Submodule compress.zlib

The compress.zlib submodule provides the ability to compress and decompress data using the zlib algorithm. You can use the zlib compressor as follows:

1. Create a compressor instance using the compress.zlib.new() function:

    
   local zlib_compressor = require('compress.zlib').new()-- or --local zlib_compressor = require('compress').zlib.new()

   Optionally, you can pass compression options (zlib_opts) specific for zlib:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

2. To compress the specified data, use the compress() method:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

3. To decompress data, call decompress():

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

Below is a list of the compress.zlib functions and objects.

Create a zlib compressor instance.

Parameters:

• zlib_opts (table) — zlib compression options (see zlib_opts)

Returns

a new zlib compressor instance (see zlib_compressor)

Return type

userdata

Example:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

A compressor instance that exposes the API for compressing and decompressing data using the zlib algorithm. To create the zlib compressor, call compress.zlib.new().

Compress the specified data.

Parameters:

• data (string) — data to be compressed

Returns

compressed data

Return type

string

Example:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

Decompress the specified data.

Parameters:

• data (string) — data to be decompressed

Returns

decompressed data

Return type

string

Example:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

Configuration options of the zlib_compressor. These options can be passed to the compress.zlib.new() function.

Example:

 
local zlib_compressor = require('compress.zlib').new({    level = 5,    mem_level = 5,    strategy = 'filtered'})compressed_data = zlib_compressor:compress('Hello world!')decompressed_data = zlib_compressor:decompress(compressed_data)print(decompressed_data)

Specifies the zlib compression level that enables you to adjust the compression ratio and speed. The lower level improves the compression speed at the cost of compression ratio.

• Default: 6
• Minimum: 0 (no compression)
• Maximum: 9

Specifies how much memory is allocated for the zlib compressor. The larger value improves the compression speed and ratio.

• Default: 8
• Minimum: 1
• Maximum: 9

Specifies the compression strategy. The possible values:

• default - for normal data.
• huffman_only - forces Huffman encoding only (no string match). The fastest compression algorithm but not very effective in compression for most of the data.
• filtered - for data produced by a filter or predictor. Filtered data consists mostly of small values with a somewhat random distribution. This compression algorithm is tuned to compress them better.
• rle - limits match distances to one (run-length encoding). rle is designed to be almost as fast as huffman_only but gives better compression for PNG image data.
• fixed - prevents the use of dynamic Huffman codes and provides a simpler decoder for special applications.