Pattern Matching with Regular Expressions - Part 1

Introduction

Regular expressions are huge time-savers, not just for software users but also for programmers. In fact, tech writer Cory Doctorow argues that even before teaching programming, we should be teaching regular expressions:

“Knowing [regular expressions] can mean the difference between solving a problem in 3 steps and solving it in 3,000 steps. When you’re a nerd, you forget that the problems you solve with a couple keystrokes can take other people days of tedious, error-prone work to slog through.”

Finding Patterns of Text Without Regular Expressions

Let’s use a function named isPhoneNumber() to check whether a string matches this pattern, returning either True or False. Open a new file editor window and enter the following code; then save the file as isPhoneNumber.py:

   def isPhoneNumber(text):
➊     if len(text) != 12:
           return False
       for i in range(0, 3):
➋         if not text[i].isdecimal():
               return False
➌     if text[3] != '-':
           return False
       for i in range(4, 7):
➍         if not text[i].isdecimal():
               return False
➎     if text[7] != '-':
           return False
       for i in range(8, 12):
➏         if not text[i].isdecimal():
               return False
➐     return True

   print('415-555-4242 is a phone number:')
   print(isPhoneNumber('415-555-4242'))
   print('Moshi moshi is a phone number:')
   print(isPhoneNumber('Moshi moshi'))

While the string in message is short in this example, it could be millions of characters long and the program would still run in less than a second. A similar program that finds phone numbers using regular expressions would also run in less than a second, but regular expressions make it quicker to write these programs.

Finding Patterns of Text with Regular Expressions

The previous phone number–finding program works, but it uses a lot of code to do something limited: The isPhoneNumber() function is 17 lines but can find only one pattern of phone numbers. What about a phone number formatted like 415.555.4242 or (415) 555-4242? What if the phone number had an extension, like 415-555-4242 x99? The isPhoneNumber() function would fail to validate them. You could add yet more code for these additional patterns, but there is an easier way.

Regular expressions, called regexes for short, are descriptions for a pattern of text. For example, a \d in a regex stands for a digit character—that is, any single numeral 0 to 9. The regex \d\d\d-\d\d\d-\d\d\d\d is used by Python to match the same text the previous isPhoneNumber() function did: a string of three numbers, a hyphen, three more numbers, another hyphen, and four numbers. Any other string would not match the \d\d\d-\d\d\d-\d\d \d\d regex.

But regular expressions can be much more sophisticated. For example, adding a 3 in curly brackets ({3}) after a pattern is like saying, “Match this pattern three times.” So the slightly shorter regex \d{3}-\d{3}-\d{4} also matches the correct phone number format.

Creating Regex Objects

All the regex functions in Python are in the re module. Enter the following into the interactive shell to import this module:

import re

Passing a string value representing your regular expression to re.compile() returns a Regex pattern object (or simply, a Regex object).

To create a Regex object that matches the phone number pattern, enter the following into the interactive shell. (Remember that \d means “a digit character” and \d\d\d-\d\d\d-\d\d\d\d is the regular expression for the correct phone number pattern.)

phoneNumRegex = re.compile(r'\d\d\d-\d\d\d-\d\d\d\d')
# raw strings

Matching Regex Objects

A Regex object’s search() method searches the string it is passed for any matches to the regex. The search() method will return None if the regex pattern is not found in the string. If the pattern is found, the search() method returns a Match object. Match objects have a group() method that will return the actual matched text from the searched string. (I’ll explain groups shortly.) For example, enter the following into the interactive shell:

>>> phoneNumRegex = re.compile(r'\d\d\d-\d\d\d-\d\d\d\d')
>>> mo = phoneNumRegex.search('My number is 415-555-4242.')
>>> print('Phone number found: ' + mo.group())
Phone number found: 415-555-4242

The mo variable name is just a generic name to use for Match objects. This example might seem complicated at first, but it is much shorter than the earlier isPhoneNumber.py program and does the same thing.

Here, we pass our desired pattern to re.compile() and store the resulting Regex object in phoneNumRegex. Then we call search() on phoneNumRegex and pass search() the string we want to search for a match. The result of the search gets stored in the variable mo. In this example, we know that our pattern will be found in the string, so we know that a Match object will be returned. Knowing that mo contains a Match object and not the null value None, we can call group() on mo to return the match. Writing mo.group() inside our print statement displays the whole match, 415-555-4242.

