Metadata-Version: 2.1
Name: javaobj-py3
Version: 0.4.0
Summary: Module for serializing and de-serializing Java objects.
Home-page: https://github.com/tcalmant/python-javaobj
Author: Volodymyr Buell
Author-email: vbuell@gmail.com
Maintainer: Thomas Calmant
Maintainer-email: thomas.calmant@gmail.com
License: Apache License 2.0
Keywords: python java marshalling serialization
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Software Development :: Libraries :: Python Modules

javaobj-py3
###########

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*python-javaobj* is a python library that provides functions for reading and
writing (writing is WIP currently) Java objects serialized or will be
deserialized by ``ObjectOutputStream``. This form of object representation is a
standard data interchange format in Java world.

The ``javaobj`` module exposes an API familiar to users of the standard library
``marshal``, ``pickle`` and ``json`` modules.

About this repository
=====================

This project is a fork of *python-javaobj* by Volodymyr Buell, originally from
`Google Code <http://code.google.com/p/python-javaobj/>`_ and now hosted on
`GitHub <https://github.com/vbuell/python-javaobj>`_.

This fork intends to work both on Python 2.7 and Python 3.4+.

Compatibility Warnings
======================

New implementation of the parser
--------------------------------

:Implementations: ``v1``, ``v2``
:Version: ``0.4.0+``

Since version 0.4.0, two implementations of the parser are available:

* ``v1``: the *classic* implementation of ``javaobj``, with a work in progress
  implementation of a writer.
* ``v2``: the *new* implementation, which is a port of the Java project
  `jdeserialize <https://github.com/frohoff/jdeserialize/>`_,
  with support of the object transformer (with a new API) and of the ``numpy``
  arrays loading.

You can use the ``v1`` parser to ensure that the behaviour of your scripts
doesn't change and to keep the ability to write down files.

You can use the ``v2`` parser for new developments
*which won't require marshalling* and as a *fallback* if the ``v1``
fails to parse a file.

Object transformers V1
----------------------

:Implementations: ``v1``
:Version: ``0.2.0+``

As of version 0.2.0, the notion of *object transformer* from the original
project as been replaced by an *object creator*.

The *object creator* is called before the deserialization.
This allows to store the reference of the converted object before deserializing
it, and avoids a mismatch between the referenced object and the transformed one.

Object transformers V2
----------------------

:Implementations: ``v2``
:Version: ``0.4.0+``

The ``v2`` implementation provides a new API for the object transformers.
Please look at the *Usage (V2)* section in this file.

Bytes arrays
------------

:Implementations: ``v1``
:Version: ``0.2.3+``

As of version 0.2.3, bytes arrays are loaded as a ``bytes`` object instead of
an array of integers.


Features
========

* Java object instance un-marshalling
* Java classes un-marshalling
* Primitive values un-marshalling
* Automatic conversion of Java Collections to python ones
  (``HashMap`` => ``dict``, ``ArrayList`` => ``list``, etc.)
* Basic marshalling of simple Java objects (``v1`` implementation only)

Requirements
============

* Python >= 2.7 or Python >= 3.4
* ``enum34`` and ``typing`` when using Python <= 3.4 (installable with ``pip``)
* Maven 2+ (for building test data of serialized objects.
  You can skip it if you do not plan to run ``tests.py``)

Usage (V1 implementation)
=========================

Un-marshalling of Java serialised object:

.. code-block:: python

   import javaobj

   with open("obj5.ser", "rb") as fd:
       jobj = fd.read()

   pobj = javaobj.loads(jobj)
   print(pobj)

Or, you can use ``JavaObjectUnmarshaller`` object directly:

.. code-block:: python

   import javaobj

   with open("objCollections.ser", "rb") as fd:
       marshaller = javaobj.JavaObjectUnmarshaller(fd)
       pobj = marshaller.readObject()

       print(pobj.value, "should be", 17)
       print(pobj.next, "should be", True)

       pobj = marshaller.readObject()


**Note:** The objects and methods provided by ``javaobj`` module are shortcuts
to the ``javaobj.v1`` package, for Compatibility purpose.
It is **recommended** to explicitly import methods and classes from the ``v1``
(or ``v2``) package when writing new code, in order to be sure that your code
won't need import updates in the future.


