Regex

Regex

Regular expressions provide a declarative language to match patterns within strings. They are commonly used for string validation, parsing, and transformation. Since regular expressions are not fully standardized, all questions with this tag should also include a tag specifying the applicable programming language or tool.
Ambert Lency

Ambert Lency

1581576250

How to Use Regex in Java

Introduction

In this article, we will learn about Java Regex, and how to use Regex with examples in Java. Java regex is also known as Java Regular Expression.

What is Regex in Java?

Regular expressions or Java Regex is an API built to define string patterns that can be used to read, alter, and delete data. For pattern matching with the regular expressions, Java offers java.util.regex bundle.

In other words, a regular expression is a special sequence of characters that helps us match or find other strings using a special syntax held in a pattern that is used to search, edit, or manipulate text and data.

java.util.regex package

This provides regular expressions with three classes and a single interface. The classes Matcher and Pattern are usually used in standard Java language.

The complete program of regex package is listed below.

import java.util.regex.Pattern;  
  
public class RegexPackageExample {  
    public static void main(String args[]) {  
        System.out.println(Pattern.matches(".y", "toy"));  
        System.out.println(Pattern.matches("s..", "sam"));  
        System.out.println(Pattern.matches(".a", "mia"));  
    }  
} 

The above program generates the following output.

This is image title

PatternSyntaxException class

PatternSyntaxException is a unresolved exception object which means a syntax error in a normal speaking pattern.

The complete program of Showing the PatternSyntaxException class example is listed below.

import java.util.regex.Pattern;  
  
public class PatternSyntaxExceptionExample {  
    public static void main(String... args) {  
        String regex = "["; // invalid regex  
        Pattern pattern = Pattern.compile(regex);  
    }   
} 

The above program generates the following output.

This is image title

Note

In the above example program, we use the invalid syntax of regex. So, when we run the program it generates the PatternSyntaxException: Unclosed character class near index 0;

java.util.regex.Matcher;

A Matcher entity is a motor that interprets the template against an input string and executes operations of play. Matcher doesn’t describe any public builders, as the class Template. By calling the matcher method) (you get a Matcher object on a Pattern object.

Methods of Matcher class

public boolean matches()

The matches method is used to check the pattern string is matches with matcher string or not. It returns the boolean value. If the string matches, it returns true otherwise false. It does not take any argument. It does not throw any exception.

Syntax

public boolean matches();

The complete program of java.util.regex.Matcher.matches() method is listed below.

import java.util.regex.*;  
public class MatchesMethodExample {  
    public static void main(String[] args) {  
        boolean result;  
        // Get the string value to be checked  
        String value1 = "CsharpCorner";  
  
        // Create a pattern from regex  
        Pattern pattern = Pattern.compile(value1);  
  
        // Get the String value to be matched  
        String value2 = "CsharpC";  
  
        // Create a matcher for the input String  
        Matcher matcher = pattern.matcher(value2);  
  
        // Get the current matcher state  
        System.out.println("result : " + matcher.matches());  
    }  
} 

The above program generates the following output.

This is image title

public int start() Method

The start() method is used to get the start subsequence index. public int start() method does not take any argument. It returns the index of the first character matched 0. If the operation is failed it throws IllegalStateException.

Syntax

public int start();

The complete program of java.util.regex.Matcher.start() method is listed below.

import java.util.regex.*;  
  
public class StartMethodExample {  
    public static void main(String[] args) {  
  
        // Get the string value to be checked  
        String value1  = "CsharpCorner";  
  
        // Create a pattern from regex  
        Pattern pattern = Pattern.compile(value1);  
  
        // Get the String value to be matched  
        String value2 = "Csharp";  
        // Create a matcher for the input String  
        Matcher matcher = pattern.matcher(value2);  
  
        // Get the current matcher state  
        MatchResult result = matcher.toMatchResult();  
        System.out.println("Current Matcher: " + result);  
  
        while (matcher.find()) {  
            // Get the first index of match result  
            System.out.println(matcher.start());  
        }  
    }  
}

The above program generates the following output.

This is image title

public boolean find() Method

The find method is used to find the next subsequence of the input sequence that finds the pattern.  It returns a boolean value. If the input string matches then it returns true otherwise returns false. This method does not take any argument. This method does not throw any exception.

