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. 2.11. Capture and Name Parts of the Match

    Problem

    Create a regular expression that matches any date in yyyy-mm-dd format and separately captures the year, month, and day. The goal is to make it easy to work with these separate values in the code that processes the match. Contribute to this goal by assigning the descriptive names “year,” “month,” and “day” to the captured text.

    Create another regular expression that matches “magical” dates in yyyy-mm-dd format. A date is magical if the year minus the century, the month, and the day of the month are all the same numbers. For example, 2008-08-08 is a magical date. Capture the magical number (08 in the example), and label it “magic.”

    You can assume all dates in the subject text to be valid. The regular expressions don’t have to exclude things like 9999-99-99, because these won’t occur in the subject text.

    Solution

    Named capture

    \b(?<year>\d\d\d\d)-(?<month>\d\d)-(?<day>\d\d)\b
    Regex options: None
    Regex flavors: .NET, Java 7, XRegExp, PCRE 7, Perl 5.10, Ruby 1.9
    \b(?'year'\d\d\d\d)-(?'month'\d\d)-(?'day'\d\d)\b
    Regex options: None
    Regex flavors: .NET, PCRE 7, Perl 5.10, Ruby 1.9
    \b(?P<year>\d\d\d\d)-(?P<month>\d\d)-(?P<day>\d\d)\b
    Regex options: None
    Regex flavors: PCRE 4 and later, Perl 5.10, Python

Named backreferences

\b\d\d(?<magic>\d\d)-\k<magic>-\k<magic>\b
Regex options: None
Regex flavors: .NET, Java 7, XRegExp, PCRE 7, Perl 5.10, Ruby 1.9
\b\d\d(?'magic'\d\d)-\k'magic'-\k'magic'\b
Regex options: None
Regex flavors: .NET, PCRE 7, Perl 5.10, Ruby 1.9
\b\d\d(?P<magic>\d\d)-(?P=magic)-(?P=magic)\b
Regex options: None
Regex flavors: PCRE 4 and later, Perl 5.10, Python

Discussion

Named capture

Recipes 2.9 and 2.10 illustrate capturing groups and backreferences. To be more precise: these recipes use numbered capturing groups and numbered backreferences. Each group automatically gets a number, which you use for the backreference.

Modern regex flavors support named capturing groups in addition to numbered groups. The only difference between named and numbered groups is your ability to assign a descriptive name, instead of being stuck with automatic numbers. Named groups make your regular expression more readable and easier to maintain. Inserting a capturing group into an existing regex can change the numbers assigned to all the capturing groups. Names that you assign remain the same.

Python was the first regular expression flavor to support named capture. It uses the syntax (?P<name>regex). The name must consist of word characters matched by \w. (?P<name> is the group’s opening bracket, and ) is the closing bracket.

The designers of the .NET Regex class came up with their own syntax for named capture, using two interchangeable variants. (?<name>regex) mimics Python’s syntax, minus the P. The name must consist of word characters matched by \w. (?<name> is the group’s opening bracket, and ) is the closing bracket.

The angle brackets in the named capture syntax are annoying when you’re coding in XML, or writing this book in DocBook XML. That’s the reason for .NET’s alternate named capture syntax: (?'name'regex). The angle brackets are replaced with single quotes. Choose whichever syntax is easier for you to type. Their functionality is identical.

Perhaps due to .NET’s popularity over Python, the .NET syntax seems to be the one that other regex library developers prefer to copy. Perl 5.10 and later have it, and so does the Oniguruma engine in Ruby 1.9. Perl 5.10 and Ruby 1.9 support both the syntax using angle brackets and single quotes. Java 7 also copied the .NET syntax, but only the variant using angle brackets. Standard JavaScript does not support named capture. XRegExp adds support for named capture using the .NET syntax, but only the variant with angle brackets.

PCRE copied Python’s syntax long ago, at a time when Perl did not support named capture at all. PCRE 7, the version that adds the new features in Perl 5.10, supports both the .NET syntax and the Python syntax. Perhaps as a testament to the success of PCRE, in a reverse compatibility move, Perl 5.10 also supports the Python syntax. In PCRE and Perl 5.10, the functionality of the .NET syntax and the Python syntax for named capture is identical.

