Text Compression
Explore the Huffman Encoding algorithm to compress text by building frequency dictionaries and min-heaps, creating optimal prefix-free codes. Learn how to construct and traverse Huffman Trees for efficient binary encoding of characters, reducing storage size based on character frequency.
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The Huffman Encoding algorithm can be used to find provably optimal length prefix free codes to compress data that involves redundancies. For simplicity, the algorithm can be divided into five parts:
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First, we create a
dictionary A Python dictionary stores unordered key-value pairs. createFrequencyDictionary. This dictionary is calledfrequencyDictionary. We check for every unique character and add its count in thefrequencyDictionaryagainst the ...