Tagged with strings
Python strings are Unicode text, while bytes are encoded binary data that must be encoded or decoded at boundaries.
Escape sequences, Unicode, encoding, and decoding in Python
Python regular expressions help when patterns are simpler to express declaratively than with manual loops.
Regular expressions: search vs match, groups, and substitution
Python supports old `%` formatting, `str.format`, and f-strings, with f-strings usually being the clearest modern default.
String formatting and f-strings
Strings are immutable primitive values, and JavaScript offers many helper methods plus template literals for interpolation.
JavaScript strings, string methods, template literals, and string immutability
JavaScript regexes support pattern matching, modifiers, capture groups, and replacement operations for text processing.
Regular expressions basics in JavaScript: pattern matching, flags, groups, and replace/substitution
Either sort both strings and compare them, or build character frequency maps. The hash-map version is linear time and communicates counting skill well.
Check whether two strings contain the same characters with the same counts.
Iterate through the string once and increment the count for each character so the result maps each distinct character to its frequency.
Return a frequency map for all characters in a string.
Split the text into words, normalize if needed, and increment counts in a dictionary. Python collections.Counter is great, but interviewers may ask for the manual version first.
Return a frequency map for the words in a sentence.
Build a frequency map for the characters, then iterate through the string a second time to return the first character whose count is one.
Return the first character in a string that appears exactly once, or an empty string if none exists.
Use a dictionary keyed by the sorted characters of each word, then append each word into the matching bucket.
Group words that are anagrams of each other and return the grouped lists.