Syntax

public boolean find()

The complete program of java.util.regex.Matcher.find() method is listed below.

import java.util.regex.*;  
public class FindMethodExample {  
    public static void main(String args[]) {  
        // Get the regex to be checked  
        String value = "CsharpCorner";  
        String value1 = "Java Programming";  
  
        // Create a string from regex  
        Pattern pattern = Pattern.compile(value);  
        Pattern pattern1 = Pattern.compile(value1);  
  
        // Get the String for matching  
        String matchString = "CsharpCorner";  
        String matchString1 ="Java";  
  
        // Create a matcher for the String  
        Matcher match = pattern.matcher(matchString);  
        Matcher match1 = pattern.matcher(matchString1);  
        //find() method  
        System.out.println(match.find());  
        System.out.println(match1.find());  
  
    }  
} 

The above program generates the following output.

This is image title

public boolean find(int start) Method

The find(int start) method is used to find the next subsequence of the input sequence that finds the pattern, according to the given argument. It returns a boolean value. This method does not take any argument. This method throws IndexOutOfBoundException if the given argument is less then zero or greater then the length of the string.

Syntax

public boolean find(int start);

The complete program of java.util.regex.Matcher.find() method is listed below.

import java.util.regex.*;  
  
public class FindMethodExample2 {  
    public static void main(String args[]) {  
        // Get the regex to be checked  
        String value = "CsharpCorner";  
        String value1 = "Java Programming";  
  
        // Create a string from regex  
        Pattern pattern = Pattern.compile(value);  
        Pattern pattern1 = Pattern.compile(value1);  
  
        // Get the String for matching  
        String matchString = "CsharpCorner";  
        String matchString1 = "Java";  
  
        // Create a matcher for the String  
        Matcher match = pattern.matcher(matchString);  
        Matcher match1 = pattern.matcher(matchString1);  
        //find() method  
        System.out.println(match.find(3));  
        System.out.println(match1.find(6));  
  
    }  
} 

The above program generates the following output.

This is image title

public int end() Method

The end method is used to get the offset after the last match of the character is done. This method doesn’t take any argument. this method throws IllegalStateException if the operation fails.

Syntax

public int end()

The complete program example of java.util.regex.Matcher.end() is listed below.

import java.util.regex.*;  
public class endMethodExample {  
    public static void main(String[] args) {  
        // TODO Auto-generated method stub  
        Pattern p=Pattern.compile("Hello C#Corner");  
        Matcher m=p.matcher("Hello C#Corner");  
        if(m.matches())  
            System.out.println("Both are matching till "+m.end()+" character");  
        else  
            System.out.println("Both are not matching"+m.end());  
    }  
} 

The above program generates the following output.

This is image title

java.util.regex.Pattern

A Pattern object is a compiled representation of a regular expression. There are no Template level public designers. To construct a template, you first need to invoke one of its public static compiles (methods which subsequently return a Template item, which acknowledges a regular expression as the first statement

It is the compiled form of a regular expression and is used to describe the Regex engine template.

Methods of Pattern class

static Pattern compile(String regex)

The compile() method is used to match a text from a regular expression(regex) pattern. If the operation is failed it returns false otherwise true. This method takes a pattern string value as the argument.

Syntax

static Pattern compile(String regex)

The complete program of the java.util.regex.pattern.compile();

import java.util.regex.Matcher;  
import java.util.regex.Pattern;  
  
public class CompileMethodExample {  
  
    public static void main(String args[]) {  
  
        // Get the string value to be checked  
        Pattern p = Pattern.compile(".o");  
          
        //Matcher string for  
        Matcher m = p.matcher("to");  
        boolean m1 = m.matches();  
        System.out.println(m1);  
    }  
}  

The above program generates the following output.

This is image title

public boolean matches(regex, String)

The matches() method is used to check the given string matches the given regular expression or not. This method returns the boolean value true if the string matches the regex otherwise it returns false.  If the syntax is invalid then this method throws PatternStateException.

This method takes two arguments.

  • regex- This argument is the regular expression value which has to check from the string.
  • String- This string value has to check from the regex through the matches() method.

The complete program of the public boolean matches(regex, String) method is listed below.

import java.util.regex.Pattern;  
  
public class PatternClassMatchesMethod {  
    public static void main(String args[]) {  
        System.out.println(Pattern.matches("[bad]", "abcd"));  
        System.out.println(Pattern.matches("[as]", "a"));  
        System.out.println(Pattern.matches("[ass]", "asssna"));  
    }  
} 

The above program generates the following output.

This is image title

Summary

In this article, we learned about Java Regular Expression(regex) in Java Programming Language and the varoius methods of regex.

