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DAA2.py

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+import heapq
+import itertools
+
+def build_huffman_tree(freq):
+    heap = []
+    counter = itertools.count()  # unique sequence count
+    for ch, weight in freq.items():
+        heap.append([weight, next(counter), [ch]])  # add counter as second element
+    heapq.heapify(heap)
+
+    while len(heap) > 1:
+        low = heapq.heappop(heap)
+        high = heapq.heappop(heap)
+        combined_weight = low[0] + high[0]
+        combined_node = [low[2], high[2]]
+        heapq.heappush(heap, [combined_weight, next(counter), combined_node])
+
+    return heap[0]
+
+def assign_codes(node, prefix="", codebook={}):
+    # node is [char] for leaf, or [left, right] for internal node
+    if len(node) == 1 and isinstance(node[0], str):
+        codebook[node[0]] = prefix
+    else:
+        assign_codes(node[0], prefix + "0", codebook)
+        assign_codes(node[1], prefix + "1", codebook)
+    return codebook
+
+def huff_en(txt):
+    freq = {}
+    for c in txt:
+        freq[c] = freq.get(c, 0) + 1
+
+    root = build_huffman_tree(freq)
+    codes = assign_codes(root[2])  # Note: root[2] because of tie-breaker
+
+    print("Huffman Codes:")
+    for ch in sorted(codes):
+        print(f"{ch}: {codes[ch]}")
+
+txt="abbbbbbcccddddddddee"
+huff_en(txt)