from collections import Counte
class Solution:
def isAnagram(self, s: str, t: str) -> bool:
if len(s) != len(t):
return False
return Counter(s) == Counter(t)r
An anagram is defined as "any other word that has the same number of occurrences of each letter in the given word as in the provided word, and the other word contains no letters that are not present in the given word."
In other words, a word is an anagram of another word if the counts of the individual letters in each are the same. For a string, the Counter datatype monitors letter counts in a word. And its equals operation == determines if two Counter objects have the identical letter counts in the two words that were used to initialize the objects.
Hence, we create a Key-value in Counter object where key is the character of string and value is count of occurrences of that character.
When comparing two counters or dictionaries
- Keys: Make sure that the keys in the two dictionaries are comparable. For example, if one dictionary has keys of type int and the other has keys of type str, they cannot be compared directly.
- Order: In Python, dictionaries are unordered by default. If you want to compare two dictionaries based on their order, you will need to use an OrderedDict.
- Values: Depending on your use case, you may need to compare the values in the dictionaries as well. Make sure that the values are of the same type and can be compared directly.
- Size: If the two dictionaries have different sizes, they cannot be equal. However, if you only want to compare certain keys or values, you can create a new dictionary with just those keys or values and compare them.
- Comparison method: Python provides several methods for comparing dictionaries, such as ==, !=, and set(). Make sure to choose the method that best fits your needs.
- Performance: Depending on the size of the dictionaries and the complexity of the comparison, performance can become an issue. If you need to compare dictionaries frequently or with large data sets, consider optimizing your code or using a more efficient data structure.
