Introduction to Regex Parser

Regex parser is a powerful tool used to analyze and manipulate strings based on regular expressions. In this guide, we will explore the regex-parser library, showcasing dozens of useful API functions with practical code snippets.

API Examples

1. Importing the Regex Parser

First, you need to import the regex-parser to start using its functions:

  
    import regex_parser as rp
  

2. Matching Strings

You can test if a string matches a pattern using match function.

  
    pattern = r"\d+"
    string = "12345"
    result = rp.match(pattern, string)
    print(result)  # Output: True
  

3. Searching Strings

Use search to find a match anywhere in the string:

  
    pattern = r"\d+"
    string = "abc123xyz"
    match = rp.search(pattern, string)
    if match:
        print(f"Found: {match.group()}")  # Output: Found: 123
  

4. Finding All Matches

Extract all matches of a pattern in a string with findall:

  
    pattern = r"\d+"
    string = "123 abc 456 def 789"
    matches = rp.findall(pattern, string)
    print(matches)  # Output: ['123', '456', '789']
  

5. Splitting Strings

Split a string by the occurrences of a pattern using split:

  
    pattern = r"\d+"
    string = "abc123def456ghi"
    parts = rp.split(pattern, string)
    print(parts)  # Output: ['abc', 'def', 'ghi']
  

6. Replacing Substrings

Replace parts of the string that match a pattern using sub:

  
    pattern = r"\d+"
    string = "abc123def"
    new_string = rp.sub(pattern, "-", string)
    print(new_string)  # Output: "abc-def"
  

7. Compiling Patterns

Compile regex patterns for better performance with compile:

  
    pattern = rp.compile(r"\d+")
    matches = pattern.findall("123 abc 456")
    print(matches)  # Output: ['123', '456']
  

8. Using Named Groups

Use named groups for more readable regex patterns:

  
    pattern = r"(?P\d+)"
    string = "123 abc 456"
    match = rp.search(pattern, string)
    if match:
        print(f"Named group 'digits': {match.group('digits')}")  # Output: Named group 'digits': 123
  

Application Example

Simple Log File Analyzer

Let’s build a simple log file analyzer that extracts error messages using the regex-parser library:

  
    import regex_parser as rp

    log = """
    INFO: Starting application...
    ERROR: Failed to connect to database.
    INFO: Retrying connection...
    ERROR: Connection timed out.
    """

    error_pattern = r"ERROR: (.+)"
    errors = rp.findall(error_pattern, log)
    for error in errors:
        print(f"Error message: {error}")
    # Output:
    # Error message: Failed to connect to database.
    # Error message: Connection timed out.
  

With these examples, you can start leveraging the regex-parser library to efficiently process and analyze strings using regular expressions.

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