================

python-zstandard

================

This project provides Python bindings for interfacing with the

`Zstandard <http://www.zstd.net>`_ compression library. A C extension

and CFFI interface are provided.

The primary goal of the project is to provide a rich interface to the

underlying C API through a Pythonic interface while not sacrificing

performance. This means exposing most of the features and flexibility

of the C API while not sacrificing usability or safety that Python provides.

https://github.com/indygreg/python-zstandard.

|  |ci-status| |win-ci-status|

Requirements

============

Installing

==========

This package is uploaded to PyPI at https://pypi.python.org/pypi/zstandard.

So, to install this package::

   $ pip install zstandard

Binary wheels are made available for some platforms. If you need to

install from a source distribution, all you should need is a working C

compiler and the Python development headers/libraries. On many Linux

distributions, you can install a ``python-dev`` or ``python-devel``

package to provide these dependencies.

Packages are also uploaded to Anaconda Cloud at

https://anaconda.org/indygreg/zstandard. See that URL for how to install

this package with ``conda``.

Performance

===========

API

===

are documented in the sections below.

.. note::

   The documentation in this section makes references to various zstd

ZstdCompressor

--------------

The ``ZstdCompressor`` class provides an interface for performing

Each instance is associated with parameters that control compression

behavior. These come from the following named arguments (all optional):

level

   Integer compression level. Valid values are between 1 and 22.

dict_data

   Compression dictionary to use.

   Note: When using dictionary data and ``compress()`` is called multiple

compression_params

write_checksum

   Whether a 4 byte checksum should be written with the compressed data.

   Defaults to False. If True, the decompressor can verify that decompressed

   data matches the original input data.

write_content_size

   Whether the size of the uncompressed data will be written into the

   written if the compressor knows the size of the input data. This is

write_dict_id

   Whether to write the dictionary ID into the compressed data.

   Defaults to True. The dictionary ID is only written if a dictionary

   is being used.

threads

   Enables and sets the number of threads to use for multi-threaded compression

   operations. Defaults to 0, which means to use single-threaded compression.

   Negative values will resolve to the number of logical CPUs in the system.

   Read below for more info on multi-threaded compression. This argument only

   controls thread count for operations that operate on individual pieces of

   data. APIs that spawn multiple threads for working on multiple pieces of

   data have their own ``threads`` argument.

Unless specified otherwise, assume that no two methods of ``ZstdCompressor``

instances can be called from multiple Python threads simultaneously. In other

words, assume instances are not thread safe unless stated otherwise.

Simple API

^^^^^^^^^^

``compress(data)`` compresses and returns data as a one-shot operation.::

   cctx = zstd.ZstdCompressor()

   compressed = cctx.compress(b'data to compress')

The ``data`` argument can be any object that implements the *buffer protocol*.

Streaming Input API

^^^^^^^^^^^^^^^^^^^

data into a compressor.::

   cctx = zstd.ZstdCompressor(level=10)

       compressor.write(b'chunk 0')

       compressor.write(b'chunk 1')

       ...

compressed data is available, ``write()`` will be called with the compressed

data as its argument. Many common Python types implement ``write()``, including

open file handles and ``io.BytesIO``.

A ``flush()`` method can be called to evict whatever data remains within the

compressor's internal state into the output object. This may result in 0 or

more ``write()`` calls to the output object.

Both ``write()`` and ``flush()`` return the number of bytes written to the

object's ``write()``. In many cases, small inputs do not accumulate enough

data to cause a write and ``write()`` will return ``0``.

If the size of the data being fed to this streaming compressor is known,

you can declare it before compression begins::

   cctx = zstd.ZstdCompressor()

       compressor.write(chunk0)

       compressor.write(chunk1)

       ...

Declaring the size of the source data allows compression parameters to

be tuned. And if ``write_content_size`` is used, it also results in the

content size being written into the frame header of the output data.

The size of chunks being ``write()`` to the destination can be specified::

    cctx = zstd.ZstdCompressor()

        ...

To see how much memory is being used by the streaming compressor::

    cctx = zstd.ZstdCompressor()

        ...

        byte_size = compressor.memory_size()

Streaming Output API

^^^^^^^^^^^^^^^^^^^^

   cctx = zstd.ZstdCompressor()

        # Do something with emitted data.

Uncompressed data is fetched from the source either by calling ``read(size)``

or by fetching a slice of data from the object directly (in the case where

the buffer protocol is being used). The returned iterator consists of chunks

of compressed data.

