Range based compression and archiving library. Support for Zip, Tar (with .gz, .bz2, .xz), Zstandard, LZMA...
To use this package, run the following command in your project's root directory:
Put the following dependency into your project's dependences section:
A D library that handles compression / decompression and archiving.
Download, build, install
squiz-box, the easiest is to use the Dub package from the registry.
On Linux, you will need
On Windows, a compiled copy of these libraries is shipped with the package (only Windows 64 bit is supported).
Squiz-box is developped with Meson, which will build the C libraries if they are not found. If you want to use squiz-box in a Meson project, you can use it as a subproject.
To build, test on Linux:
meson builddir -Ddefault_library=static cd builddir ninja && ./squiz-test
To build test on Windows:
rem Visual Studio prompt is required rem A script is provided to help this (needs vswhere) win_env_vs.bat meson builddir -Ddefault_library=static cd builddir ninja && squiz-test.exe
Compression / decompression
The compression is designed to work with ranges, which makes it suitable for streaming and for transforming data from any kind of source to any kind of destination.
Algorithms and formats
An algorithm refers to the compression algorithm properly, and format refers to a header and a trailer attached to the compressed data that gives information about decompression parameters and integrity checking. A raw format refers to data compressed without such header and trailer and can be used inside an externally defined format (e.g. zip, 7z, ...).
|Algorithms||Squiz structs||Available formats|
|Deflate||Zlib, Gzip, Raw|
|LZMA1 (legacy compression)||Xz, Lzma (legacy format), Raw|
|LZMA (aka. LZMA2)||Xz, Raw|
In addition, the LZMA1 and LZMA compression also support additional filters that transorm the data before the compression stage in order to increase the compression ratio:
- higher compression of repetitive binary data such as audio PCM, RGB...
- BCJ (Branch/Call/Jump)
- higher compression of compiled executable
- available for a different architectures (X86, ARM, ...)
Algorithms are represented by structs that share a common interface.
Constructed objects from those structs carry parameters for compression / decompression
and can instantiate a stream (class that derives
SquizStream) that will carry the
necessary state as well as input and output buffer.
To process these algorithms and streams as D ranges, you use the
squiz function works for both compression and decompression and there are many
helpers built upon it (
See code examples below for usage.
Whenever possible, archving and de-archiving are implemented as the transformation of a range of file entries to a range of bytes. It is never required to have the full archive in memory at the same time, so it is possible to create or extract archives of dozens of giga-bytes with minimal memory foot print.
The following formats are supported:
- Tar (including
There is also WIP for 7z.
Archive update is not supported at this stage.
Compress data with zlib
import squiz_box; import std.range; const ubyte data = myDataToCompress(); auto algo = Deflate.init; // defaults to zlib format only(data) // InputRange of const(ubyte) (uncompressed) .squiz(algo) // also InputRange of const(ubyte) (deflated) .sendOverNetwork(); // the following code is equivalent only(data) .deflate() .sendOverNetwork();
Re-inflate data with zlib
import squiz_box; import std.array; const data = receiveFromNetwork() // InputRange of const(ubyte) .inflate() .join(); // const(ubyte)
Create an archive from a directory
Zip a directory:
import squiz_box; import std.algorithm; import std.file; const root = buildNormalizedPath(someDir); dirEntries(root, SpanMode.breadth, false) .filter!(e => !e.isDir) .map!(e => fileEntry(e.name, root, null)) // range of FileEntry .createZipArchive() // range of bytes .writeBinaryFile("some-dir.zip");
.tar.xz file from a directory (with little bit more control):
import squiz_box; import std.algorithm; import std.file; import std.path; const root = squizBoxDir; // prefix all files path in the archive // don't forget the trailing '/'! const prefix = "squiz-box-12.5/"; const exclusion = [".git", ".dub", ".vscode", "libsquiz-box.a", "build"]; dirEntries(root, SpanMode.breadth, false) .filter!(e => !e.isDir) .filter!(e => !exclusion.any!(ex => e.name.canFind(ex))) .map!(e => fileEntry(e.name, root, prefix)) .createTarArchive() .compressXz() .writeBinaryFile("squiz-box-12.5.tar.xz");
Extract an archive into a directory
import squiz_box; const archive = "my-archive.tar.gz"; const extractionSite = "some-dir"; mkdir(extractionSite); readBinaryFile(archive) .inflateGz() .readTarArchive() .each!(e => e.extractTo(extractionSite));
Full control over the streaming process
Sometimes, D ranges are not practical. Think of a receiver thread that receives data, compresses it and sends it over network with low latency. You will not wait to receive the full data before to start streaming, and a D range is probably not well suited to receive the data from a different thread. In that situation you can use the streaming API directly.
The following code gives the spirit of it.
import squiz_box; // Zstandard is a good fit for low latency streaming auto algo = CompressZstd.init; auto stream = algo.initialize(); // repeat for as many chunks of memory as necessary stream.input = dataChunk; stream.output = buffer; auto streamEnded = algo.process(stream, No.lastChunk); // send buffer content out // at some point we send the last chunk and receive notification that the stream is done. // we can reset the stream and keep the allocated resources for a new round algo.reset(stream); // more streaming... // finally we can release the resources algo.end(stream);
- Registered by Remi Thebault
- 0.1.0 released a month ago
- Copyright (C) 2022, Rémi Thebault