Review of Regular Expression Matching

While there are several steps to using regular expressions in Python, each step is fairly simple.

1. Import the regex module with import re.

2. Create a Regex object with the re.compile() function. (Remember to use a raw string.)

3. Pass the string you want to search into the Regex object’s search() method. This returns a Match object.

4. Call the Match object’s group() method to return a string of the actual matched text.

More Pattern Matching with Regular Expressions

Now that you know the basic steps for creating and finding regular expression objects with Python, you’re ready to try some of their more powerful pattern-matching capabilities.

Grouping with Parentheses

Say you want to separate the area code from the rest of the phone number. Adding parentheses will create groups in the regex: (\d\d\d)-(\d\d\d-\d\d\d\d). Then you can use the group() match object method to grab the matching text from just one group.

The first set of parentheses in a regex string will be group 1. The second set will be group 2. By passing the integer 1 or 2 to the group() match object method, you can grab different parts of the matched text. Passing 0 or nothing to the group() method will return the entire matched text. Enter the following into the interactive shell:

>>> phoneNumRegex = re.compile(r'(\d\d\d)-(\d\d\d-\d\d\d\d)')
>>> mo = phoneNumRegex.search('My number is 415-555-4242.')
>>> mo.group(1)
'415'
>>> mo.group(2)
'555-4242'
>>> mo.group(0)
'415-555-4242'
>>> mo.group()
'415-555-4242'

If you would like to retrieve all the groups at once, use the groups() method—note the plural form for the name.

>>> mo.groups()
('415', '555-4242')
>>> areaCode, mainNumber = mo.groups()
>>> print(areaCode)
415
>>> print(mainNumber)
555-4242

Since mo.groups() returns a tuple of multiple values, you can use the multiple-assignment trick to assign each value to a separate variable, as in the previous areaCode, mainNumber = mo.groups() line.

Parentheses have a special meaning in regular expressions, but what do you do if you need to match a parenthesis in your text? For instance, maybe the phone numbers you are trying to match have the area code set in parentheses. In this case, you need to escape the ( and ) characters with a backslash. Enter the following into the interactive shell:

>>> phoneNumRegex = re.compile(r'(\(\d\d\d\)) (\d\d\d-\d\d\d\d)')
>>> mo = phoneNumRegex.search('My phone number is (415) 555-4242.')
>>> mo.group(1)
'(415)'
>>> mo.group(2)
'555-4242'

The ( and ) escape characters in the raw string passed to re.compile() will match actual parenthesis characters.

Matching Multiple Groups with the Pipe

The | character is called a pipe. You can use it anywhere you want to match one of many expressions. For example, the regular expression r'Batman|Tina Fey' will match either 'Batman' or 'Tina Fey'.

When both Batman and Tina Fey occur in the searched string, the first occurrence of matching text will be returned as the Match object. Enter the following into the interactive shell:

heroRegex = re.compile (r'Batman|Tina Fey')
mo1 = heroRegex.search('Batman and Tina Fey.')
mo1.group()
'Batman'
mo2 = heroRegex.search('Tina Fey and Batman.')
mo2.group()
'Tina Fey'

Matching one of serveral patterns

>>> batRegex = re.compile(r'Bat(man|mobile|copter|bat)')
>>> mo = batRegex.search('Batmobile lost a wheel')
>>> mo.group()
'Batmobile'
>>> mo.group(1)
'mobile'

The method call mo.group() returns the full matched text 'Batmobile', while mo.group(1) returns just the part of the matched text inside the first parentheses group, 'mobile'. By using the pipe character and grouping parentheses, you can specify several alternative patterns you would like your regex to match.

If you need to match an actual pipe character, escape it with a backslash, like |.

---

Optional Matching with the Question Mark

Sometimes there is a pattern that you want to match only optionally. That is, the regex should find a match whether or not that bit of text is there. The ? character flags the group that precedes it as an optional part of the pattern. For example, enter the following into the interactive shell:

>>> batRegex = re.compile(r'Bat(wo)?man')
>>> mo1 = batRegex.search('The Adventures of Batman')
>>> mo1.group()
'Batman'

>>> mo2 = batRegex.search('The Adventures of Batwoman')
>>> mo2.group()
'Batwoman'

The (wo)? part of the regular expression means that the pattern wo is an optional group. The regex will match text that has zero instances or one instance of wo in it. This is why the regex matches both 'Batwoman' and 'Batman'.