Thank for reading and keep visiting!

#java #java-regex #programming #language #regex

How to Use Regex in Java

Why should you be aware of Regex | How Regex helps in your project?

In this video I’ve explained how regex are beneficial for your project and why should you have a glimps over it …

Tryout the demo site (devlopment stage) of College Facemash : http://cfm-react.s3-website-us-east-1.amazonaws.com/

The whole journey of making facemash: https://www.youtube.com/playlist?list=PL83X-jRLQqGGTDlCmLLzgnLpMY3xo1Nj8

Checkout the other videos of DevTalks: https://www.youtube.com/playlist?list=PL83X-jRLQqGGOXn5eJU_JJTlXUyC3gXQB

If you have any suggestions, Queries or any though just leave it in comment and I’ll be happy to get back to you
#Regex #formValidation #DBMS

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#formvalidation #dbms #regex

Why should you be aware of Regex | How Regex helps in your project?
Edureka Fan

Edureka Fan

1599616805

Introduction to Python RegEx | What is Python RegEx | Python Training

This Edureka “Python RegEx” tutorial will help you in understanding how to use regular expressions in Python. You will get to learn different regular expression operations and syntaxes.

#python #regex

Introduction to Python RegEx | What is Python RegEx | Python Training

Regular Expression Complete Guide

Regular expressions or regex puts a lot of people off, just because of its look at first glance. But once you master this it will open a whole new different level of doing string manipulation and the best part of it is that it can be used with mostly all of the programming language as well as with Linux commands. It can be used to find any kind of pattern that you can think of within the text and once you find the text you can do pretty much whatever you want to do with that text. By this example, you can get an idea of how powerful and useful regex is.
What is Regex?
If you are reading this post then most probably you already know what a regex is, if you don’t know here is a quick and easy definition
Regex stands for Regular Expression and is essentially an easy way to define a pattern of characters. The most common use of regex is in pattern identification, text mining, or input validation.

#regular-expressions #python #regex #python-regex #pattern-finding

Regular Expression Complete Guide
Adam Daniels

Adam Daniels

1560786340

An Introduction to Regex in Python

What is Regex?

Regex stands for Regular Expression and essentially is an *easy *way to define a pattern of characters. Regex is mostly used in pattern identification, text mining or input validation.

Regex puts a lot of people off, because it looks like gibberish on first look; as for the people who know how to use it, they can’t seem to stop! It’s a very powerful tool that is worth learning about if you don’t already know.

Introduction to Regex

The first thing you need to know about regex, is that you can match a specific character or words.

Let’s assume, that we want to know whether a specific string, contains the letter ‘a’ or word ‘lot’. If that is the case, we can use the following python code:

import re
str = "Learning regex can be a lot of fun"
lst = re.findall('a', str)
lst2 = re.findall('lot', str)
print(lst)
print(lst2)

which will return, a list with 3 matches and a list of 1:

['a', 'a', 'a']
['lot']

Keeping our set up the same, imagine that you want to search for the following 3 letters in any order a, b or c. You can use a list, by using square brackets:

lst = re.findall('[abc]', str)
lst2 = re.findall('[a-c]', str)
print(lst)
print(lst2)

returning:

['a', 'c', 'a', 'b', 'a']
['a', 'c', 'a', 'b', 'a']

Photo by Dayne Topkin on Unsplash

The Regex Cheat Sheet

Every time I am about to write a complicate regular expression, my first port of contact is the following list, by Dr Chuck Severance:

Python Regular Expression Quick Guide

^        Matches the beginning of a line
$        Matches the end of the line
.        Matches any character
\s       Matches whitespace
\S       Matches any non-whitespace character
*        Repeats a character zero or more times
*?       Repeats a character zero or more times 
         (non-greedy)
+        Repeats a character one or more times
+?       Repeats a character one or more times 
         (non-greedy)
[aeiou]  Matches a single character in the listed set
[^XYZ]   Matches a single character not in the listed set
[a-z0-9] The set of characters can include a range
(        Indicates where string extraction is to start
)        Indicates where string extraction is to end

Using the above cheat sheet as a guide, you can pretty much come up with any syntax. Let’s take a closer look in some more complicate search patterns.

Stepping it Up

Imagine that you are building some sort of validation on an input field where the user can input any number followed by the letter d, m or y.

Your regex algorithm would look something like this:

^[0-9]+[dmy]$

Decomposing the above: ^ signifies the beginning of the match followed by a 0–9 number. However the + sign means it needs to be at least one 0–9 number though there can be more. Then the string needs to be followed by d, m or y, which have to be at the end because of $.

