Python advanced 2. regular expression in python
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This document provides an overview of regular expressions in Python. It discusses how regular expressions can be used to search, match, replace, and split strings. The syntax for common regular expression patterns is explained, including character classes, grouping, quantifiers, anchors, and more. Examples are given showing how to use the re module to compile patterns, search and match strings, and extract matched groups. Regular expressions in Python provide a powerful tool for manipulating text data.
![Regular Expression Python Syntax
• regular match:
Example: the regular expression “test” only
matches the string ‘test’
• [x] matches any one of a list of characters
Example: “*abc+” matches ‘a’,‘b’,or ‘c’
• [^x] matches any one character that is not
included in x
“*^abc+” matches any single character except
‘a’,’b’,or ‘c’](https://image.slidesharecdn.com/pythonadvanced2-131221115012-phpapp02/85/Python-advanced-2-regular-expression-in-python-3-320.jpg)
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Python advanced 2. regular expression in python
- 1. PYTHON REGULAR EXPRESSIONS John Zhang Tuesday, December 11, 2012
- 2. Regular Expressions • Regular expressions are a powerful string manipulation tool • All modern languages have similar library packages for regular expressions • Use regular expressions to: – Search a string (search and match) – Replace parts of a string (sub) – Break stings into smaller pieces (split)
- 3. Regular Expression Python Syntax • regular match: Example: the regular expression “test” only matches the string ‘test’ • [x] matches any one of a list of characters Example: “*abc+” matches ‘a’,‘b’,or ‘c’ • [^x] matches any one character that is not included in x “*^abc+” matches any single character except ‘a’,’b’,or ‘c’
- 4. Regular Expressions Syntax • “.” matches any single character • Parentheses can be used for grouping by () Example: “(abc)+” matches ’abc’, ‘abcabc’, ‘abcabcabc’, etc. • x|y matches x or y Example: “this|that” matches ‘this’ and ‘that’, but not ‘thisthat’.
- 5. Regular Expression Syntax • x* matches zero or more x’s “a*” matches ’’, ’a’, ’aa’, etc. • x+ matches one or more x’s “a+” matches ’a’,’aa’,’aaa’, etc. • x? matches zero or one x’s “a?” matches ’’ or ’a’ . • x{m, n} matches i x‘s, where m<i< n “a,2,3-” matches ’aa’ or ’aaa’
- 6. Regular Expression Syntax • “d” matches any digit; “D” matches any non-digit • “s” matches any whitespace character; “S” matches any non-whitespace character • “w” matches any alphanumeric character; “W” matches any non-alphanumeric character • “^” matches the beginning of the string; “$” matches the end of the string • “b” matches a word boundary; “B” matches position that is not a word boundary
- 7. Search and Match • The two basic functions are re.search and re.match – Search looks for a pattern anywhere in a string – Match looks for a match staring at the beginning • Both return None if the pattern is not found (logical false) and a “match object” if it is pat = "a*b" import re matchObj = re.search(pat,"fooaaabcde") if matchObj: print “match successfully at %s” % matchObj.group(0)
- 8. Q: What’s a match object? • A: an instance of the match class with the details of the match result pat = "a*b" >>> r1 = re.search(pat,"fooaaabcde") >>> r1.group() # group returns string matched 'aaab' >>> r1.start() # index of the match start 3 >>> r1.end() # index of the match end 7 >>> r1.span() # tuple of (start, end) (3, 7)
- 9. What got matched? • Here’s a pattern to match simple email addresses w+@(w+.)+(com|org|net|edu) >>> pat1 = "w+@(w+.)+(com|org|net|edu)" >>> r1 = re.match(pat1,“[email protected]") >>> r1.group() '[email protected]’ • We might want to extract the pattern parts, like the email name and host
- 10. What got matched? • We can put parentheses around groups we want to be able to reference >>> pat2 = "(w+)@((w+.)+(com|org|net|edu))" >>> r2 = re.match(pat2,"[email protected]") >>> r2.group(1) ‘qzhang' >>> r2.group(2) ‘pku.cn.edu' >>> r2.groups() r2.groups() (‘qzhang', ' pku.cn.edu ', ‘cn.', 'edu’) • Note that the ‘groups’ are numbered in a preorder traversal of the forest
- 11. What got matched? • We can ‘label’ the groups as well… >>> pat3 ="(?P<name>w+)@(?P<host>(w+.)+(com|org|net|edu))" >>> r3 = re.match(pat3,"[email protected]") >>> r3.group('name') ‘qzhang' >>> r3.group('host') ‘pku.cn.edu’ • And reference the matching parts by the labels
- 12. More re functions • re.split() is like split but can use patterns >>> re.split("W+", “This... is a test, short and sweet, of split().”) *'This', 'is', 'a', 'test', 'short’, 'and', 'sweet', 'of', 'split’, ‘’+ • re.sub substitutes one string for a pattern >>> re.sub('(blue|white|red)', 'black', 'blue socks and red shoes') 'black socks and black shoes’ • re.findall() finds al matches >>> re.findall("d+”,"12 dogs,11 cats, 1 egg") *'12', '11', ’1’+
- 13. Compiling regular expressions • If you plan to use a re pattern more than once, compile it to a re object • Python produces a special data structure that speeds up matching >>> capt3 = re.compile(pat3) >>> cpat3 <_sre.SRE_Pattern object at 0x2d9c0> >>> r3 = cpat3.search("[email protected]") >>> r3 <_sre.SRE_Match object at 0x895a0> >>> r3.group() '[email protected]'
- 14. Pattern object methods • There are methods defined for a pattern object that parallel the regular expression functions, e.g., – match – search – split – findall – sub