utilize functions like re.sub() to replace patterns with new text.