In this blog, you will get a logical understanding of what is RegEx, what it can do, and what it can’t do, and also you will get a piece of knowledge about when to use them and — more importantly — when not to.
So Let’s start.
On an abstract level a regular expression, regex for short, is a shorthand representation for a set of strings that holds a specific pattern.
In the terms of research when a data scientist comes across a text processing problem whether it is searching for titles in paragraphs, validation on the phone number field in a form, or dob in a dataset, the power of regular expression comes into play.
For example, we have a list or a group of valid phone numbers. Instead of keeping that long and unwieldy list around, it’s often more practical to have a short and precise pattern that completely describes that set and if you want to check a new phone number is valid or not. So you can simply match it against the pattern and get the result of its validation in the terms of true and false.
So, this article will let us know about the necessary concepts related to Regular Expressions and also discuss important properties and limitations of Regular Expressions.
In simple words, we can say that a regular expression is a set of characters that helps to find a certain pattern, substrings in a given string.
Regular expressions are patterns or a sequence of special characters that help programmers to find or match patterns present in the text.
Regular expressions are very powerful but can be hard to read because they use special characters.
There are lots of analyses that say Regular Expression is frequently used when we work with string-searching algorithms for “find” or “find and replace” operations on strings, or for input validation.
For Example, extracting all hashtags from a tweet, getting email iD or phone numbers, etc from large unstructured text content, Implementing validation on the input field.
Sometimes, we want to identify the different components of an email address.
What are the Properties of Regular Expressions?
The innumerable use of Regular Expression in different tech is because of its vast properties. These properties make the RegEx a very useful functionality. Some of the important properties of Regular Expressions are as follows:
1. The Regular Expression language is formalized by an American Mathematician named Stephen Cole Kleene.
2. Regular Expression(RE) is a formula in a special language, which can be used for specifying simple classes of strings, a sequence of symbols. In simple words, we can say that Regular Expression is an algebraic notation for characterizing a set of strings.
3. Regular expression requires two things, one is the pattern that we want to search or that we want to match and the other is a corpus of text or a string from an input field from which we need to search/match the pattern.
4. It works as a pattern validator in many cases.
5. Mathematically, the concept of Regular Expression can be defined in the following manner:
- ε is a Regular Expression, which indicates that the language is having an empty string.
- φ is a Regular Expression which denotes that it is an empty language.
- If A and B are Regular Expressions, then the following expressions are also regular.
- A, B
- A.B(Concatenation of AB)
- A+B (Union of A and B)
- A*, B* (Kleen Closure of A and B)
6. If a string is derived from the above rules then that would also be a regular expression.
Building Blocks of Regular Expression
These are the distinct blocks that help to construct a regular expression. There are many building blocks for Regular Expression and some of these are Literals, groups, Ranges, OR operator, quantifier, etc.
Let us take a look into the overview of them.
The literal is the most basic building block for RegEx. Literals are the pattern in the regular expression that matches the same literal value.
Most characters in a regex pattern do not have a special meaning, they simply match themselves. Consider the following pattern:
I am a useless regex pattern or a regular expression
None of the characters in this pattern has a special meaning. Thus each character of the pattern matches itself. Therefore there is only one string that matches this pattern, and it is identical to the pattern string itself.
The groups are a very useful building block in the regular expression. The grouping of a pattern has several uses. You can easily make the subpattern by enclosing them in round brackets. Some of the use cases are:
- simplify regex notation, making intent clerer
- apply quantifiers to sub-expressions
- extract sub-strings matching a group
- replace sub-strings matching a group
It is often tedious and error-prone to list all possible characters in a character class. Used to add consecutive characters in the character class. To specify the range of the acceptable character we use the dash operator:
The ordering of characters by a numeric value is present in Unicode Index. If you’re working with numbers, Latin characters, and basic punctuation, you can instead look at the much smaller historical subset of Unicode: ASCII.
The digits zero through nine are encoded sequentially through code-points:
0 to code point
9, so a character set of
[0–9] is a valid range.
Also, the lower and upper case alphabets are present and ordered in the alphabetic character class.
The following character set matches any lower case Latin character:
The following character set matches any upper case Latin character:
[ A-Z ]
You can define multiple ranges within the same character class. The following character class matches all lower case and upper case Latin characters:
The above pattern can also be defined as:
That is a valid character class, but it matches not only A-Z and a-z, it also matches all characters defined between Z and a, such as
Predefined Character Classes
Some character classes are used so frequently that there are shorthand notations defined for them. Consider the character class
[0–9]. It matches any digit character and is used so often that there is a mnemonic notation for it:
The below table shows character classes with the most common shorthand notations, likely to be supported by any regex engine you use.
Boundary matchers — also known as “anchors” — do not match a character as such, they match a boundary. They match the positions between characters if you will.
The most common anchors are
These tags match the beginning and end of a line respectively.
The below table shows the most commonly supported anchors.
Use cases of RegEx.
Regular expressions are useful in any scenario that benefits from full or partial pattern match on strings. These are some of the common use cases:
- verify the structure of strings
- extract substrings form structured strings
- search / replace / rearrange parts of the string
- split a string into tokens
- Rule-based information Mining systems
- Text feature Engineering
- Pattern Validation in Forms
- Data Extraction, etc.
Limitation of Regular Expression
Regex can only parse regular grammars anything context-free and higher you need a stack (i.e. a real parser) which is the real-time limitation.
The performance of the RegEx depends on the particular implementation.
- It Cannot solve everything. ( anyone on SO would say what happens when you try to parse HTML with regex)
- Having readability and performance issues.
- It is not for simple task, like substrings of string, and also not for complex task.
- Regular expressions derive their name from the fact that the strings they recognize are (in a formal computer science sense) “regular.” This implies that there are certain kinds of strings that it will be very hard, if not impossible, to recognize with regular expressions.
- Another issue to keep in mind is that some regular expressions can have exponential complexity. In plain words, this means that it is possible to craft regular expressions that take a really, really long time to test strings against.
- A common Most issue when performing form validation with regular expressions is validating e-mail addresses. Most people aren’t aware of the variety of forms e-mail addresses can take. Valid e-mail addresses can contain punctuation characters like ! and +, and they can employ IP addresses instead of domain names (like firstname.lastname@example.org). You’ll need to do a bit of research and some experimentation to ensure that the regexps you create will be robust enough to match the types of strings you’re interested in.
And finally, it is important to remember that even the best-crafted pattern cannot test for semantic validity.
So we can conclude that the regular expression or regEx contains a specific set of rules which we have to follow while using it. The numerous use of the regular expression in various use cases also marks the limitation of the regular expression.
I hope this article made you help gain a better insight into this concept.
Thanks for reading.