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. 9.5. Convert Plain Text to HTML by Adding <p> and <br> Tags

    Problem

    Given a plain text string, such as a multiline value submitted via a form, you want to convert it to an HTML fragment to display within a web page. Paragraphs, separated by two line breaks in a row, should be surrounded with <p>⋯</p>. Additional line breaks should be replaced with <br> tags.

    Solution

    This problem can be solved in four simple steps. In most programming languages, only the middle two steps benefit from regular expressions.

    Step 1: Replace HTML special characters with named character references

    As we’re converting plain text to HTML, the first step is to convert the three special HTML characters &, <, and > to named character references (see Table 9-3). Otherwise, the resulting markup could lead to unintended results when displayed in a web browser.

    Table 9-3. HTML special character substitutions

    Search for

    Replace with

    ‹&›

    «&amp;»

    ‹<›

    «&lt;»

    ‹>›

    «&gt;»

Ampersands (&) must be replaced first, since you’ll be adding more ampersands to the subject string as part of the named character references.

Step 2: Replace all line breaks with <br>

Search for:

\r\n?|\n
Regex options: None
Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby
\R
Regex options: None
Regex flavors: PCRE 7, Perl 5.10

Replace with:

<br>
Replacement text flavors: .NET, Java, JavaScript, Perl, PHP, Python, Ruby

Step 3: Replace double <br> tags with </p><p>

Search for:

<br>\s*<br>
Regex options: None
Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby

Replace with:

</p><p>
Replacement text flavors: .NET, Java, JavaScript, Perl, PHP, Python, Ruby

Step 4: Wrap the entire string with <p>⋯</p>

This step is a simple string concatenation, and doesn’t require regular expressions.

Example JavaScript solution

Tying all four steps together, we’ll create a JavaScript function called htmlFromPlainText(). This function accepts a string, processes it using the steps we’ve just described, then returns the new HTML string:

function htmlFromPlainText(subject) {
    // Step 1 (plain text searches)
    subject = subject.replace(/&/g, "&amp;").
                      replace(/</g, "&lt;").
                      replace(/>/g, "&gt;");

    // Step 2
    subject = subject.replace(/\r\n?|\n/g, "<br>");

    // Step 3
    subject = subject.replace(/<br>\s*<br>/g, "</p><p>");

    // Step 4
    subject = "<p>" + subject + "</p>";

    return subject;
}

// Run some tests...
htmlFromPlainText("Test.");            // -> "<p>Test.</p>"
htmlFromPlainText("Test.\n");          // -> "<p>Test.<br></p>"
htmlFromPlainText("Test.\n\n");        // -> "<p>Test.</p><p></p>"
htmlFromPlainText("Test1.\nTest2.");   // -> "<p>Test1.<br>Test2.</p>"
htmlFromPlainText("Test1.\n\nTest2."); // -> "<p>Test1.</p><p>Test2.</p>"
htmlFromPlainText("< AT&T >");         // -> "<p>&lt; AT&amp;T &gt;</p>"

Several examples are included at the end of the code snippet that show the output when this function is applied to various subject strings. If JavaScript is foreign to you, note that the /g modifier appended to each of the regex literals causes the replace() method to replace all occurrences of the pattern, rather than just the first. The \n metasequence in the example subject strings inserts a line feed character (ASCII position 0x0A) in a JavaScript string literal.

Discussion

Step 1: Replace HTML special characters with named character references

The easiest way to complete this step is to use three discrete search-and-replace operations (see Table 9-3, shown earlier, for the list of replacements). JavaScript always uses regular expressions for global search-and-replace operations, but in other programming languages you will typically get better performance from simple plain-text substitutions.

Step 2: Replace all line breaks with <br>

In this step, we use the regular expression ‹\r\n?|\n› to find line breaks that follow the Windows/MS-DOS (CRLF), Unix/Linux/BSD/OS X (LF), and legacy Mac OS (CR) conventions. Perl 5.10 and PCRE 7 users can use the dedicated ‹\R› token (note the uppercase R) instead for matching those and other line break sequences.

Replacing all line breaks with <br> before adding paragraph tags in the next step keeps things simpler overall. It also makes it easy to add whitespace between your </p><p> tags in later substitutions, if you want to keep your HTML code readable.

If you prefer to use XHTML-style singleton tags, use «<br●/>» instead of «<br>» as your replacement string. You’ll also need to alter the regular expression in Step 3 to match this change.

Step 3: Replace double <br> tags with </p><p>

Two line breaks in a row indicate the end of one paragraph and the start of another, so our replacement text for this step is a closing </p> tag followed by an opening <p>. If the subject text contains only one paragraph (i.e., two line breaks never appear in a row), no substitutions will be made. Step 2 already replaced any of several line break types (leaving behind only <br> tags), so this step could be handled with a plain text substitution. However, using a regex here makes it easy to take things one step further and ignore whitespace that appears between line breaks. Any extra space characters won’t be rendered in an HTML document anyway.

If you’re generating XHTML and therefore replaced line breaks with «<br●/>» instead of «<br>», you’ll need to adjust the regex for this step to ‹<br●/>\s*<br●/>›.

Step 4: Wrap the entire string with <p>⋯</p>

Step 3 merely added markup between paragraphs. Now you need to add a <p> tag at the very beginning of the subject string, and a closing </p> at the very end. That completes the process, whether there were 1 or 100 paragraphs in the text.

See Also

Recipe 4.10 includes more information about Perl and PCRE’s ‹\R› token, and shows how to manually match the additional, esoteric line separators that are supported by ‹\R›.

Recipe 9.6 demonstrates how to decode XML-style named and numbered character references.

Techniques used in the regular expressions in this recipe are discussed in Chapter 2. Recipe 2.2 explains how to match nonprinting characters. Recipe 2.3 explains character classes. Recipe 2.8 explains alternation. Recipe 2.12 explains repetition.