If reading from the source via ``read()``, ``read()`` will be called until

it raises or returns an empty bytes (``b''``). It is perfectly valid for

the source to deliver fewer bytes than were what requested by ``read(size)``.

declaring the size of the input stream::

    cctx = zstd.ZstdCompressor()

        pass

You can also control the size that data is ``read()`` from the source and

the ideal size of output chunks::

    cctx = zstd.ZstdCompressor()

        pass

Stream Copying API

^^^^^^^^^^^^^^^^^^

``copy_stream(ifh, ofh)`` can be used to copy data between 2 streams while

compressing it.::

   cctx = zstd.ZstdCompressor()

   cctx.copy_stream(ifh, ofh)

For example, say you wish to compress a file::

   cctx = zstd.ZstdCompressor()

   with open(input_path, 'rb') as ifh, open(output_path, 'wb') as ofh:

       cctx.copy_stream(ifh, ofh)

It is also possible to declare the size of the source stream::

   cctx = zstd.ZstdCompressor()

   cctx.copy_stream(ifh, ofh, size=len_of_input)

You can also specify how large the chunks that are ``read()`` and ``write()``

from and to the streams::

   cctx = zstd.ZstdCompressor()

   cctx.copy_stream(ifh, ofh, read_size=32768, write_size=16384)

The stream copier returns a 2-tuple of bytes read and written::

   cctx = zstd.ZstdCompressor()

   read_count, write_count = cctx.copy_stream(ifh, ofh)

Compressor API

^^^^^^^^^^^^^^

``compressobj()`` returns an object that exposes ``compress(data)`` and

``flush()`` methods. Each returns compressed data or an empty bytes.

The purpose of ``compressobj()`` is to provide an API-compatible interface

swap in different compressor objects while using the same API.

``flush()`` accepts an optional argument indicating how to end the stream.

``zstd.COMPRESSOBJ_FLUSH_FINISH`` (the default) ends the compression stream.

Once this type of flush is performed, ``compress()`` and ``flush()`` can

no longer be called. This type of flush **must** be called to end the

compression context. If not called, returned data may be incomplete.

A ``zstd.COMPRESSOBJ_FLUSH_BLOCK`` argument to ``flush()`` will flush a

zstd block. Flushes of this type can be performed multiple times. The next

call to ``compress()`` will begin a new zstd block.

Here is how this API should be used::

   cctx = zstd.ZstdCompressor()

   cobj = cctx.compressobj()

   data = cobj.compress(b'raw input 0')

   data = cobj.compress(b'raw input 1')

   data = cobj.flush()

Or to flush blocks::

   cctx.zstd.ZstdCompressor()

   cobj = cctx.compressobj()

   data = cobj.compress(b'chunk in first block')

   data = cobj.flush(zstd.COMPRESSOBJ_FLUSH_BLOCK)

   data = cobj.compress(b'chunk in second block')

   data = cobj.flush()

For best performance results, keep input chunks under 256KB. This avoids

extra allocations for a large output object.

It is possible to declare the input size of the data that will be fed into

the compressor::

   cctx = zstd.ZstdCompressor()

   cobj = cctx.compressobj(size=6)

   data = cobj.compress(b'foobar')

   data = cobj.flush()

Batch Compression API

^^^^^^^^^^^^^^^^^^^^^

(Experimental. Not yet supported in CFFI bindings.)

``multi_compress_to_buffer(data, [threads=0])`` performs compression of multiple

inputs as a single operation.

Data to be compressed can be passed as a ``BufferWithSegmentsCollection``, a

``BufferWithSegments``, or a list containing byte like objects. Each element of

the container will be compressed individually using the configured parameters

on the ``ZstdCompressor`` instance.

The ``threads`` argument controls how many threads to use for compression. The

default is ``0`` which means to use a single thread. Negative values use the

number of logical CPUs in the machine.

The function returns a ``BufferWithSegmentsCollection``. This type represents

N discrete memory allocations, eaching holding 1 or more compressed frames.

Output data is written to shared memory buffers. This means that unlike

regular Python objects, a reference to *any* object within the collection

keeps the shared buffer and therefore memory backing it alive. This can have

undesirable effects on process memory usage.

The API and behavior of this function is experimental and will likely change.

Known deficiencies include:

* If asked to use multiple threads, it will always spawn that many threads,

  even if the input is too small to use them. It should automatically lower

  the thread count when the extra threads would just add overhead.

* The buffer allocation strategy is fixed. There is room to make it dynamic,

  perhaps even to allow one output buffer per input, facilitating a variation

  of the API to return a list without the adverse effects of shared memory

  buffers.

ZstdDecompressor

----------------

The ``ZstdDecompressor`` class provides an interface for performing

Each instance is associated with parameters that control decompression. These

come from the following named arguments (all optional):

dict_data

   Compression dictionary to use.

The interface of this class is very similar to ``ZstdCompressor`` (by design).

Unless specified otherwise, assume that no two methods of ``ZstdDecompressor``

instances can be called from multiple Python threads simultaneously. In other

words, assume instances are not thread safe unless stated otherwise.