Table of Contents for
Regular Expressions Cookbook, 2nd Edition

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Regular Expressions Cookbook, 2nd Edition by Steven Levithan Published by O'Reilly Media, Inc., 2012
  1. Cover
  2. Regular Expressions Cookbook
  3. Preface
  4. Caught in the Snarls of Different Versions
  5. Intended Audience
  6. Technology Covered
  7. Organization of This Book
  8. Conventions Used in This Book
  9. Using Code Examples
  10. Safari® Books Online
  11. How to Contact Us
  12. Acknowledgments
  13. 1. Introduction to Regular Expressions
  14. Regular Expressions Defined
  15. Search and Replace with Regular Expressions
  16. Tools for Working with Regular Expressions
  17. 2. Basic Regular Expression Skills
  18. 2.1. Match Literal Text
  19. 2.2. Match Nonprintable Characters
  20. 2.3. Match One of Many Characters
  21. 2.4. Match Any Character
  22. 2.5. Match Something at the Start and/or the End of a Line
  23. 2.6. Match Whole Words
  24. 2.7. Unicode Code Points, Categories, Blocks, and Scripts
  25. 2.8. Match One of Several Alternatives
  26. 2.9. Group and Capture Parts of the Match
  27. 2.10. Match Previously Matched Text Again
  28. 2.11. Capture and Name Parts of the Match
  29. 2.12. Repeat Part of the Regex a Certain Number of Times
  30. 2.13. Choose Minimal or Maximal Repetition
  31. 2.14. Eliminate Needless Backtracking
  32. 2.15. Prevent Runaway Repetition
  33. 2.16. Test for a Match Without Adding It to the Overall Match
  34. 2.17. Match One of Two Alternatives Based on a Condition
  35. 2.18. Add Comments to a Regular Expression
  36. 2.19. Insert Literal Text into the Replacement Text
  37. 2.20. Insert the Regex Match into the Replacement Text
  38. 2.21. Insert Part of the Regex Match into the Replacement Text
  39. 2.22. Insert Match Context into the Replacement Text
  40. 3. Programming with Regular Expressions
  41. Programming Languages and Regex Flavors
  42. 3.1. Literal Regular Expressions in Source Code
  43. 3.2. Import the Regular Expression Library
  44. 3.3. Create Regular Expression Objects
  45. 3.4. Set Regular Expression Options
  46. 3.5. Test If a Match Can Be Found Within a Subject String
  47. 3.6. Test Whether a Regex Matches the Subject String Entirely
  48. 3.7. Retrieve the Matched Text
  49. 3.8. Determine the Position and Length of the Match
  50. 3.9. Retrieve Part of the Matched Text
  51. 3.10. Retrieve a List of All Matches
  52. 3.11. Iterate over All Matches
  53. 3.12. Validate Matches in Procedural Code
  54. 3.13. Find a Match Within Another Match
  55. 3.14. Replace All Matches
  56. 3.15. Replace Matches Reusing Parts of the Match
  57. 3.16. Replace Matches with Replacements Generated in Code
  58. 3.17. Replace All Matches Within the Matches of Another Regex
  59. 3.18. Replace All Matches Between the Matches of Another Regex
  60. 3.19. Split a String
  61. 3.20. Split a String, Keeping the Regex Matches
  62. 3.21. Search Line by Line
  63. Construct a Parser
  64. 4. Validation and Formatting
  65. 4.1. Validate Email Addresses
  66. 4.2. Validate and Format North American Phone Numbers
  67. 4.3. Validate International Phone Numbers
  68. 4.4. Validate Traditional Date Formats
  69. 4.5. Validate Traditional Date Formats, Excluding Invalid Dates
  70. 4.6. Validate Traditional Time Formats
  71. 4.7. Validate ISO 8601 Dates and Times
  72. 4.8. Limit Input to Alphanumeric Characters
  73. 4.9. Limit the Length of Text
