def _is_zero_filled(self, block): return all(byte == 0 for byte in block)
import discipline_zerozip
class DisciplineZerozip: def __init__(self, block_size=4096): self.block_size = block_size
# Iterate through the compressed data while len(compressed_data) > 0: # Read the block type (zero-filled or non-zero-filled) block_type = struct.unpack_from('B', compressed_data)[0] compressed_data = compressed_data[1:] discipline zerozip
import struct
# Compress the data using Discipline Zerozip compressed_data = discipline_zerozip.compress(data)
def compress(self, data): compressed_data = bytearray() def _is_zero_filled(self, block): return all(byte == 0 for
# Preprocess the data into fixed-size blocks for i in range(0, len(data), self.block_size): block = data[i:i + self.block_size]
assert data == decompressed_data The Discipline Zerozip algorithm can be implemented in a variety of programming languages. Here is a sample implementation in Python:
def _compress_zero_block(self, block): # Compress the zero-filled block using a simple header header = struct.pack('B', 0) # Block type (zero-filled) header += struct.pack('H', len(block)) # Block size return header discipline zerozip
# Decompress the data decompressed_data = discipline_zerozip.decompress(compressed_data)
# Detect zero-filled blocks if self._is_zero_filled(block): compressed_data.extend(self._compress_zero_block(block)) else: compressed_data.extend(self._compress_non_zero_block(block))
def _compress_non_zero_block(self, block): # Compress the non-zero-filled block using RLE and entropy coding compressed_block = bytearray() i = 0 while i < len(block): count = 1 while i + 1 < len(block) and block[i] == block[i + 1]: i += 1 count += 1 compressed_block.extend(struct.pack('B', count)) compressed_block.extend(bytes([block[i]])) i += 1 return bytes(compressed_block)