Choose the syntax that is most useful to you. If you’re coding in PHP and you want your code to work with older versions of PHP that incorporate older versions of PCRE, use the Python syntax. If you don’t need compatibility with older versions and you also work with .NET or Ruby, the .NET syntax makes it easier to copy and paste between all these languages. If you’re unsure, use the Python syntax for PHP/PCRE. People recompiling your code with an older version of PCRE are going to be unhappy if the regexes in your code suddenly stop working. When copying a regex to .NET or Ruby, deleting a few Ps is easy enough.

Documentation for PCRE 7 and Perl 5.10 barely mention the Python syntax, but it is by no means deprecated. For PCRE and PHP, we actually recommend it.

Named backreferences

With named capture comes named backreferences. Just as named capturing groups are functionally identical to numbered capturing groups, named backreferences are functionally identical to numbered backreferences. They’re just easier to read and maintain.

Python uses the syntax (?P=name) to create a backreference to the group name. Although this syntax uses parentheses, the backreference is not a group. You cannot put anything between the name and the closing parenthesis. A backreference (?P=name) is a singular regex token, just like \1. PCRE and Perl 5.10 also support the Python syntax for named backreferences.

.NET uses the syntax \k<name> and \k'name'. The two variants are identical in functionality, and you can freely mix them. A named group created with the bracket syntax can be referenced with the quote syntax, and vice versa. Perl 5.10, PCRE 7, and Ruby 1.9 also support the .NET syntax for named backreferences. Java 7 and XRegExp support only the variant using angle brackets.

We strongly recommend you don’t mix named and numbered groups in the same regex. Different flavors follow different rules for numbering unnamed groups that appear between named groups. Perl 5.10, Ruby 1.9, Java 7, and XRegExp copied .NET’s syntax, but they do not follow .NET’s way of numbering named capturing groups or of mixing numbered capturing groups with named groups. Instead of trying to explain the differences, we simply recommend not mixing named and numbered groups. Avoid the confusion and either give all unnamed groups a name or make them noncapturing.

Groups with the same name

Perl 5.10, Ruby 1.9, and .NET allow multiple named capturing groups to share the same name. We take advantage of this in the solutions for recipes 4.5, 8.7, and 8.19. When a regular expression uses alternation to find different variations of certain text, using capturing groups with the same name makes it easy to extract parts from the match, regardless of which alternative actually matched the text. The section Pure regular expression in Recipe 4.5 uses alternation to separately match dates in months of different lengths. Each alternative matches the day and the month. By using the same group names “day” and “month” in all the alternatives, we only need to query two capturing groups to retrieve the day and the month after the regular expression finds a match.

All the other flavors in this book that support named capture treat multiple groups with the same name as an error.

Caution

Using multiple capturing groups with the same name only works reliably when only one of the groups participates in the match. That is the case in all the recipes in this book that use capturing groups with the same name. The groups are in separate alternatives, and the alternatives are not inside a group that is repeated. Perl 5.10, Ruby 1.9, and .NET do allow two groups with the same name to participate in the match. But then the behavior of backreferences and the text retained for the group after the match will differ significantly between these flavors. It is confusing enough for us to recommend to use groups with the same name only when they’re in separate alternatives in the regular expression.

See Also

Recipe 2.9 on numbered capturing groups has more fundamental information on how grouping works in regular expressions.

Recipe 2.10 explains how to make a regex match the same text that was matched by a named capturing group.

Recipe 2.11 explains named capturing groups. Naming the groups in your regex makes the regex easier to read and maintain.

Recipe 2.21 explains how to make the replacement text reinsert text matched by a capturing group when doing a search-and-replace.

Recipe 3.9 explains how to retrieve the text matched by a capturing group in procedural code.

Recipe 2.15 explains how to make sure the regex engine doesn’t needlessly try different ways of matching a group.

Many of the recipes in the later chapters use named capture to make it easier to retrieve parts of the text that was matched. Recipes 4.5, 8.7, and Recipe 8.19 show some of the more interesting solutions.