  74. 4.10. Limit the Number of Lines in Text
  75. 4.11. Validate Affirmative Responses
  76. 4.12. Validate Social Security Numbers
  77. 4.13. Validate ISBNs
  78. 4.14. Validate ZIP Codes
  79. 4.15. Validate Canadian Postal Codes
  80. 4.16. Validate U.K. Postcodes
  81. 4.17. Find Addresses with Post Office Boxes
  82. 4.18. Reformat Names From “FirstName LastName” to “LastName, FirstName”
  83. 4.19. Validate Password Complexity
  84. 4.20. Validate Credit Card Numbers
  85. 4.21. European VAT Numbers
  86. 5. Words, Lines, and Special Characters
  87. 5.1. Find a Specific Word
  88. 5.2. Find Any of Multiple Words
  89. 5.3. Find Similar Words
  90. 5.4. Find All Except a Specific Word
  91. 5.5. Find Any Word Not Followed by a Specific Word
  92. 5.6. Find Any Word Not Preceded by a Specific Word
  93. 5.7. Find Words Near Each Other
  94. 5.8. Find Repeated Words
  95. 5.9. Remove Duplicate Lines
  96. 5.10. Match Complete Lines That Contain a Word
  97. 5.11. Match Complete Lines That Do Not Contain a Word
  98. 5.12. Trim Leading and Trailing Whitespace
  99. 5.13. Replace Repeated Whitespace with a Single Space
  100. 5.14. Escape Regular Expression Metacharacters
  101. 6. Numbers
  102. 6.1. Integer Numbers
  103. 6.2. Hexadecimal Numbers
  104. 6.3. Binary Numbers
  105. 6.4. Octal Numbers
  106. 6.5. Decimal Numbers
  107. 6.6. Strip Leading Zeros
  108. 6.7. Numbers Within a Certain Range
  109. 6.8. Hexadecimal Numbers Within a Certain Range
  110. 6.9. Integer Numbers with Separators
  111. 6.10. Floating-Point Numbers
  112. 6.11. Numbers with Thousand Separators
  113. 6.12. Add Thousand Separators to Numbers
  114. 6.13. Roman Numerals
  115. 7. Source Code and Log Files
  116. Keywords
  117. Identifiers
  118. Numeric Constants
  119. Operators
  120. Single-Line Comments
  121. Multiline Comments
  122. All Comments
  123. Strings
  124. Strings with Escapes
  125. Regex Literals
  126. Here Documents
  127. Common Log Format
  128. Combined Log Format
  129. Broken Links Reported in Web Logs
  130. 8. URLs, Paths, and Internet Addresses
  131. 8.1. Validating URLs
  132. 8.2. Finding URLs Within Full Text
  133. 8.3. Finding Quoted URLs in Full Text
  134. 8.4. Finding URLs with Parentheses in Full Text
  135. 8.5. Turn URLs into Links
  136. 8.6. Validating URNs
  137. 8.7. Validating Generic URLs
  138. 8.8. Extracting the Scheme from a URL
  139. 8.9. Extracting the User from a URL
  140. 8.10. Extracting the Host from a URL
  141. 8.11. Extracting the Port from a URL
  142. 8.12. Extracting the Path from a URL
  143. 8.13. Extracting the Query from a URL
  144. 8.14. Extracting the Fragment from a URL
  145. 8.15. Validating Domain Names
  146. 8.16. Matching IPv4 Addresses
  147. 8.17. Matching IPv6 Addresses
  148. 8.18. Validate Windows Paths
  149. 8.19. Split Windows Paths into Their Parts
  150. 8.20. Extract the Drive Letter from a Windows Path
  151. 8.21. Extract the Server and Share from a UNC Path
  152. 8.22. Extract the Folder from a Windows Path
  153. 8.23. Extract the Filename from a Windows Path
  154. 8.24. Extract the File Extension from a Windows Path
  155. 8.25. Strip Invalid Characters from Filenames
  156. 9. Markup and Data Formats
  157. Processing Markup and Data Formats with Regular Expressions
  158. 9.1. Find XML-Style Tags
  159. 9.2. Replace Tags with
  160. 9.3. Remove All XML-Style Tags Except and
  161. 9.4. Match XML Names
  162. 9.5. Convert Plain Text to HTML by Adding