Testing the above in python:

import re
str = '1d'
str2 = '200y'
str3 = 'y200'
lst = re.findall('^[0-9]+[dmy]$', str)
lst2 = re.findall('^[0-9]+[dmy]$', str2)
lst3 = re.findall('^[0-9]+[dmy]$', str3)
print(lst)
print(lst2)
print(lst3)

Returning:

['1d']
['200y']
[]

Photo by Arget on Unsplash

Escaping Special Characters

When it comes to regular expressions, certain characters are special. For instance, dot, star and dollar sign are all used for matching purposes. So what happens if you want to match those characters?

In that case, we can use the back slash.

import re
str = 'Sentences have dots. How do we escape them?'
lst = re.findall('.', str)
lst1 = re.findall('\.', str)
print(lst)
print(lst1)

The above example is using dot, and backslash dot. As you would expect, it returns two results. The first one matches all characters, while the second one, only the dot.

['S', 'e', 'n', 't', 'e', 'n', 'c', 'e', 's', ' ', 'h', 'a', 'v', 'e', ' ', 'd', 'o', 't', 's', '.', ' ', 'H', 'o', 'w', ' ', 'd', 'o', ' ', 'w', 'e', ' ', 'e', 's', 'c', 'a', 'p', 'e', ' ', 't', 'h', 'e', 'm', '?']
['.']

Matching exact number of characters

Imagine that you want to match a date. You know that what the format will be, DD/MM/YYYY. Sometimes there will be 2Ds or 2Ms, sometimes just one, but always 4Ys.

import re
str = 'The date is 22/10/2018'
str1 = 'The date is 3/1/2019'
lst = re.findall('[0-9]{1,2}\/[0-9]{1,2}\/[0-9]{4}', str)
lst = re.findall('[0-9]{1,2}\/[0-9]{1,2}\/[0-9]{4}', str1)
print(lst)
print(lst1)

Which gives the following results:

['22/10/2018']
['3/1/2019']

Extracting the matched pattern

There are certain times, that knowing the fact that you’re matching a pattern is not enough. You want to have the ability to extract information from the match.

For instance, imagine that you are scanning a large data set looking for email addresses. If you use what we learnt about, you could search for a pattern of:

  • Could start with a letter, number, dot or underscore
  • Then followed by at least another letter, or number
  • Which could be followed by a dot or an underscore
  • Then there’s a @
  • Then follow the same logic again as before the @
  • Finally look for a dot followed by at least a letter
^[a-zA-Z0-9\.\_]*[a-zA-Z0-9]+[\.\_]*\@[a-zA-Z0-9\.\_]*[a-zA-Z0-9]+[\.\_]*\.[a-zA-z]+

From the above match, you only want to extract the domain name ie everything after the @. All you have to do is add brackets around what you’re after:

import re
str = '[email protected]'
lst = re.findall('^[a-zA-Z0-9\.\_]*[a-zA-Z0-9]+[\.\_]*\@([a-zA-Z0-9\.\_]*[a-zA-Z0-9]+[\.\_]*\.[a-zA-z]+)', str)
print(lst)

Returning:

['gmail.com']

In Summary

In summary, you can use regex to match strings of data and it can be used in a number of different ways. Python includes a regex package called re, which will allow you to use this. Should you find yourself on a Unix machine however, you can use regular expression along with grep, awk or sed. On Windows should you want to access all these commands, you can use tools like Cygwin.

Thanks for reading ❤

If you liked this post, share it with all of your programming buddies!

#python #regex

An Introduction to Regex in Python
Joseph  Norton

Joseph Norton

1591862303

An Introduction to Regex In JavaScript

Useful tools for finding matching patterns in a string

What’s Regex?

Regex, short for Regular Expressions are useful tools to find matching patterns in a string.

They can be used to validate text from user input, check formatting of the string (like an email or a 12-digit phone number) and allows the search for a certain pattern of words or numbers in a string.

Most programming languages like JavaScript use regex. It can be, however, quite difficult to learn all its complicated syntax and rules to follow. But once you get started with the basics, I have a simple and fun way for you to master regex like a pro.

Let’s go to the basics: The Rules

Here are some basic regex rules and syntax to know.

#regex #javascript #developer

An Introduction to Regex In JavaScript
Micheal  Block

Micheal Block

1604026800

What’s So Regular About RegEx?

