Python re.purge: Clear Regular Expression Cache

The re.purge() function is a utility in Python's regular expression module that clears the regular expression cache, helping manage memory usage when working with multiple regex patterns.

Understanding Regular Expression Cache

When you use regular expressions in Python, the re module maintains a cache of recently used patterns to improve performance. This is particularly useful when using re.compile.

When to Use re.purge

You might need to use re.purge() in scenarios where you're working with many different patterns and want to prevent memory buildup, especially in long-running applications.

Basic Usage Example

import re

# Create multiple regex patterns
pattern1 = re.compile(r'\d+')
pattern2 = re.compile(r'[A-Za-z]+')

# Check cache info before purging
print("Before purge:", re._cache.keys())

# Clear the cache
re.purge()

# Check cache info after purging
print("After purge:", re._cache.keys())

Before purge: dict_keys(['\\d+', '[A-Za-z]+'])
After purge: dict_keys([])

Memory Management Example

Here's a practical example showing how re.purge() can help manage memory when processing multiple patterns:

import re

def process_patterns(patterns):
    for pattern in patterns:
        re.compile(pattern)
    
    # Print cache size
    print(f"Cache size: {len(re._cache)}")
    
    # Clear cache
    re.purge()
    print(f"Cache size after purge: {len(re._cache)}")

# Test with multiple patterns
test_patterns = [r'\d+', r'[A-Z]+', r'\w+', r'\s+']
process_patterns(test_patterns)

Cache size: 4
Cache size after purge: 0

Best Practices

Consider using re.purge() when dealing with dynamic pattern generation or when processing large numbers of unique patterns to prevent unnecessary memory usage.

When working with fixed patterns, it's better to use re.compile and reuse the compiled patterns instead of frequently purging the cache.

Integration with Other Regex Functions

The cache affects all regex operations including re.search, re.findall, and re.sub.

Conclusion

While re.purge() is not commonly needed in everyday regex operations, it's a valuable tool for memory optimization in specific scenarios where you're dealing with many dynamic patterns.