Completed Hashing-1

14. Group Anagrams.py

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+#Group Anagrams
+
+class Solution:
+    def groupAnagrams(self, strs: List[str]) -> List[List[str]]:
+        # Using prime number hashing to identify anagrams
+        def getPrimes(str):
+            # Computing hash by multiplying prime numbers assigned to each character
+            hash = 1
+            primes = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101]
+            for s in str:
+                # Multiplying hash with prime corresponding to each character
+                hash *= primes[ord(s) - ord('a')]
+            return hash
+
+        # Storing strings grouped by their hash values
+        result = defaultdict(list)
+        for s in strs:
+            # Computing hash for each string and grouping anagrams together
+            hashValue = getPrimes(s)
+            result[hashValue].append(s)
+        # Returning all grouped anagrams
+        return list(result.values())
+
+# TC: O(n * k) where n is number of strings and k is average length of string
+# SC: O(n * k) for storing all strings in the result dictionary

15. Isomorphic Strings.py

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+15. Isomorphic Strings
+
+
+class Solution:
+    def isIsomorphic(self, s: str, t: str) -> bool:
+        # We are maintaining two mappings to ensure one-to-one character correspondence
+        smap = {}  # Mapping characters from s to t
+        tmap = {}  # Mapping characters from t to s
+
+        # We are iterating through each character pair in both strings
+        for i in range(len(s)):
+            sChar = s[i]
+            tChar = t[i]
+
+            # We are checking if sChar already has a mapping
+            if sChar in smap:
+                # We are verifying the mapping is consistent
+                if smap[sChar] != tChar:
+                    return False
+            else:
+                # We are creating a new mapping from s to t
+                smap[sChar] = tChar
+
+            # We are checking if tChar already has a mapping
+            if tChar in tmap:
+                # We are verifying the reverse mapping is consistent
+                if tmap[tChar] != sChar:
+                    return False
+            else:
+                # We are creating a new reverse mapping from t to s
+                tmap[tChar] = sChar
+
+        # We are returning True if all character mappings are consistent
+        return True
+
+# Time Complexity (TC): O(n) - where n is the length of string s
+# Space Complexity (SC): O(1) - at most 26 lowercase letters in each map (constant space)

16. Word Pattern.py

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+class Solution:
+    def wordPattern(self, pattern: str, s: str) -> bool:
+        # Splitting the string into words
+        words = s.split(" ")
+        # Checking if the number of words matches the pattern length
+        if len(words) != len(pattern):
+            return False
+        # Creating a mapping from pattern characters to words
+        pat_to_words = {}
+        # Creating a reverse mapping from words to pattern characters
+        words_to_pat = {}
+
+        # Iterating through each pattern character and corresponding word
+        for p, w in zip(pattern, words):
+            # Checking if pattern character already exists with a different word
+            if p in pat_to_words and pat_to_words[p] != w:
+                return False
+            # Checking if word already exists with a different pattern character
+            if w in words_to_pat and words_to_pat[w] != p:
+                return False
+            # Mapping pattern character to word
+            pat_to_words[p] = w
+            # Mapping word to pattern character
+            words_to_pat[w] = p
+        # Returning True if all mappings are consistent
+        return True
+
+# Time Complexity (TC): O(n) where n is the length of pattern/words
+# Space Complexity (SC): O(k) where k is the number of unique characters in pattern