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:

 
code_snippets/compress_zlib.lua

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

 
code_snippets/compress_zlib.lua

3. To decompress data, call decompress():

 
code_snippets/compress_zlib.lua

Create a zlib compressor instance.

Parameters:

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

Returns

a new zlib compressor instance (see zlib_compressor)

Return type

userdata

Example

 
code_snippets/compress_zlib.lua

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().

method compress(data)

Compress the specified data.

Parameters:

• data (string) — data to be compressed

Returns

compressed data

Return type

string

Example

 
code_snippets/compress_zlib.lua

method decompress(data)

Decompress the specified data.

• data (string) — data to be decompressed

Returns

decompressed data

Return type

string

Example

 
code_snippets/compress_zlib.lua

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

Example

 
code_snippets/compress_zlib.lua

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.