I’m coding along in Ruby and given a string of items separated by a comma and space plus ANOTHER string of items separated just by a space. The program I’m building should be able to take in these strings as arguments and convert them to a standard format where both are an array of individual strings. So, I need to build ONE method that can parse these items into their own individual strings in an array.

FROM:

vineyard_1 = “riesling, chardonnay, viognier”

vineyard_2 = “grenache syrah mourvedre”

TO:

vineyard_1 = [“riesling”, “chardonnay”, “viognier”]

vineyard_2 = [“grenache”, “syrah”, “mourvedre”]

Seems pretty simple.

Setting Up Pry

Since I’m going to experiment a bit I’m going to set up the pry gem.

Type in console:

gem install pry

Once successfully installed, set up a Ruby doc similar to this with a binding.pry

Image for post

Ruby file

Run the file by typing in console:

ruby <what your file name is>.rb

Welcome to the pry console!

Note: The 0 after the _binding.pry_ is just to help “catch” it so it doesn’t just pass over it and exit out. You can also put anything else after it like:

_puts “Done with Pry”_

And it will run (display to console) when you exit out of pry.

The Search for the Answer

Call ****.methods****_ to see what’s available._

In pry console, type vineyard_1.methods to see a loooooooong list of methods with no definitions that can be used on vineyard_1. I still don’t know how to use most of these yet.

Image for post

Methods PT 1

Note: To exit out of the long list that’s loading bit-by-bit, enter ‘q’.

I can get carried away with googling them one-by-one to see if it will achieve the results I want. Or….

Ask Google

I googled something like “how to split string into individual strings ruby”.

This gave useful clues towards the .split() method.

#regex #code #ruby #split #parse

What’s So Regular About RegEx?
Adam Daniels

Adam Daniels

1582888620

RegEx Roman Numerals

Working with regular expressions to decode Roman Numerals. Professor Brailsford is on the case.

#regex #python #javascript #java #webdev

RegEx Roman Numerals
Madilyn  Kihn

Madilyn Kihn

1590552565

Regex in Python — A-Z

Regex can help you perform various data preprocessing very easily.

A RegEx, or Regular Expression, is a sequence of characters that forms a search pattern with a formal syntax. Regular expressions are typically used in applications that involve a lot of text processing.

As a data scientist/engineer, having a solid understanding of Regex can help you perform various data preprocessing very easily. Personally, I use them for lots of random stuff, mostly when I have to work with text data or do Natural Language Processing projects.

There are multiple open-source implementations of regular expressions, each sharing a common core syntax but with different extensions or modifications to their advanced features. Python has a built-in package called re, which can be used to work with Regular Expressions.

Import the re module:

import re

This tutorial is quite unique because it not only explains the regex in theory but also describes in detail how the regex methods/attributes actually go about its work in Python. By following this article, you will soon be able to craft your own regular expressions if you have never done anything else before.

Let’s get started!

#data-science #regex #python #programming

Regex in Python — A-Z

What Is Regular Expressions (RegEx)?

Introduction

I really enjoy regular expressions and I find that for a lot of the algorithm challenges on leetcode or codewars, you can come up with some interesting solutions for problems using regular expressions. Or they are great for creating form validators or whatever way in which you may need to check for a string of characters, numbers, and even special characters. If you are not familiar with what regular expressions are, then this blog post is for you.

Regular Expressions, or RegEx for short, allow us to check for a match of a series of characters. For instance, you might find yourself needing to only find vowels in a string, well you can use RegEx to match ‘a’,‘e’,‘i’,‘o’,‘u’ and you can even have flexibility when doing so. You could potentially either pull all instances of each vowel’s occurrence or when they first occur or only match for them if they happen in succession. The possibilities are up to you which is great!

There are multiple ways in which you can test for matches. Two ways I will show in this blog post are the .test() method and the .match() method. Let’s look at an example so that you can get a better idea of what this would actually look like.

For the sake of this post, I will not add any flags in the RegEx examples, but I will talk about them in an upcoming blog post.

#javascript #regex #programming #developer

What Is Regular Expressions (RegEx)?

Breaking Down a Complex RegEx

While learning multiple ways to create a Pig Latinizer, I struggled to understand how a complex regex (regular expression) works its magic inside a .split method.
More specifically, I was amazed yet perplexed by a simple line of code (via this amazing programmer):
“forest”.split(/([aeiou].*)/)

=> [“f”, “orest”]

The goal of this split method is to divide a word into an array of two strings, with the first vowel of the word as a delimiter. As illustrated above, the first string contains all character(s) before the first vowel, and the second string has all characters after the first vowel (including the vowel itself).
To demystify the complexity of this split/regex combo, I decided to, uh, “split” up the regex — one regular expression at a time.

