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. 9.12. Extract CSV Fields from a Specific Column

    Problem

    You want to extract every field (record item) from the third column of a CSV file.

    Solution

    The regular expressions from Recipe 9.11 can be reused here to iterate over each field in a CSV subject string. With a bit of extra code, you can count the number of fields from left to right in each row, or record, and extract the fields at the position you’re interested in.

    The following regular expression (shown with and without the free-spacing option) matches a single CSV field and its preceding delimiter in two separate capturing groups. Since line breaks can appear within double-quoted fields, it would not be accurate to simply search from the beginning of each line in your CSV string. By matching and stepping past fields one by one, you can easily determine which line breaks appear outside of double-quoted fields and therefore start a new record.

    Tip

    The regular expressions in this recipe are designed to work correctly with valid CSV files only, according to the format rules discussed in Comma-Separated Values (CSV).

    (,|\r?\n|^)([^",\r\n]+|"(?:[^"]|"")*")?
    Regex options: None
    Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby
    ( , | \r?\n | ^ )   # Capture the leading field delimiter to backref 1
(                   # Capture a single field to backref 2:
  [^",\r\n]+        #   Unquoted field
|                   #  Or:
  " (?:[^"]|"")* "  #   Quoted field (may contain escaped double quotes)
)?                  # The group is optional because fields may be empty
    Regex options: Free-spacing
    Regex flavors: .NET, Java, XRegExp, PCRE, Perl, Python, Ruby

    These regular expressions are exactly the same as in Recipe 9.11, and they can be repurposed for plenty of other CSV processing tasks as well. The following example code demonstrates how you can use the version without the free-spacing option to help you extract a CSV column.

    Example web page with JavaScript

    The following code is a complete web page that includes two multiline text input fields and a button between them labeled Extract Column 3. Clicking the button takes whatever string you put into the Input text box, extracts the value of the third field in each record with the help of the regular expression just shown, then puts the entire column (with each value separated by a line break) into the Output field. To test it, save this code into a file with the .html extension and open it in your favorite web browser:

    <html>
<head>
<title>Extract the third column from a CSV string</title>
</head>

<body>
<p>Input:</p>
<textarea id="input" rows="5" cols="75"></textarea>

<p><input type="button" value="Extract Column 3"
    onclick="displayCsvColumn(2)"></p>

<p>Output:</p>
<textarea id="output" rows="5" cols="75"></textarea>

<script>
function displayCsvColumn(index) {
    var input = document.getElementById("input"),
        output = document.getElementById("output"),
        columnFields = getCsvColumn(input.value, index);

    if (columnFields.length > 0) {
        // Show each record on its own line, separated by a line feed (\n)
        output.value = columnFields.join("\n");
    } else {
        output.value = "[No data found to extract]";
    }
}

// Return an array of CSV fields at the provided, zero-based index
function getCsvColumn(csv, index) {
    var regex = /(,|\r?\n|^)([^",\r\n]+|"(?:[^"]|"")*")?/g,
        result = [],
        columnIndex = 0,
        match;

    while (match = regex.exec(csv)) {
        // Check the value of backreference 1. If it's a comma,
        // increment columnIndex. Otherwise, reset it to zero.
        if (match[1] == ",") {
            columnIndex++;
        } else {
            columnIndex = 0;
        }
        if (columnIndex == index) {
            // Add the field (backref 2) at the end of the result array
            result.push(match[2]);
        }

        // If there is an empty match, prevent some browsers from getting
        // stuck in an infinite loop
        if (match.index == regex.lastIndex) {
            regex.lastIndex++;
        }
    }

    return result;
}
</script>
</body>
</html>

Discussion

Since the regular expressions here are repurposed from Recipe 9.11, we won’t repeat the detailed explanation of how they work. However, this recipe includes new JavaScript example code that uses the regex to extract fields at a specific index from each record in the CSV subject string.

In the provided code, the getCsvColumn() function works by iterating over the subject string one match at a time. After each match, backreference 1 is examined to check whether it contains a comma. If so, you’ve matched something other than the first field in a row, so the columnIndex variable is incremented to keep track of which column you’re at. If backreference 1 is anything other than a comma (i.e., an empty string or a line break), you’ve matched the first field in a new row and columnIndex is reset to zero.

The next step in the code is to check whether the columnIndex counter has reached the index you’re looking to extract. Every time it does, the value of backreference 2 (everything after the leading delimiter) is pushed to the result array. After you’ve iterated over the entire subject string, the getCsvColumn() function returns an array containing values for the entire specified column (in this example, the third column). The list of matches is then dumped into the second text box on the page, with each value separated by a line feed character (\n).

A simple improvement would be to let the user specify which column index should be extracted, via a prompt or additional text field. The getCsvColumn() function we’ve been discussing is already written with this feature in mind, and lets you specify the desired column as an integer (counting from zero) via its second parameter (index).

Variations

Although using code to iterate over a string one CSV field at a time allows for extra flexibility, if you’re using a text editor to get the job done, you may be limited to just search-and-replace. In this situation, you can achieve a similar result by matching each complete record and replacing it with the value of the field at the column index you’re searching for (using a backreference). The following regexes illustrate this technique for particular column indexes, replacing each record with the field in a specific column.

With all of these regexes, if any record does not contain at least as many fields as the column index you’re searching for, that record will not be matched and will be left in place.

Match a CSV record and capture the field in column 1 to backreference 1

^([^",\r\n]+|"(?:[^"]|"")*")?(?:,(?:[^",\r\n]+|"(?:[^"]|"")*")?)*
Regex options: ^ and $ match at line breaks
Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby

Match a CSV record and capture the field in column 2 to backreference 1

^(?:[^",\r\n]+|"(?:[^"]|"")*")?,([^",\r\n]+|"(?:[^"]|"")*")?↵
(?:,(?:[^",\r\n]+|"(?:[^"]|"")*")?)*
Regex options: ^ and $ match at line breaks
Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby

Match a CSV record and capture the field in column 3 or higher to backreference 1

^(?:[^",\r\n]+|"(?:[^"]|"")*")?(?:,(?:[^",\r\n]+|"(?:[^"]|"")*")?){1},↵
([^",\r\n]+|"(?:[^"]|"")*")?(?:,(?:[^",\r\n]+|"(?:[^"]|"")*")?)*
Regex options: ^ and $ match at line breaks
Regex flavors: .NET, Java, JavaScript, PCRE, Perl, Python, Ruby

Increment the number within the ‹{1}› quantifier to make this last regex work for anything higher than column 3. For example, change it to ‹{2}› to capture fields from column 4, ‹{3}› for column 5, and so on. If you’re working with column 3, you can simply remove the ‹{1}› if you prefer, since it has no effect here.

Replacement string

The same replacement string (backreference 1) is used with all of these regexes. Replacing each match with backreference 1 should leave you with just the fields you’re searching for.

$1
Replacement text flavors: .NET, Java, JavaScript, Perl, PHP
\1
Replacement text flavors: Python, Ruby

See Also

Recipe 9.11 shows how to use the regex in this recipe to change the delimiters in a CSV file from commas to tabs.

Techniques used in the regular expressions and replacement text in this recipe are discussed in Chapter 2. Recipe 2.2 explains how to match nonprinting characters. Recipe 2.3 explains character classes. Recipe 2.5 explains anchors. Recipe 2.8 explains alternation. Recipe 2.9 explains grouping. Recipe 2.12 explains repetition. Recipe 2.21 explains how to insert text matched by capturing groups into the replacement text.