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A regular expression is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. A regular expression also known as regex is a sequence of characters that defines a search pattern. Popularly known as as regex or regexp; it is a sequence of characters that specifies a match pattern in text. Usually, such patterns are used by string-searching algorithms for "find" or "find and replace" operations on strings, or for input validation.

Large scale text processing in data science projects requires manipulation of textual data. The regular expressions processing is supported by many programming languages including Python. Python's standard library has 're' module for this purpose.

Since most of the functions defined in re module work with raw strings, let us first understand what the raw strings are.

Raw Strings

Regular expressions use the backslash character ('\') to indicate special forms or to allow special characters to be used without invoking their special meaning. Python on the other hand uses the same character as escape character. Hence Python uses the raw string notation.

A string become a raw string if it is prefixed with r or R before the quotation symbols. Hence 'Hello' is a normal string were are r'Hello' is a raw string.

>>> normal="Hello" >>> print (normal) Hello >>> raw=r"Hello" >>> print (raw) Hello

In normal circumstances, there is no difference between the two. However, when the escape character is embedded in the string, the normal string actually interprets the escape sequence, where as the raw string doesn't process the escape character.

>>> normal="Hello\nWorld" >>> print (normal) Hello World >>> raw=r"Hello\nWorld" >>> print (raw) Hello\nWorld

In the above example, when a normal string is printed the escape character '\n' is processed to introduce a newline. However because of the raw string operator 'r' the effect of escape character is not translated as per its meaning.

Metacharacters

Most letters and characters will simply match themselves. However, some characters are special metacharacters, and don't match themselves. Meta characters are characters having a special meaning, similar to * in wild card.

Here's a complete list of the metacharacters −

. ^ $ * + ? { } [ ] \ | ( )

The square bracket symbols[ and ] indicate a set of characters that you wish to match. Characters can be listed individually, or as a range of characters separating them by a '-'.

Sr.No. Metacharacters & Description
1

[abc]

match any of the characters a, b, or c
2

[a-c]

which uses a range to express the same set of characters.
3

[a-z]

match only lowercase letters.
4

[0-9]

match only digits.
5

'^'

complements the character set in [].[^5] will match any character except'5'.

'\'is an escaping metacharacter. When followed by various characters it forms various special sequences. If you need to match a [ or \, you can precede them with a backslash to remove their special meaning: \[ or \\.

Predefined sets of characters represented by such special sequences beginning with '\' are listed below −

Sr.No. Metacharacters & Description
1

\d

Matches any decimal digit; this is equivalent to the class [0-9].
2

\D

Matches any non-digit character; this is equivalent to the class [^0-9].
3 \sMatches any whitespace character; this is equivalent to the class [\t\n\r\f\v].
4

\S

Matches any non-whitespace character; this is equivalent to the class [^\t\n\r\f\v].
5

\w

Matches any alphanumeric character; this is equivalent to the class [a-zAZ0-9_].
6

\W

Matches any non-alphanumeric character. equivalent to the class [^a-zAZ0-9_].
7

.

Matches with any single character except newline '\n'.
8

?

match 0 or 1 occurrence of the pattern to its left
9

+

1 or more occurrences of the pattern to its left
10

*

0 or more occurrences of the pattern to its left
11

\b

boundary between word and non-word and /B is opposite of /b
12

[..]

Matches any single character in a square bracket and [^..] matches any single character not in square bracket.
13

\

It is used for special meaning characters like \. to match a period or \+ for plus sign.
14

{n,m}

Matches at least n and at most m occurrences of preceding
15

a| b

Matches either a or b

Python's re module provides useful functions for finding a match, searching for a pattern, and substitute a matched string with other string etc.

re.match() Function

This function attempts to match RE pattern at the start of string with optional flags.

Here is the syntax for this function −

re.match(pattern, string, flags=0)

Here is the description of the parameters −

Sr.No. Parameter & Description
1

pattern

This is the regular expression to be matched.

2

String

This is the string, which would be searched to match the pattern at the beginning of string.

3

Flags

You can specify different flags using bitwise OR (|). These are modifiers, which are listed in the table below.

The re.match function returns a match object on success, None on failure. A match object instance contains information about the match: where it starts and ends, the substring it matched, etc.

The match object's start() method returns the starting position of pattern in the string, and end() returns the endpoint.

If the pattern is not found, the match object is None.

We use group(num) or groups() function of match object to get matched expression.

Sr.No. Match Object Methods & Description
1 group(num=0)This method returns entire match (or specific subgroup num)
2 groups()This method returns all matching subgroups in a tuple (empty if there weren't any)

Example

 
import re line = "Cats are smarter than dogs" matchObj = re.match( r'Cats', line) print (matchObj.start(), matchObj.end()) print ("matchObj.group() : ", matchObj.group())

It will produce the following output −

0 4
matchObj.group() : Cats

re.search() Function

This function searches for first occurrence of RE pattern within the string, with optional flags.

Here is the syntax for this function −

re.search(pattern, string, flags=0)

Here is the description of the parameters −

Sr.No. Parameter & Description
1

Pattern

This is the regular expression to be matched.

2

String

This is the string, which would be searched to match the pattern anywhere in the string.

3

Flags

You can specify different flags using bitwise OR (|). These are modifiers, which are listed in the table below.

The re.search function returns a match object on success, none on failure. We use group(num) or groups() function of match object to get the matched expression.

