Regular expressions (regex) are special sequences of characters used to find or match patterns in strings, as this introduction to regex explains. We’ve previously shown how to use regular expressions with JavaScript and PHP. The focus of this article is Python regex, with the goal of helping you better understand how to manipulate regular expressions in Python. You’ll learn how to use Python regex functions and methods effectively in your programs as we cover the nuances involved in handling Python regex objects. Regular Expression Modules in Python: re and regexPython has two modules — Python’s Built-in re ModuleMore often than not, Python developers use the Before we can use the
This makes the module available in the current file so that Python’s regex functions and methods are easily accessible. With the A Selection of re Functions.The re.search(pattern, string, flags=0) vs re.match(pattern, string, flags=0)The Both functions always return the first matched substring found in a given string and maintain a default value Python’s
Python’s
Let’s see some code examples to further clarify:
From the above example,
With 45, the match object at the beginning of the string, the re.compile(pattern, flags=0)The Here’s an example of how it works:
re.fullmatch(pattern, string, flags=0)This function takes two arguments: a string passed as a regular expression pattern, a string to search, and an optional flag argument. A match object is returned if the entire string matches the given regex pattern. If there’s no match, it returns
The code raises an re.findall(pattern, string, flags=0)The
In the code snippet above, the regex consists of a character class and a word character, which ensures that the matched substring begins with a capital letter. re.sub(pattern, repl, string, count=0, flags=0)Parts of a string can be substituted with another substring with the help of the Here’s an example:
subn(pattern, repl, string, count=0, flags=0)The
Match Objects and MethodsA match object is returned when a regex pattern matches a given string in the regex object’s Match.group([group1, …])This method returns one or more subgroups of a match object. A single argument will return a signal subgroup; multiple arguments will return multiple subgroups, based on their indexes. By default, the Here’s an example:
The argument
Match.groups(default=None)
Match.start([group]) & Match.end([group])The
The example above has a regex pattern for matching any word character after a whitespace. A match was found — Pattern.search(string[, pos[, endpos]])The
The code above picks out any alphanumeric character in the search string. The search begins at string index position of 20 and stops at 30. re Regex FlagsPython allows the use of flags when using re.I (re.IGNORECASE)This flag is used when performing a case-insentive match. The regex engine will ignore uppercase or lowercase variation of regular expression patterns:
The re.S (re.DOTALL)The
The
re.M (re.MULTILINE)By default the
re.X (re.VERBOSE)Sometimes, Python regex patterns can get long and messy. The
Practical Examples of Regex in PythonLet’s now dive in to some more practical examples. Python password strength test regexOne of the most popular use cases for regular expressions is to test for password strength. When signing up for any new account, there’s a check to ensure we input an appropriate combination of letters, numbers, and characters to ensure a strong password. Here’s a sample regex pattern for checking password strength:
Note the use of Python search and replace in file regexHere’s our goal for this example:
Here’s some code for doing that:
Python web scraping regexSometimes you might need to harvest some data on the Internet or automate simple tasks like web scraping. Regular expressions are very useful when extracting certain data online. Below is an example:
ConclusionRegular expressions can vary from simple to complex. They’re a vital part of programming, as the examples above demonstrate. To better understand regex in Python, it’s good to begin by getting familiar with things like character classes, special characters, anchors, and grouping constructs. There’s a lot further we can go to deepen our understanding of regex in Python. The Python Regex significantly reduces the amount of code we need write to do things like validate input and implement search algorithms. It’s also good to be able to answer questions about the use of regular expressions, as they often come up in technical interviews for software engineers and developers. via Pixel Lyft https://ift.tt/ceNk9zx
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