    and
    Tags

  163. 9.6. Decode XML Entities
  164. 9.7. Find a Specific Attribute in XML-Style Tags
  165. 9.8. Add a cellspacing Attribute to Tags That Do Not Already Include It
  166. 9.9. Remove XML-Style Comments
  167. 9.10. Find Words Within XML-Style Comments
  168. 9.11. Change the Delimiter Used in CSV Files
  169. 9.12. Extract CSV Fields from a Specific Column
  170. 9.13. Match INI Section Headers
  171. 9.14. Match INI Section Blocks
  172. 9.15. Match INI Name-Value Pairs
  173. Index
  174. Index
  175. Index
  176. Index
  177. Index
  178. Index
  179. Index
  180. Index
  181. Index
  182. Index
  183. Index
  184. Index
  185. Index
  186. Index
  187. Index
  188. Index
  189. Index
  190. Index
  191. Index
  192. Index
  193. Index
  194. Index
  195. Index
  196. Index
  197. Index
  198. Index
  199. About the Authors
  200. Colophon
  201. Copyright
  202. 3.13. Find a Match Within Another Match

    Problem

    You want to find all the matches of a particular regular expression, but only within certain sections of the subject string. Another regular expression matches each of the sections in the string.

    Suppose you have an HTML file in which various passages are marked as bold with <b> tags. You want to find all numbers marked as bold. If some bold text contains multiple numbers, you want to match all of them separately. For example, when processing the string 1 <b>2</b> 3 4 <b>5 6 7</b>, you want to find four matches: 2, 5, 6, and 7.

    Solution

    C#

    StringCollection resultList = new StringCollection();
    Regex outerRegex = new Regex("<b>(.*?)</b>", RegexOptions.Singleline);
    Regex innerRegex = new Regex(@"\d+");
    // Find the first section
    Match outerMatch = outerRegex.Match(subjectString);
    while (outerMatch.Success) {
        // Get the matches within the section
    	Match innerMatch = innerRegex.Match(outerMatch.Groups[1].Value);
    	while (innerMatch.Success) {
    		resultList.Add(innerMatch.Value);
    		innerMatch = innerMatch.NextMatch();
    	}
    	// Find the next section
        outerMatch = outerMatch.NextMatch();
    }

    VB.NET

    Dim ResultList = New StringCollection
    Dim OuterRegex As New Regex("<b>(.*?)</b>", RegexOptions.Singleline)
    Dim InnerRegex As New Regex("\d+")
    'Find the first section
    Dim OuterMatch = OuterRegex.Match(SubjectString)
    While OuterMatch.Success
        'Get the matches within the section
        Dim InnerMatch = InnerRegex.Match(OuterMatch.Groups(1).Value)
        While InnerMatch.Success
            ResultList.Add(InnerMatch.Value)
            InnerMatch = InnerMatch.NextMatch
        End While
        OuterMatch = OuterMatch.NextMatch
    End While

    Java

    Iterating using two matchers is easy, and works with Java 4 and later:

    List<String> resultList = new ArrayList<String>();
    Pattern outerRegex = Pattern.compile("<b>(.*?)</b>", Pattern.DOTALL);
    Pattern innerRegex = Pattern.compile("\\d+");
    Matcher outerMatcher = outerRegex.matcher(subjectString);
    while (outerMatcher.find()) {
        Matcher innerMatcher = innerRegex.matcher(outerMatcher.group(1));
        while (innerMatcher.find()) {
            resultList.add(innerMatcher.group());
        }
    }

    The following code is more efficient (because innerMatcher is created only once), but requires Java 5 or later:

    List<String> resultList = new ArrayList<String>();
    Pattern outerRegex = Pattern.compile("<b>(.*?)</b>", Pattern.DOTALL);
    Pattern innerRegex = Pattern.compile("\\d+");
    Matcher outerMatcher = outerRegex.matcher(subjectString);
    Matcher innerMatcher = innerRegex.matcher(subjectString);
    while (outerMatcher.find()) {
        innerMatcher.region(outerMatcher.start(1), outerMatcher.end(1));
        while (innerMatcher.find()) {
            resultList.add(innerMatcher.group());
        }
    }

    JavaScript

    var result = [];
    var outerRegex = /<b>([\s\S]*?)<\/b>/g;
    var innerRegex = /\d+/g;
    var outerMatch;
    var innerMatches;
    while (outerMatch = outerRegex.exec(subject)) {
        if (outerMatch.index == outerRegex.lastIndex)
            outerRegex.lastIndex++;
        innerMatches = outerMatch[1].match(innerRegex);
        if (innerMatches) {
            result = result.concat(innerMatches);
        }
    }

    XRegExp

    XRegExp has a matchChain() method that is specifically designed to get the matches of one regex within the matches of another regex:

    var result = XRegExp.matchChain(subject, [
        {regex: XRegExp("<b>(.*?)</b>", "s"), backref: 1},
        /\d+/
    ]);

    Alternatively, you can use XRegExp.forEach() for a solution similar to the standard JavaScript solution:

    var result = [];
    var outerRegex = XRegExp("<b>(.*?)</b>", "s");
    var innerRegex = /\d+/g;
    XRegExp.forEach(subject, outerRegex, function(outerMatch) {
        var innerMatches = outerMatch[1].match(innerRegex);
        if (innerMatches) {
            result = result.concat(innerMatches);
        }
    });

    PHP

    $list = array();
    preg_match_all('%<b>(.*?)</b>%s', $subject, $outermatches,
                   PREG_PATTERN_ORDER);
    for ($i = 0; $i < count($outermatches[0]); $i++) {
        if (preg_match_all('/\d+/', $outermatches[1][$i], $innermatches,
                           PREG_PATTERN_ORDER)) {
            $list = array_merge($list, $innermatches[0]);
        }
    }

    Perl

    while ($subject =~ m!<b>(.*?)</b>!gs) {
        push(@list, ($1 =~ m/\d+/g));
    }

    This only works if the inner regular expression (\d+, in this example) doesn’t have any capturing groups, so use noncapturing groups instead. See Recipe 2.9 for details.

