In this lesson you will learn the syntax of regular expressions and how you can utilize them to match and search text data!

Introduction to Regular Expressions

In 1951, mathematician Stephen Cole Kleene developed a system to match patterns in written language with mathematical notation. This notation is now known as regular expressions!

In his honor, the next piece of regular expressions syntax we will learn is known as the Kleene star. The **_Kleene star_**, denoted with the asterisk `*`, is also a quantifier, and matches the preceding character `0` or more times. This means that the character doesn't need to appear, can appear once, or can appear many many times.

The regex `meo*w` will match the characters `me`, followed by `0` or more `o`s, followed by a `w`. Thus the regex will match `mew`, `meow`, `meooow`, and `meoooooooooooow`.

Another useful quantifier is the **_Kleene plus_**, denoted by the plus `+`, which matches the preceding character `1` or more times. 

The regex `meo+w` will match the characters `me`, followed by `1` or more `o`s, followed by a `w`. Thus the regex will match `meow`, `meooow`, and `meoooooooooooow`, but not match  `mew`.

Like all the other metacharacters, in order to match the symbols `*` and `+`, you need to use the escape character in your regex. The regex `My cat is a \*` will completely match the text `My cat is a *`.

Quantifiers - 0 or More, 1 or More

Do you feel those regular expression superpowers coursing through your body? Do you just want to scream `ah+` really loud? Awesome! You are now ready to take these skills and use them out in the wild. Before beginning your adventures, let's review what we've learned.
* _Regular expressions_ are special sequences of characters that describe a pattern of text that is to be matched
* We can use _literals_ to match the exact characters that we desire
* _Alternation_, using the pipe symbol `|`, allows us to match the text preceding or following the `|`
* _Character sets_, denoted by a pair of brackets `[]`, let us match one character from a series of characters
* _Wildcards_, represented by the period or dot `.`, will match any single character (letter, number, symbol or whitespace)
* _Ranges_ allow us to specify a range of characters in which we can make a match
* _Shorthand character classes_ like `\w`, `\d` and `\s` represent the ranges representing word characters, digit characters, and whitespace characters, respectively
* _Groupings_, denoted with parentheses `()`, group parts of a regular expression together, and allows us to limit alternation to part of a regex
* _Fixed quantifiers_, represented with curly braces `{}`, let us indicate the exact quantity or a range of quantity of a character we wish to match
* _Optional quantifiers_, indicated by the question mark `?`, allow us to indicate a character in a regex is optional, or can appear either `0` times or `1` time
* The _Kleene star_, denoted with the asterisk `*`, is a quantifier that matches the preceding character `0` or more times
* The _Kleene plus_, denoted by the plus `+`, matches the preceding character `1` or more times
* The _anchor_ symbols hat `^` and dollar sign `$` are used to match text at the start and end of a string, respectively

Review

The simplest text we can match with regular expressions are **_literals_**. This is where our regular expression contains the exact text that we want to match. The regex `a`, for example, will match the text `a`, and the regex `bananas` will match the text `bananas`.

We can additionally match just part of a piece of text. Perhaps we are searching a document to see if the word `monkey` occurs, since we love monkeys. We could use the regex `monkey` to match `monkey` in the piece of text `The monkeys like to eat bananas.`.

Not only are we able to match alphabetical characters — digits work as well! The regex `3` will match the `3` in the piece of text `34`, and the regex `5 gibbons` will completely match the text `5 gibbons`!

Regular expressions operate by moving character by character, from left to right, through a piece of text. When the regular expression finds a character that matches the first piece of the expression, it looks to find a continuous sequence of matching characters.

Literals

You are working on a research project that summarizes the findings of primate behavioral scientists from around the world. Of particular interest to you are the scientists' observations of humor in chimpanzees, so you whip up some regex to find all occurrences of the word `humor` in the documents you have collected. To your dismay, your regex misses the observations of amusement written by scientists hailing from British English speaking countries, where the spelling of the word is `humour`. Optional quantifiers to the rescue!

**_Optional quantifiers_**, indicated by the question mark `?`, allow us to indicate a character in a regex is optional, or can appear either `0` times or `1` time. For example, the regex `humou?r` matches the characters `humo`, then either `0` occurrences or `1` occurrence of the letter `u`, and finally the letter `r`. Note the `?` _only_ applies to the character directly before it.

With all quantifiers, we can take advantage of grouping to make even more advanced regexes. The regex `The monkey ate a (rotten )?banana` will completely match both `The monkey ate a rotten banana` and `The monkey ate a banana`.

Since the `?` is a metacharacter, you need to use the escape character in your regex in order to match a question mark `?` in a piece of text. The regex `Aren't owl monkeys beautiful\?` will thus completely match the text `Aren't owl monkeys beautiful?`.

Quantifiers - Optional

Character sets are great, but their true power isn't realized without ranges. **_Ranges_** allow us to specify a range of characters in which we can make a match without having to type out each individual character. The regex `[abc]`, which would match any character `a`, `b`, _or_ `c`, is equivalent to regex range `[a-c]`. The `-` character allows us to specify that we are interested in matching a range of characters.