#regex #ruby-on-rails #programming #ruby #coding

Breaking Down a Complex RegEx

Regex (Regular Expressions) Demystified

To fully utilize the power of shell scripting (and programming), one needs to master Regular Expressions. Certain commands and utilities commonly used in scripts, such as grepexprsed and awk use REs.

Image for post

In this article we are going to talk about Regular Expressions

What is Regex?

Regular Expressions are sets of characters and/or metacharacters that match (or specify) patterns. The main uses for Regular Expressions (REs) are text searches and string manipulation. An RE matches a single character or a set of characters — a string or a part of a string.

Those characters having an interpretation above and beyond their literal meaning are called metacharacters.

Regex Pattern:

Generally you define a Regex pattern by enclosing that pattern (without any additional quotes) within two forward-slashes. For example, _/\w/_, and _/[aeiou]/_.

Case Sensitivity:

Note that regex engines are case sensitive by default, unless you tell the regex engine to ignore the differences in case.

Regex uses:

When you scan a string (may be multi-line) with a regex pattern, you can get following information:

  • Whether there is any match or not
  • Matched substrings within given string
  • Position of these substring within given string
  • Group back references for every substring
  • When used with \A, and \Z, rather than a matching substring, we can match whole of the given string as a unit

Regex Metacharacters

Inside a pattern, all characters except ()[]{}|\?*+.^, and $ match themselves. If you want to match one of the special characters literally in a pattern, precede it with a backslash.

Note: _Even __/_ cannot be used inside a pattern, you can escape it by preceding it with backslash.

Most regular expression flavors treat the brace { as a literal character, unless it is part of a repetition operator like {1,3}. So you generally do not need to escape it with a backslash, though you can do so if you want. An exception to this rule is the java.util.regex package which requires all literal braces to be escaped.

Escaping a Metacharacter:

The _\_ (backslash) is used to escape special characters and is used to give special meaning to some normal characters. For example, _\1_ is used to back reference first word and _\d_ means a digit character, and _\D_ means non-digit character, and to specify non-printable characters such as _\n_ (LF), _\r_ (CR), and _\t_ (tab).

Note: You can also escape backslash with backslash.

Escaping a single meta-character with a backslash works in all regular expression flavors.

All other characters should not be escaped with a backslash. That is because the backslash is also a special character. The backslash in combination with a literal character can create a regex token with a special meaning. For example, \d will match a single digit from 0 to 9.

As a programmer, you may be surprised that characters like the single quote and double quote are not special characters.

Special characters and programming languages:

In your source code, you have to keep in mind which characters get special treatment inside strings by your programming language. That is because those characters will be processed by the compiler, before the regex library sees the string.

Non-Printable Characters:

You can use special character sequences to put non-printable characters in your regular expression.

  • Use **\t** to match a tab character (ASCII 0x09), **\r** for carriage return (0x0D) and **\n** for line feed (0x0A).
  • More exotic non-printables are \a (bell, 0x07), \e (escape, 0x1B), \f (form feed, 0x0C) and \v (vertical tab, 0x0B).
  • Remember that Windows text files use **\r\n** to terminate lines, while UNIX (Linux and Mac OS X) text files use **\n**** (LF)**, and \r (CR) in older versions of Mac OS.
  • You can include any character in your regular expression if you know its hexadecimal ASCII or ANSI code for the character set that you are working with. In the Latin-1 character set, the copyright symbol is character 0xA9. So to search for the copyright symbol, you can use \xA9.
  • If your regular expression engine supports Unicode, use \uFFFF rather than \xFF to insert a Unicode character. The euro currency sign occupies code point 0x20AC. If you cannot type it on your keyboard, you can insert it into a regular expression with \u20AC.

Basic vs. Extended Regular Expressions:

Refer: http://www.gnu.org/software/grep/manual/html_node/Basic-vs-Extended.html

In basic regular expressions the meta-characters ?+{|(, and ) lose their special meaning; instead use the backslashed versions \?\+\{\|\(, and \).

Portable scripts should avoid { is **grep -E** patterns and should use [{] to match a literal {. Some implementations support \{ as meta-character.


How a Regex Engine works internally?

Knowing how the regex engine works will enable you to craft better regexes more easily.