    Python

    list = []
    innerre = re.compile(r"\d+")
    for outermatch in re.finditer("(?s)<b>(.*?)</b>", subject):
        list.extend(innerre.findall(outermatch.group(1)))

    Ruby

    list = []
    subject.scan(/<b>(.*?)<\/b>/m) {|outergroups|
        list += outergroups[1].scan(/\d+/)
    }

    Discussion

    Regular expressions are well suited for tokenizing input, but they are not well suited for parsing input. Tokenizing means to identify different parts of a string, such as numbers, words, symbols, tags, comments, etc. It involves scanning the text from left to right, trying different alternatives and quantities of characters to be matched. Regular expressions handle this very well.

    Parsing means to process the relationship between those tokens. For example, in a programming language, combinations of such tokens form statements, functions, classes, namespaces, etc. Keeping track of the meaning of the tokens within the larger context of the input is best left to procedural code. In particular, regular expressions cannot keep track of nonlinear context, such as nested constructs.[6]

    Trying to find one kind of token within another kind of token is a task that people commonly try to tackle with regular expressions. A pair of HTML bold tags is easily matched with the regular expression <b>(.*?)</b>.[7] A number is even more easily matched with the regex \d+. But if you try to combine these into a single regex, you’ll end up with something rather different:

    \d+(?=(?:(?!<b>).)*</b>)
    Regex options: None
    Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby

    Though the regular expression just shown is a solution to the problem posed by this recipe, it is hardly intuitive. Even a regular expression expert will have to carefully scrutinize the regex to determine what it does, or perhaps resort to a tool to highlight the matches. And this is the combination of just two simple regexes.

    A better solution is to keep the two regular expressions as they are and use procedural code to combine them. The resulting code, while a bit longer, is much easier to understand and maintain, and creating simple code is the reason for using regular expressions in the first place. A regex such as <b>(.*?)</b> is easy to understand by anyone with a modicum of regex experience, and quickly does what would otherwise take many more lines of code that are harder to maintain.

    Though the solutions for this recipe are some of the most complex ones in this chapter, they’re very straightforward. Two regular expressions are used. The “outer” regular expression matches the HTML bold tags and the text between them, and the text in between is captured by the first capturing group. This regular expression is implemented with the same code shown in Recipe 3.11. The only difference is that the placeholder comment saying where to use the match has been replaced with code that lets the “inner” regular expression do its job.

    The second regular expression matches a digit. This regex is implemented with the same code as shown in Recipe 3.10. The only difference is that instead of processing the subject string entirely, the second regex is applied only to the part of the subject string matched by the first capturing group of the outer regular expression.

    There are two ways to restrict the inner regular expressions to the text matched by (a capturing group of) the outer regular expressions. Some languages provide a function that allows the regular expression to be applied to part of a string. That can save an extra string copy if the match function doesn’t automatically fill a structure with the text matched by the capturing groups. We can always simply retrieve the substring matched by the capturing group and apply the inner regex to that.

    Either way, using two regular expressions together in a loop will be faster than using the one regular expression with its nested lookahead groups. The latter requires the regex engine to do a whole lot of backtracking. On large files, using just one regex will be much slower, as it needs to determine the section boundaries (HTML bold tags) for each number in the subject string, including numbers that are not between <b> tags. The solution that uses two regular expressions doesn’t even begin to look for numbers until it has found the section boundaries, which it does in linear time.

    The XRegExp library for JavaScript has a special matchChain() method that is specifically designed to get the matches of one regex within the matches of another regex. This method takes an array of regexes as its second parameter. You can add as many regexes to the array as you want. You can find the matches of a regex within the matches of another regex, within the matches of other regexes, as many levels deep as you want. This recipe only uses two regexes, so our array only needs two elements. If you want the next regex to search within the text matched by a particular capturing group of a regex, add that regex as an object to the array. The object should have a regex property with the regular expression, and a backref property with the name or number of the capturing group. If you specify the last regex in the array as an object with a regex and a backref property, then the returned array will contain the matches of that capturing group in the final regex.

See Also

This recipe uses techniques introduced by three earlier recipes. Recipe 3.8 shows code to determine the position and length of the match. Recipe 3.10 shows code to get a list of all the matches a regex can find in a string. Recipe 3.11 shows code to iterate over all the matches a regex can find in a string.



[6] A few modern regex flavors have tried to introduce features for balanced or recursive matching. These features result in such complex regular expessions, however, that they only end up proving our point that parsing is best left to procedural code.

[7] To allow the tag to span multiple lines, turn on “dot matches line breaks” mode. For JavaScript, use <b>([\s\S]*?)</b>.