The regex `I adopted [2-9] [b-h]ats` will match the text `I adopted 4 bats` as well as `I adopted 8 cats` and even `I adopted 5 hats`.

With ranges we can match any single capital letter with the regex `[A-Z]`, lowercase letter with the regex `[a-z]`, any digit with the regex `[0-9]`. We can even have multiple ranges in the same character set! To match any single capital _or_ lowercase alphabetical character, we can use the regex `[A-Za-z]`. 

Remember, within any character set `[]` we only match _one_ character.

Ranges

Do you love baboons and gorillas? You can find either of them with the same regular expression using **_alternation!_** Alternation, performed in regular expressions with the pipe symbol, `|`, allows us to match either the characters preceding the `|` OR the characters after the `|`. The regex `baboons|gorillas` will match `baboons` in the text `I love baboons`, but will also match `gorillas` in the text `I love gorillas`.

Are you thinking about how to match the whole piece of text `I love baboons` or `I love gorillas`? We will get to that later on!

Alternation

While character ranges are extremely useful, they can be cumbersome to write out every single time you want to match common ranges such as those that designate alphabetical characters or digits. To alleviate this pain, there are **_shorthand character classes_** that represent common ranges, and they make writing regular expressions much simpler. These shorthand classes include:
* `\w`: the "word character" class represents the regex range `[A-Za-z0-9_]`, and it matches a single uppercase character, lowercase character, digit or underscore
* `\d`: the "digit character" class represents the regex range `[0-9]`, and it matches a single digit character
* `\s`: the "whitespace character" class represents the regex range `[ \t\r\n\f\v]`, matching a single space, tab, carriage return, line break, form feed, or vertical tab

For example, the regex `\d\s\w\w\w\w\w\w\w` matches a digit character, followed by a whitespace character, followed by 7 word characters. Thus the regex completely matches the text `3 monkeys`.

In addition to the shorthand character classes `\w`, `\d`, and `\s`, we also have access to the _negated shorthand character classes_! These shorthands will match any character that is NOT in the regular shorthand classes. These negated shorthand classes include:
* `\W`: the "non-word character" class represents the regex range `[^A-Za-z0-9_]`, matching any character that is not included in the range represented by `\w`
* `\D`: the "non-digit character" class represents the regex range `[^0-9]`, matching any character that is not included in the range represented by `\d`
* `\S`:  the "non-whitespace character" class represents the regex range `[^ \t\r\n\f\v]`, matching any character that is not included in the range represented by `\s`

Shorthand Character Classes

Spelling tests may seem like a distant memory from grade school, but we ultimately take them every day while typing. It's easy to make mistakes on commonly misspelled words like `consensus`, and on top of that, there are sometimes alternate spellings for the same word. 

**_Character sets_**, denoted by a pair of brackets `[]`, let us match one character from a series of characters, allowing for matches with incorrect or different spellings.

The regex `con[sc]en[sc]us` will match `consensus`, the correct spelling of the word, but also match the following three incorrect spellings: `concensus`, `consencus`, and `concencus`. The letters inside the first brackets, `s` and `c`, are the different possibilities for the character that comes after `con` and before `en`. Similarly for the second brackets, `s` and `c` are the different character possibilities to come after `en` and before `us`.

Thus the regex `[cat]` will match the characters `c`, `a`, _or_ `t`, but not the text `cat`. 

The beauty of character sets (and alternation) is that they allow our regular expressions to become more flexible and less rigid than by just matching with literals!

We can make our character sets even more powerful with the help of the caret `^` symbol. Placed at the front of a character set, the `^` negates the set, matching any character that is _not_ stated. These are called _negated character sets_. Thus the regex `[^cat]` will match any character that is not `c`, `a`, _or_ `t`, and would completely match each character `d`, `o` _or_ `g`.

Do we have a consensus that regular expressions are pretty cool?

Character Sets

When registering an account for a new social media app or completing an order for a gift online, nearly every piece of information you enter into a web form is validated. Did you enter a properly formatted email including an `@` symbol? Did you enter a phone number `10` digits long, with or without `-`s and parentheses? And then there's the king of them all — did your new password meet the seemingly growing number of requirements for inclusion (and exclusion) of symbols, digits, and both upper and lower case letters?

While correcting each field in our digital lives for proper format can be a pain, it's integral to ensuring that our accounts are secure, our packages are successfully delivered, and that we can be contacted by phone and email.

The technology that fuels this verification system on nearly every website and application is the ever reliable, often quirky language of **_regular expressions_**, commonly shortened to regex, as we will use here, or regexp (<a href="https://english.stackexchange.com/questions/94371/what-is-the-correct-pronunciation-of-regex" target="_blank" rel="noopener noreferrer">pronunciation is up for debate</a>). A _regular expression_ is a special sequence of characters that describe a pattern of text that should be found, or matched, in a string or document. By matching text, we can identify how often and where certain pieces of text occur, as well as have the opportunity to replace or update these pieces of text if needed.