Sr.No. Match Object Methods & Description
1 group(num=0)This method returns entire match (or specific subgroup num)
2 groups()This method returns all matching subgroups in a tuple (empty if there weren't any)

Example

 
import re line = "Cats are smarter than dogs" matchObj = re.search( r'than', line) print (matchObj.start(), matchObj.end()) print ("matchObj.group() : ", matchObj.group())

It will produce the following output −

17 21
matchObj.group() : than

Matching Vs Searching

Python offers two different primitive operations based on regular expressions :match checks for a match only at the beginning of the string, while search checks for a match anywhere in the string (this is what Perl does by default).

Example

 
import re line = "Cats are smarter than dogs"; matchObj = re.match( r'dogs', line, re.M|re.I) if matchObj: print ("match --> matchObj.group() : ", matchObj.group()) else: print ("No match!!") searchObj = re.search( r'dogs', line, re.M|re.I) if searchObj: print ("search --> searchObj.group() : ", searchObj.group()) else: print ("Nothing found!!")

When the above code is executed, it produces the following output −

No match!!
search --> matchObj.group() : dogs

re.findall() Function

The findall() function returns all non-overlapping matches of pattern in string, as a list of strings or tuples. The string is scanned left-to-right, and matches are returned in the order found. Empty matches are included in the result.

Syntax

re.findall(pattern, string, flags=0)

Parameters

Sr.No. Parameter & Description
1

Pattern

This is the regular expression to be matched.

2

String

This is the string, which would be searched to match the pattern anywhere in the string.

3

Flags

You can specify different flags using bitwise OR (|). These are modifiers, which are listed in the table below.

Example

 
import re string="Simple is better than complex." obj=re.findall(r"ple", string) print (obj)

It will produce the following output −

['ple', 'ple']

Following code obtains the list of words in a sentence with the help of findall() function.

 
import re string="Simple is better than complex." obj=re.findall(r"\w*", string) print (obj)

It will produce the following output −

['Simple', '', 'is', '', 'better', '', 'than', '', 'complex', '', '']

re.sub() Function

One of the most important re methods that use regular expressions is sub.

Syntax

re.sub(pattern, repl, string, max=0)

This method replaces all occurrences of the RE pattern in string with repl, substituting all occurrences unless max is provided. This method returns modified string.

Example

 
import re phone = "2004-959-559 # This is Phone Number" # Delete Python-style comments num = re.sub(r'#.*$', "", phone) print ("Phone Num : ", num) # Remove anything other than digits num = re.sub(r'\D', "", phone) print ("Phone Num : ", num)

It will produce the following output −

Phone Num : 2004-959-559
Phone Num : 2004959559

Example

The following example uses sub() function to substitute all occurrences of is with was word −

 
import re string="Simple is better than complex. Complex is better than complicated." obj=re.sub(r'is', r'was',string) print (obj)

It will produce the following output −

Simple was better than complex. Complex was better than complicated.

re.compile() Function

The compile() function compiles a regular expression pattern into a regular expression object, which can be used for matching using its match(), search() and other methods.

Syntax

re.compile(pattern, flags=0)

Flags

Sr.No. Modifier & Description
1

re.I

Performs case-insensitive matching.

2

re.L

Interprets words according to the current locale. This interpretation affects the alphabetic group (\w and \W), as well as word boundary behavior (\b and \B).

3

re.

M Makes $ match the end of a line (not just the end of the string) and makes ^ match the start of any line (not just the start of the string).

4

re.S

Makes a period (dot) match any character, including a newline.

5

re.U

Interprets letters according to the Unicode character set. This flag affects the behavior of \w, \W, \b, \B.

6

re.X

Permits "cuter" regular expression syntax. It ignores whitespace (except inside a set [] or when escaped by a backslash) and treats unescaped # as a comment marker.

The sequence −

prog = re.compile(pattern) result = prog.match(string)

is equivalent to −

result = re.match(pattern, string)

But using re.compile() and saving the resulting regular expression object for reuse is more efficient when the expression will be used several times in a single program.

Example

 
import re string="Simple is better than complex. Complex is better than complicated." pattern=re.compile(r'is') obj=pattern.match(string) obj=pattern.search(string) print (obj.start(), obj.end()) obj=pattern.findall(string) print (obj) obj=pattern.sub(r'was', string) print (obj)

It will produce the following output −

7 9
['is', 'is']
Simple was better than complex. Complex was better than complicated.

re.finditer() Function

This function returns an iterator yielding match objects over all non-overlapping matches for the RE pattern in string.

Syntax

re.finditer(pattern, string, flags=0)

Example

 
import re string="Simple is better than complex. Complex is better than complicated." pattern=re.compile(r'is') iterator = pattern.finditer(string) print (iterator ) for match in iterator: print(match.span())

It will produce the following output −

(7, 9)
(39, 41)

Use Cases of Python Regex

Finding all Adverbs

findall() matches all occurrences of a pattern, not just the first one as search() does. For example, if a writer wanted to find all of the adverbs in some text, they might use findall() in the following manner −

 
import re text = "He was carefully disguised but captured quickly by police." obj = re.findall(r"\w+ly\b", text) print (obj)

It will produce the following output −

['carefully', 'quickly']

Finding words starting with vowels

 
import re text = 'Errors should never pass silently. Unless explicitly silenced.' obj=re.findall(r'\b[aeiouAEIOU]\w+', text) print (obj)

It will produce the following output −

['Errors', 'Unless', 'explicitly']


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