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Kenneth Reitz
264 lines
8.8 KiB
HTML
264 lines
8.8 KiB
HTML
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<title>Python + Regular Expressions</title>
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<a href=".">Kenneth's log </a>
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<article>
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<header> <h1 class="entry-title"><a href="python-regular-expressions.html"
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rel="bookmark" title="Permalink to Python + Regular Expressions">Python + Regular Expressions</a></h1> </header>
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<div class="entry-content">
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<footer class="post-info">
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<abbr class="published" title="2009-03-17T05:30:00">
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Tue 17 March 2009
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</abbr>
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<p>In <a href="./category/Code.html">Code</a>.
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</p>
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</footer><!-- /.post-info -->
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<p>Have you ever needed to parse through large amounts of text looking
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for a specific pattern? Patterns like “one capital letter followed
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by three numbers” or “dd/mm/yyyy”? This is known as Pattern
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Matching. Regular Expressions allow easy syntax for pattern
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matching, and is an invaluable skill to add to one’s toolkit, no
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matter what your area of expertise/practice is. Whether you’re
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writing a Compiler, Form Validator, Text Editor, Django Project, or
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Language Translator, Regular Expressions will always prove to be
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invaluable. Here is a very basic overview of some syntax: ‘\d’
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represents a digit. ‘\s’ represents whitespace. ‘.’ represents any
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character. If you have worked with Python for very long, you are
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probably already familiar with the concept. Take a look at the
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following code: print(“Rounded = %05d” % (42))</p>
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<p>This makes sure that the digit printed has 5 digits, and will
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automatically add 0’s to compensate. If you understand this
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concept, then you shouldn’t have a problem. Perl-style Regular
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Expressions are a very widely-accepted implementation, and Python
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has built in support for this mini-language! It’s easily
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accessible, so let’s get started. The included ‘re’ module will
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give us everything we need to get started: import re</p>
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<p>Lets give our new module a try! It will enable you to do anything
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you could ever want with regular expressions. Here’s a quick
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example of some basic use. import re</p>
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<pre class="literal-block">
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string0 = 'Kenneth Reitz is a cool guy!'
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regExp = r’kenneth[- ]?reitz’
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if re.match(regExp, string0, re.IGNORECASE):
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print “True”
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else:
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print “False”
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</pre>
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<p>This script takes the string ‘Kenneth Reitz is a cool guy’, and
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searches for ‘kenneth reitz’ inside of it. If ‘kenneth reitz’ is
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found within string0 (re.match compares the expression with the
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string), the script will print “True”, if not, it will print
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“False”. Additional parameters can be passed to the re.match
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function when needed. Note the ‘re.IGNORECASE’ flag used here –
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This tells the function be case-insensitive. Once you master the
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regular expression syntax, you’ll realize how truly powerful they
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can be. The options become limitless and the usefulness becomes
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undeniable. Here’s another example: import re</p>
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<pre class="literal-block">
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string0 = '10.03.1988'
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regExp = r'^\d\d[./]\d\d[./]\d\d\d\d?$'
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if re.match(regExp, string0):
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print 'True'
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else:
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print 'False/
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</pre>
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<p>When run, this script prints out “True”. If we were to change
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string0 to ‘10.03.88’, it would print “False”. Simple, isn’t it?
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Now, while a True/False return could be useful in certain
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applications (i.e. form validation), most of the time, we’re going
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to want to have a bit more information in order for our checks to
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be useful. We can tell Python to show us the data that matches our
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query. To do this, we’re going to have to break our expression up
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into different groups. In the date we have defined, there are three
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obvious groups we could separate this into: the day, month, and
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year. While defining a Regular Expression, you can use parentheses
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‘()’ to define groups: regExp = r’^()././$’</p>
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<p>This separates our expression into 3 separate groups. Python also
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supports turning a Regular Expression string into an
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heavily-supported object with the re.compile() function. Once you
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define a string as a Regular Expression object, you can use the
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built in methods to preform powerful parsing. Now we can ask python
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what is in those groups: import restring0 = ‘10.03.1988’ regExp =
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re.compile(‘^()././$’) regExpMatches = regExp.match(string0)</p>
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<pre class="literal-block">
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if re.match(regExp, string0):
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print(“Day: %s\nMonth: %s\nYear: %s” % (regExpMatches.group(1), \
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regExpMatches.group(2), regExpMatches.group(3)))
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else:
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print(“Invalid Date.”)
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</pre>
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<p>When executed, this script parses through our validated date,
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breaks it down into groups, and prints the following: > Day: 10 >
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Month: 03 > Year: 1988</p>
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<p>The possibilities are limitless! Here’s a quick run-down of the re
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module’s functions, strait from the Python documentation for
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reference: match: Match a regular expression pattern to the
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beginning of a string. search: Search a string for the presence of
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a pattern. sub: Substitute occurrences of a pattern found in a
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string subn: Same as sub, but also return the number of
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substitutions made. split: Split a string by the occurrences of a
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pattern. findall: Find all occurrences of a pattern in a string.
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compile: Compile a pattern into a RegexObject. purge: Clear the
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regular expression cache. escape: Backslash all non-alphanumerics
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in a string.</p>
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<p>Remember, you can always type help(re) (after importing the re
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module) into the Python interpret to take a quick look at the
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module’s built-in documentation. Good luck and happy coding!</p>
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© 2011 Kenneth Reitz & co. All Rights Reserved.
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