Pattern recognition in strings using regular expressions

Key takeaways:
Regex in python is a powerful tool for string pattern recognition, useful in text processing and data validation.
Pattern matching involves defining rules for identifying strings like email addresses and valid variable names.
The re module of python enables the extraction of valid identifiers from text, distinguishing between valid and invalid formats.

Regular expressions (regex) in python provide a powerful way to perform pattern recognition in strings.

This technique is widely used in various applications, including text processing, data validation, and searching for specific patterns within larger datasets. In the context of the theory of computation, regular expressions play a crucial role in understanding pattern recognition and automata theory.

Understanding regular expressions

A regular expression is a sequence of characters that defines a search pattern. It allows us to specify rules for matching strings that follow a certain pattern. For example, We can use regular expressions to find email addresses, phone numbers, dates, and more within a given text.

Recognizing valid identifiers

Let’s explore an example inspired by the theory of computation. Imagine working with a programming language where variable names must adhere to a specific pattern to be considered valid. Valid identifiers start with a letter (uppercase or lowercase) and can be followed by letters, digits, or underscores.

Implementation

Following is the implementation of the pattern recognition in strings using regular expressions in python.

# Importing the required library
import re
# Defining the Example Text
text = """
validVar1
_invalidVar
Another_Valid
123Invalid
no_spaces
"""
# Defining the Regular Expression Pattern
pattern = r'^[a-zA-Z]\w*$'
# Finding All Matches
valid_identifiers = re.findall(pattern, text, re.MULTILINE)
# Printing Valid Identifiers
print("Valid identifiers:")
for identifier in valid_identifiers:
    print(identifier)
# Finding Invalid Identifiers
lines = text.strip().split('\n')
invalid_identifiers = [line for line in lines if line not in valid_identifiers]
# Printing Invalid Identifiers
print("\nInvalid identifiers:")
for identifier in invalid_identifiers:
    print(identifier)

Code explanation

Following is the breakdown of the code given above:

Line 2: Importing the re module, which provides support for working with regular expressions in python.
Lines 5–11: This is a triple-quoted string that defines the example text containing various lines with potential identifiers. The text includes valid and invalid identifiers.
Line 13: The pattern r'^[a-zA-Z]\w*$' matches strings that start with a letter and contain only letters, digits, or underscores. Let's break this pattern to understand it more easily:
- r'': indicates that this is a raw string.
- ^: it means that whatever pattern follows must be found at the very beginning of the string.
- [a-zA-Z]: it matches any single letter, either lowercase or uppercase, at the start of the string.
- \w: it is a metacharacter matches any word character, which includes: a-z, A-Z, 0-9, and _.
- *: it is a quantifier which means "zero or more occurrences" of the preceding element.
- $: It indicates that whatever pattern precedes it must extend to the very end of the string.
Line 16: Using the re.findall() function to find all non-overlapping occurrences of the defined pattern within the given text. It extracts all the valid identifiers from the text and stores them in the valid_identifiers list.
Line 19: Prints a header to indicate that the following lines will display the valid identifiers.
Lines 20–21: Initiates a loop over each element (identifier) in the valid_identifiers list. Inside the loop, this line prints each valid identifier that was extracted from the text.
Lines 24–25: The code identifies lines from the text that are not valid identifiers and stores them in invalid_identifiers.
Lines 28–30: Prints invalid identifier to the console.

Frequently asked questions

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Who created regex?

Regular expression is originated in 1951 by Stephen Cole Kleene.

How to check if a string contains only alphabets in regex?

Use ^[a-zA-Z]+$ to confirm the string consists solely of alphabets.

How do we remove duplicate words from text using Regex in python?

We can remove duplicate words from text using this Regex: regex = r'\b(\w+)(?:\W+\1\b)+'. If you want to learn complete implementation of this regular expression in python, check out our Answer on How to remove duplicate words from text using Regex in python.

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