The regex-directed engines are more powerful:

There are two kinds of regular expression engines:

  • text-directed engines, and
  • regex-directed (important) engines.

Certain very useful features, such as lazy quantifiers and backreferences, can only be implemented in regex-directed engines. No surprise that this kind of engine is more popular.

Notable tools that use text-directed engines are awkegrepflexlexMySQL and Procmail. For awk and egrep, there are a few versions of these tools that use a regex-directed engine.

You can easily find out whether the regex flavor you intend to use has a text-directed or regex-directed engine. If backreferences and/or lazy quantifiers are available, you can be certain the engine is regex-directed. You can do the test by applying the regex /regex|regex not/ to the string regex not. If the resulting match is only regex, the engine is regex-directed. If the result is regex not, then it is text-directed. The reason behind this is that the regex-directed engine is eager.

The Regex-Directed Engine Always Returns the Leftmost Match:

This is a very important point to understand: a regex-directed engine will always return the leftmost match, even if a “better” match could be found later. When applying a regex to a string, the engine will start at the first character of the string. It will try all possible permutations of the regular expression at the first character. Only if all possibilities have been tried and found to fail, will the engine continue with the second character in the text. Again, it will try all possible permutations of the regex, in exactly the same order. The result is that the regex-directed engine will return the leftmost match.

#regex #patterns #programming #linux #regular-expressions

Regex (Regular Expressions) Demystified
Alexey Kartsev

Alexey Kartsev

1601369594

Regular Expressions (RegEx) in Python

Regular expressions, aka regex, is incredibly common to help us parse data. Before we discuss how, let’s consider a practical example by using US Phone numbers. The following are all valid written phone number formats:

  • +1-555-555-3121
  • 1-555-555-3121
  • 555-555-3121
  • +1(555)-555-3121
  • +15555553121

It’s amazing that all of these numbers are the exact same just formatted slightly different. So how would we search a whole document for all possible derivations of phone number format?

“Machine learning!” you say. Well, that would probably work but it’s overcomplicating this particular challenge. Instead, we can use pattern matching, aka regular expressions, to simplify the challenge.

Regular expressions are intimidating and take some time to wrap your head around. So I created this guide as a way to unpack how to effectively use Regular Expressions in Python. Many of these regex patterns and concepts overlap to other languages especially since Python regex was inspired by Perl.

Let’s look at some code.

my_phone_number = "555-867-5309"

How do we get all the numbers (not the dashes -) from the above string? Let’s first talk about the harder and more amateur way to do it:

numbers = []
for char in my_phone_number:
    number_val = None
    try:
        number_val = int(char)
    except:
        pass
    if number_val != None:
        numbers.append(number_val)

numbers_as_str = "".join([f"{x}" for x in numbers])
numbers_as_str
'5558675309'

Here’s another way your intuition make take you:

numbers_as_str2 = my_phone_number.replace("-", "")
numbers_as_str2
'5558675309'

Finally, Python Strings (str) have a built-in method .isdigit() that can be applied to verify if the string contains a number or not. Here’s how it’s done:

numbers_as_str3 = "".join([f"{x}" for x in my_phone_number if x.isdigit()])
numbers_as_str3
'5558675309'

All of these methods are valid in that they achieve the goal but there’s a more practical and robust way to do this.

And that’s with regular expressions. Let’s see our first regex example:

import re ## the built-in regex library

pattern = r"\d+"
matches = re.findall(pattern, my_phone_number)
matches
['555', '867', '5309']

The re.findAll method actually illustrates a much better result --> each group of numbers has been parsed out by default.

To me, it’s easier to infer that ['555', '867', '5309'] is a phone number over something like 5558675309. That’s because I’m from the USA and that’s how we typically group numbers.

We still haven’t gotten to the core reason as to why we use regex. Let’s think of another example.

my_other_phone_numbers = "Hi there, my home number is 555-867-5309 and my cell number is +1-555-555-0007."

pattern = r"\d+"
matches = re.findall(pattern, my_other_phone_numbers)
matches
['555', '867', '5309', '1', '555', '555', '0007']

The numbers ['555', '867', '5309', '1', '555', '555', '0007'] are much more challenging to distinguish a list of phone numbers within a string. The length of that string was only 79 characters (including spaces/punctuation). Imagine if we had thousands of characters?

What to do? The answer, again is regex. And this is where regex really shines.