Regular Expressions have a variety of use cases including:
* validating user input in HTML forms
* verifying and parsing text in files, code and applications
* examining test results
* finding keywords in emails and web pages

While there are [a variety of implementations of Regular Expressions across platforms](https://en.wikipedia.org/wiki/Regular_expression#History), in this lesson you will learn the basics that apply everywhere. By the lesson's end, you'll be empowered to use them in your own projects (<a href="https://xkcd.com/208/" target="_blank" rel="noopener noreferrer">and become a regex superhero</a>)!


Humorous XKCD comic about regular expressions.

Introduction

Remember when we were in love with baboons and gorillas a few exercises ago? We were able to match either `baboons` or `gorillas` using the regex `baboons|gorillas`, taking advantage of the `|` symbol.

But what if we want to match the whole piece of text `I love baboons` and `I love gorillas` with the same regex? Your first guess might be to use the regex `I love baboons|gorillas`. This regex, while it would completely match the string `I love baboons`, would not match `I love gorillas`, and would instead match `gorillas`. This is because the `|` symbol matches the _entire_ expression before or after itself.

Grouping to the rescue! **_Grouping_**, denoted with the open parenthesis `(` and the closing parenthesis `)`, lets us group parts of a regular expression together, and allows us to limit alternation to part of the regex.

The regex `I love (baboons|gorillas)` will match the text `I love ` and _then_ match either `baboons` or `gorillas`, as the grouping limits the reach of the `|` to the text within the parentheses.

These groups are also called _capture groups_, as they have the power to select, or capture, a substring from our matched text.

Grouping

When writing regular expressions, it's useful to make the expression as specific as possible in order to ensure that we do not match unintended text. To aid in this mission of specificity, we can use the anchor metacharacters. The **_anchors_** hat `^` and dollar sign `$` are used to match text at the start and the end of a string, respectively.

The regex `^Monkeys: my mortal enemy$` will completely match the text `Monkeys: my mortal enemy` but not match `Spider Monkeys: my mortal enemy in the wild` or `Squirrel Monkeys: my mortal enemy in the wild`. The `^` ensures that the matched text begins with `Monkeys`, and the `$` ensures the matched text ends with `enemy`.

Without the anchor tags, the regex `Monkeys: my mortal enemy` will match the text `Monkeys: my mortal enemy` in both `Spider Monkeys: my mortal enemy in the wild` and `Squirrel Monkeys: my mortal enemy in the wild`.

Once again, as with all other metacharacters, in order to match the symbols `^` and `$`, you need to use the escape character in your regex. The regex `My spider monkey has \$10\^6 in the bank` will completely match the text `My spider monkey has $10^6 in the bank`.


Anchors

Sometimes we don't care exactly WHAT characters are in a text, just that there are SOME characters. Enter the wildcard `.`! **_Wildcards_** will match any single character (letter, number, symbol or whitespace) in a piece of text. They are useful when we do not care about the specific value of a character, but only that a character exists!

Let's say we want to match any 9-character piece of text. The regex `.........` will completely match `orangutan` and `marsupial`! Similarly, the regex `I ate . bananas` will completely match both `I ate 3 bananas` and `I ate 8 bananas`!

What happens if we want to match an actual period, `.`? We can use the escape character, `\`, to escape the wildcard functionality of the `.` and match an actual period. The regex `Howler monkeys are really lazy\.` will completely match the text `Howler monkeys are really lazy.`.

Wild for Wildcards

Here's where things start to get really interesting. So far we have only matched text on a character by character basis. But instead of writing the regex `\w\w\w\w\w\w\s\w\w\w\w\w\w`, which would match 6 word characters, followed by a whitespace character, and then followed by more 6 word characters, such as in the text `rhesus monkey`, is there a better way to denote the quantity of characters we want to match?

The answer is yes, with the help of quantifiers! **_Fixed quantifiers_**, denoted with curly braces `{}`, let us indicate the exact quantity of a character we wish to match, or allow us to provide a quantity range to match on.
* `\w{3}` will match _exactly_ 3 word characters
* `\w{4,7}` will match _at minimum_ 4 word characters and _at maximum_ 7 word characters

The regex `roa{3}r` will match the characters `ro` followed by `3` `a`s, and then the character `r`, such as in the text `roaaar`. The regex `roa{3,7}r` will match the characters `ro` followed by _at least_ `3` `a`s and _at most_ `7` `a`s, followed by an `r`, matching the strings `roaaar`, `roaaaaar` and `roaaaaaaar`.

An important note is that quantifiers are considered to be _greedy_. This means that they will match the greatest quantity of characters they possibly can. For example, the regex `mo{2,4}` will match the text `moooo` in the string `moooo`, and not return a match of `moo`, or `mooo`. This is because the fixed quantifier wants to match the largest number of `o`s as possible, which is `4` in the string `moooo`.