正則表達式在Python中用于字符串的匹配、提取和替換。1. 使用re.match從字符串開頭匹配，re.search查找整個字符串首個匹配；2. 用捕獲組()提取部分匹配內(nèi)容，也可命名組以提升可讀性；3. re.sub用于替換匹配文本，支持引用捕獲組；4. 注意默認不匹配換行符、可使用標志位如re.IGNORECASE、重復(fù)使用模式建議編譯以提高性能。掌握這些能有效提升文本處理效率。

Handling text data in Python often involves searching, matching, or manipulating strings based on specific patterns. The re module, short for regular expressions, is a built-in tool that helps you do exactly that.

Matching Patterns with re.match and re.search

If you want to check whether a string starts with a certain pattern, use re.match. It only checks from the beginning of the string.
For example:

import re
result = re.match(r'\d ', '123abc')
print(result.group())  # Outputs: 123

But if the match might appear anywhere in the string, go with re.search. It scans through the entire string:

result = re.search(r'\d ', 'abc123def')
print(result.group())  # Outputs: 123

• Use match when position matters.
• Use search when you just need to find the first occurrence anywhere.

Both return a match object, which you can call .group() on to get the matched text.

Extracting Specific Parts with Groups

Sometimes you don’t just want to know if a match exists — you want to extract parts of it. That’s where capture groups come in handy.

Let's say you're parsing dates like '2024-05-15' and want to pull out year, month, and day:

match = re.search(r'(\d{4})-(\d{2})-(\d{2})', 'Date: 2024-05-15')
if match:
    print(match.group(1))  # Year: 2024
    print(match.group(2))  # Month: 05
    print(match.group(3))  # Day: 15

You can also name your groups for clarity:

match = re.search(r'(?P<year>\d{4})-(?P<month>\d{2})-(?P<day>\d{2})', 'Date: 2024-05-15')
print(match.group('month'))  # Outputs: 05

This makes it easier to reference later, especially with complex patterns.

Replacing Text Using re.sub

When you need to replace parts of a string based on a pattern, re.sub is your friend.

A common use case is cleaning up messy input. For example, removing extra spaces or normalizing phone numbers:

cleaned = re.sub(r'\s ', ' ', 'This   has   too     many   spaces.')
# Result: 'This has too many spaces.'

Or stripping non-digit characters from a phone number:

phone = re.sub(r'\D', '', '(123) 456-7890')
# Result: '1234567890'

The syntax is simple:
re.sub(pattern, replacement, string)
And if you need to refer to capture groups in the replacement, use \1, \2, etc.

A Few Gotchas and Tips

• Dot doesn't match newlines by default. If you want . to include newlines, use the re.DOTALL flag.
• Case-insensitive matching: Add re.IGNORECASE or re.I.
• Compiling patterns: If you reuse the same regex multiple times, compile it once using re.compile() for better performance.

Example with flags:

match = re.search(r'hello', 'HELLO world', re.IGNORECASE)

Compiling:

pattern = re.compile(r'\d ')
match = pattern.search('abc123def')

Regular expressions are powerful but can get tricky fast. Start small, test your patterns, and don’t be afraid to break them into parts. Once you get the hang of it, re becomes one of the most useful tools in your Python toolbox.

基本上就這些。

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