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Explain dictionary in python with the help of example.

Python Dictionaries: A Data Compression Perspective

What is a Python Dictionary?

  • A dictionary is a fundamental data structure in Python.
  • It stores data in key-value pairs.
  • Keys must be immutable (e.g., strings, numbers, tuples).
  • Values can be of any data type.
  • Dictionaries are unordered (before Python 3.7) and mutable.

Dictionaries and Data Compression

  • Dictionaries facilitate efficient data representation.
  • They can be used to build symbol tables for encoding/decoding in compression algorithms.
  • Representing frequent data with shorter keys saves space.
  • Key-value pairs can map original data to compressed representations.

Example: Huffman Coding with Dictionaries

  • Create a dictionary mapping characters to their Huffman codes.
  • { 'A': '00', 'B': '01', 'C': '10', 'D': '11'}
  • Use this dictionary to encode a string.
  • Decode using the same dictionary, reversing the mapping.

Example: Run-Length Encoding (RLE) with Dictionaries

  • Use a dictionary to store repeated sequences and their counts.
  • For instance, `{'AAA': 3, 'BB': 2, 'C':1}` represents 'AAABBC'.
  • This reduces storage needs for repetitive data.
  • RLE is a simple lossless compression method.

Advantages of using Dictionaries in Data Compression

  • Fast lookups using keys for encoding/decoding.
  • Efficient storage of symbol tables for various algorithms.
  • Improved compression ratios due to optimized data representation.
  • Flexibility to handle diverse data types.
**Google Search Description:** Learn Python dictionaries for data compression. This post explains dictionaries with examples of Huffman coding & Run-Length Encoding, improving your data compression skills.
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