Python Articles - Page 991 of 1048

Non capturing groupsIf  we do not want a group to capture its match, we can write this regular expression as Set(?:Value). The question mark and the colon after the opening parenthesis are the syntax that creates a non-capturing group. The regex Set(Value)? matches Set or SetValue. In the first case, the first (and only) capturing group remains empty. In the second case, the first capturing group matches Value. The question mark appearing at the end is the quantifier that makes the previous token optional. Set(?:Value) matches Setxxxxx, i.e., all those strings starting with Set but not followed by Value. Such would be ... Read More

Using Python, we can easily search for specific types of files from a mixed list of file names using regular expressions. For this, we need to import Python’s built-in module called re using the import keyword. The Regular expression or Regex is a special sequence of characters like \, *, ^, etc, which are used to search for a pattern in a string or a set of strings. It can detect the presence or absence of characters by matching them with a particular pattern and can also split a string into one or more substrings. The following is a syntax ... Read More

In this article you will find out how to extract data from a string with Python Regular Expressions. In Python, extracting data from the given string is a common task. Regular expressions (regex) offer pattern-matching functionality to get and identify specific parts of a string. Python's re module helps in working with regex easily. The common functions or this module are re.search(), re.findall() and re.match() to make it easier to extract desired data. Extract Data Using Regular Expressions For extracting data we will have to define a pattern and apply it to a string with the help of regex functions. ... Read More

This article will explain you how to write Python regular expression to check alphanumeric characters. Alphanumeric characters in Python are defined as letters like (a-z, A-Z) and numbers (0-9). If you want to check that the string has only alphanumeric characters like letters and numbers you can use Python's re module which makes this task easy. Regex Pattern for Alphanumeric Check Here is the regex pattern for checking alphanumeric characters - ^[a-zA-Z0-9]+$ The pattern (a-z) represents lowercase letters, (A-Z) means uppercase letters and (0-9) represents numbers from 0 to 9. And "^" is start of the string, ... Read More

This article will discuss how to write a Python regular expression that matches floating point numbers. We will try to create a regular expression pattern that can match any floating point number. So the regex we are going to create should also match integers and floating point numbers in which the integer part is not given. A floating-point number can be look like - Whole numbers with decimals like 3.14, 1.5, 12.10, Negative numbers like -2.55, -1.003, Numbers with optional zeros like 007.5, .75. Regex Pattern for Floating Point Number Here is the regular expression pattern ... Read More

Here, we will learn how to write a regular expression for validating a number in Python. As you may know Python has a module called re module for working with regular expression easily using the built-in functions. The re.match() function matches or validate the regex pattern with the given number. There are several ways to validate a number using regular expression, such as - Validate Integer Number Validate Real Number Validate Comma Separated Numbers Example: Validate Integer Number The following example will use different integer values to validate that they are numbers or not. We are ... Read More

This article will explain how to write a Python regular expression to use re.findall() method. Regular expression, or regex, is used insearching and extracting patterns in text. Python provides the re module to work with regex, and re.findall() to find all matches of a pattern in a string. The re.findall() method returns a list of all occurrences of a pattern. It works with strings for extracting data. And it supports metacharacters for pattern matching. There are various ways to use the re.findall() method in Python, such as - Finds One or More Digits Find All Words in a String Extract ... Read More

Backslashes in Python regular expressions (regex) are used to define special sequences and escape characters. As backslashes are also used in Python strings, we need to be careful while using them. How Backslashes Work Now let us see how backslashes work in Python regular expressions - Escaping Characters: Some characters have specific meanings in regex (such as . or *). To treat them as normal characters, use a backslash (\.). ... Read More

This article gives a guide on the difference between re.findall() and re.finditer() methods available in Python. The re module of Python helps in working with regular expressions. Both the re.findall() and re.finditer() methods are used to search for patterns, but they behave differently. Let us see the differences with simple explanations and examples in this article. Using re.findall() Method The re.findall() helps to get a list of all matching patterns. It searches from the start or end of the given string. If we use the findall() method to search for a pattern in a given string, it will return all occurrences ... Read More

In this article, we are going to learn how to extract a URL from an HTML link using Python regular expressions. URL is an acronym for Uniform Resource Locator; it is used to identify the location resource on the Internet. URL consists of a domain name, path, port number, etc. The URL can be parsed and processed by using a Regular Expression. Therefore, if we want to use a Regular Expression, we have to use the "re" library in Python. Following is an example of a URL - URL: https://www.tutorialspoint.com/courses If we parse the above URL we can find ... Read More