The reason for this is we’re looking for a specific pattern to parse in our text; not just digits. We actually want to ignore digits that don’t match this pattern. Say, for instance, I gave you a time and my phone number:

meeting_str = "Hey, give me a call at 8:30 on my cell at +1-555-555-0007."

If we try to only extract digits, we’ll get a few extra we don’t need. Take a look:

pattern = r"\d+"
matches2 = re.findall(pattern, meeting_str)
matches2
['8', '30', '1', '555', '555', '0007']

So what we need to do is improve our regular expression pattern. Let’s see how:

phone_pattern = r"\+\d{1}-\d{3}-\d{3}-\d{4}"
matches3 = re.findall(phone_pattern, meeting_str)
matches3
['+1-555-555-0007']

Whoa. Now, you’ve really lost me. What the heck is r"\+\d{1}-\d{3}-\d{3}-\d{4}"?

To match any digit, you use the string r"\d". The r in the front signifies this is a regular expression. The \d is the pattern to match any number digit. I’ll explain the curly braces parts in a minute but let’s dive into the \d a bit more.

numbers_with_decimals = r"\d+\.\d+"
matches4 = re.findall(numbers_with_decimals, "123.122")
no_matches = re.findall(numbers_with_decimals, "12")
print(matches4, no_matches)
['123.122'] []

The last two patterns we saw something strange with the characters + and .. That’s because regex treats these characters differently than English does. So if our regex pattern needs to use + or . we have to escape them with \+ and \. respectively.

#python #programming #developer #regex

Regular Expressions (RegEx) in Python
George  Koelpin

George Koelpin

1603234800

Most important IT side skill, Regex

I was astounded when I first learned how to search for texts using Regex and process text data in ways unimaginable to me before. Today we can utilize its power inside Python, but it is the same in all other programming languages, text editors, and IDEs. We will learn the basics faster than Trump tweets!

So What Is Regex?

Regex is short for Regular expression. Meaning: It is a short sequence of characters used to search or replace words in a long text. It is a minor form of a programming language that you can use to find what you need instantly. We will learn the basics using a weird little trump tweet.

#data-science #text #regex #programming #nlp

Most important IT side skill, Regex

An Introduction to Regex for Web Developers

This was originally posted as a twitter thread: https://twitter.com/chrisachard/status/1181583499112976384

1. Regular expressions find parts of a string that match a pattern

In JavaScript they’re created in between forward slashes //, or with new RegExp()

and then used in methods like match, test, or replace

You can define the regex beforehand, or directly when calling the method

new regex

2. Match individual characters one at a time,

or put multiple characters in square brackets [] to capture any that match

Capture a range of characters with a hyphen -

square brackets and hyphen

3. Add optional flags to the end of a regex to modify how the matcher works.

In JavaScript, these flags are:

i = case insensitive
m = multi line matching
g = global match (find all, instead of find one)

regex flag modifiers

4. Using a caret ^ at the start means “start of string”

Using a dollar sign $ at the end means “end of string”

Start putting groups of matches together to match longer strings

caret dollar sign, group matches together

5. Use wildcards and special escaped characters to match larger classes of characters

. = any character except line break

\d = digit
\D = NOT a digit

\s = white space
\S = any NON white space

\n new line

wildcards

6. Match only certain counts of matched characters or groups with quantifiers

  • = zero or more
  • = one more more ? = 0 or 1 {3} = exactly 3 times {2, 4} = two, three, or four times {2,} = two or more times

quantifiers

7. Use parens () to capture in a group

match will return the full match plus the groups, unless you use the g flag

Use the pipe operator | inside of parens () to specify what that group matches

| = or

parens to capture group

8. To match special characters, escape them with a backslash \

Special characters in JS regex are: ^ $ \ . * + ? ( ) [ ] { } |

So to match an asterisks, you’d use:

*

Instead of just *

special characters

9. To match anything BUT a certain character, use a caret ^ inside of square brackets

This means ^ has two meanings, which can be confusing.

It means both “start of string” when it is at the front of a regex, and “not this character” when used inside of square brackets.

caret to mean NOT

10. Regexs can be used to find and match all sort of things, from urls to filenames

HOWEVER! be careful if you try to use regexs for really complex tasks, such as parsing emails (which get really confusing, really fast), or HTML (which is not a regular language, and so can’t be fully parsed by a regular expression)

There is (of course) much more to regex like lazy vs greedy, lookahead, and capturing

but most of what web developers want to do with regular expressions can use just these base building blocks.

#javascript #web-development #regex

An Introduction to Regex for Web Developers