Using the earlier phone number example, you can make the regex look for phone numbers that do or do not have an area code. Enter the following into the interactive shell:

>>> phoneRegex = re.compile(r'(\d\d\d-)?\d\d\d-\d\d\d\d')
>>> mo1 = phoneRegex.search('My number is 415-555-4242')
>>> mo1.group()
'415-555-4242'

>>> mo2 = phoneRegex.search('My number is 555-4242')
>>> mo2.group()
'555-4242'

You can think of the ? as saying, “Match zero or one of the group preceding this question mark.”

If you need to match an actual question mark character, escape it with ?.

---

Matching Zero or More with the Star

The * (called the star or asterisk) means “match zero or more”—the group that precedes the star can occur any number of times in the text. It can be completely absent or repeated over and over again. Let’s look at the Batman example again.

>>> batRegex = re.compile(r'Bat(wo)*man')
>>> mo1 = batRegex.search('The Adventures of Batman')
>>> mo1.group()
'Batman'

>>> mo2 = batRegex.search('The Adventures of Batwoman')
>>> mo2.group()
'Batwoman'

>>> mo3 = batRegex.search('The Adventures of Batwowowowoman')
>>> mo3.group()
'Batwowowowoman'

For 'Batman', the (wo)* part of the regex matches zero instances of wo in the string; for 'Batwoman', the (wo)* matches one instance of wo; and for 'Batwowowowoman', (wo)* matches four instances of wo.

If you need to match an actual star character, prefix the star in the regular expression with a backslash, *.

Matching One or More with the Plus

While * means “match zero or more,” the + (or plus) means “match one or more.” Unlike the star, which does not require its group to appear in the matched string, the group preceding a plus must appear at least once. It is not optional. Enter the following into the interactive shell, and compare it with the star regexes in the previous section:

>>> batRegex = re.compile(r'Bat(wo)+man')
>>> mo1 = batRegex.search('The Adventures of Batwoman')
>>> mo1.group()
'Batwoman'

>>> mo2 = batRegex.search('The Adventures of Batwowowowoman')
>>> mo2.group()
'Batwowowowoman'

>>> mo3 = batRegex.search('The Adventures of Batman')
>>> mo3 == None
True

The regex Bat(wo)+man will not match the string 'The Adventures of Batman' because at least one wo is required by the plus sign.

If you need to match an actual plus sign character, prefix the plus sign with a backslash to escape it: +.

---

Matching Specific Repetitions with Curly Brackets

If you have a group that you want to repeat a specific number of times, follow the group in your regex with a number in curly brackets. For example, the regex (Ha){3} will match the string 'HaHaHa', but it will not match 'HaHa', since the latter has only two repeats of the (Ha) group.

Instead of one number, you can specify a range by writing a minimum, a comma, and a maximum in between the curly brackets. For example, the regex (Ha){3,5} will match 'HaHaHa', 'HaHaHaHa', and 'HaHaHaHaHa'.

You can also leave out the first or second number in the curly brackets to leave the minimum or maximum unbounded. For example, (Ha){3,} will match three or more instances of the (Ha) group, while (Ha){,5} will match zero to five instances. Curly brackets can help make your regular expressions shorter. These two regular expressions match identical patterns:

(Ha){3}
(Ha)(Ha)(Ha)

And these two regular expressions also match identical patterns:

(Ha){3,5}
((Ha)(Ha)(Ha))|((Ha)(Ha)(Ha)(Ha))|((Ha)(Ha)(Ha)(Ha)(Ha))

Enter the following into the interactive shell:

>>> haRegex = re.compile(r'(Ha){3}')
>>> mo1 = haRegex.search('HaHaHa')
>>> mo1.group()
'HaHaHa'

>>> mo2 = haRegex.search('Ha')
>>> mo2 == None
True

Here, (Ha){3} matches 'HaHaHa' but not 'Ha'. Since it doesn’t match 'Ha', search() returns None.