How to check if a string is a substring of items in a list of strings

Navigating special cases

When working with special characters or unique patterns within our substrings, we can deploy Python’s regular expressions (aka regex), from the re library:

import re  # Regex, Python's "hard mode".

str_list = ["abc-123", "def-456", "ghi-789"]
pattern = re.compile(r'abc-\d+')

matches = [s for s in str_list if pattern.search(s)]  # Going pattern fishing!


Efficient multiple substring checks

For optimizing checks against a multitude of substrings, a fusion of list comprehensions can be the key to success:

substrings = ["abc", "123", "xyz"]
matches = [s for s in str_list if any(substr in s for substr in substrings)]  # When one substring just isn't enough.


Navigating substrings with special characters

Extra caution and specific regex patterns may be needed when our substrings contain special characters:

import re  # We meet again, old friend.

special_substr = re.escape('fi*2')
books_with_specials = [book for book in 📚 if re.search(special_substr, book)]  # It's like a character hunt!


Validating the iterable

Ensuring the integrity of our list (making sure it's iterable) before even attempting substring detection is important:

if isinstance(📚, list):
    matching_books = [book for book in 📚 if 🔦 in book]  # Intelligent coding.


Lambdas and filters working together

To filter away the decoys (elements which are non-matches), we can deploy powerful lambda functions:

matches = list(filter(lambda book: 🔦 in book, 📚))  # Shining the flashlight through a fine filter.


Different methods for unique criteria

We delve into a multitude of situations where different approaches may be necessary for seeking out substrings in list elements.

Distinguishing directly matched unfiltered from mere substrings

If we distinguish between direct matches and the presence of a substring, we cater to diverse requirements:

# Direct match
exact_matches = [s for s in str_list if s == substr]

# Substring match
substr_matches = [s for s in str_list if substr in s]


Extracting substrings while filtering

We can even extract substrings amidst the filtering process:

extracted_substrings = [s.split(substr, 1)[1] for s in str_list if substr in s]  # It's like a Boolean filter with treasure inside.


Smart set operations

For handling extensive datasets, efficient set operations can be just what we need:

set_list = set(str_list)
substrings_set = {substr for substr in str_list if substr in set_list}  # Unleashing the power of set operations.