Usage (V2 implementation)
=========================

The following methods are provided by the ``javaobj.v2`` package:

* ``load(fd, *transformers, use_numpy_arrays=False)``:
  Parses the content of the given file descriptor, opened in binary mode (`rb`).
  The method accepts a list of custom object transformers. The default object
  transformer is always added to the list.

  The ``use_numpy_arrays`` flag indicates that the arrays of primitive type
  elements must be loaded using ``numpy`` (if available) instead of using the
  standard parsing technic.

* ``loads(bytes, *transformers, use_numpy_arrays=False)``:
  This the a shortcut to the ``load()`` method, providing it the binary data
  using a ``BytesIO`` object.

**Note:** The V2 parser doesn't have the marshalling capability.

Sample usage:

.. code-block:: python

   import javaobj.v2 as javaobj

   with open("obj5.ser", "rb") as fd:
       pobj = javaobj.load(fd)

   print(pobj.dump())


Object Transformer
-------------------

An object transformer can be called during the parsing of a Java object
instance or while loading an array.

The Java object instance parsing works in two main steps:

1. The transformer is called to create an instance of a bean that inherits
   ``JavaInstance``.
2. The latter bean is then called:

   * When the object is written with a custom block data
   * After the fields and annotations have been parsed, to update the content of
     the Python bean.

Here is an example for a Java ``HashMap`` object. You can look at the code of
the ``javaobj.v2.transformer`` module to see the whole implementation.

.. code-block:: python

   class JavaMap(dict, javaobj.v2.beans.JavaInstance):
       """
       Inherits from dict for Python usage, JavaInstance for parsing purpose
       """
       def __init__(self):
           # Don't forget to call both constructors
           dict.__init__(self)
           JavaInstance.__init__(self)

      def load_from_blockdata(self, parser, reader, indent=0):
        """
        Reads content stored in a block data.

        This method is called only if the class description has both the
        ``SC_EXTERNALIZABLE`` and ``SC_BLOCK_DATA`` flags set.

        The stream parsing will stop and fail if this method returns False.

        :param parser: The JavaStreamParser in use
        :param reader: The underlying data stream reader
        :param indent: Indentation to use in logs
        :return: True on success, False on error
        """
        # This kind of class is not supposed to have the SC_BLOCK_DATA flag set
        return False

       def load_from_instance(self, indent=0):
           # type: (int) -> bool
           """
           Load content from the parsed instance object.

           This method is called after the block data (if any), the fields and
           the annotations have been loaded.

           :param indent: Indentation to use while logging
           :return: True on success (currently ignored)
           """
           # Maps have their content in their annotations
           for cd, annotations in self.annotations.items():
               # Annotations are associated to their definition class
               if cd.name == "java.util.HashMap":
                   # We are in the annotation created by the handled class
                   # Group annotation elements 2 by 2
                   # (storage is: key, value, key, value, ...)
                   args = [iter(annotations[1:])] * 2
                   for key, value in zip(*args):
                       self[key] = value

                   # Job done
                   return True

           # Couldn't load the data
           return False

   class MapObjectTransformer(javaobj.v2.api.ObjectTransformer):
       """
       Creates a JavaInstance object with custom loading methods for the
       classes it can handle
       """
       def create_instance(self, classdesc):
           # type: (JavaClassDesc) -> Optional[JavaInstance]
           """
           Transforms a parsed Java object into a Python object

           :param classdesc: The description of a Java class
           :return: The Python form of the object, or the original JavaObject
           """
           if classdesc.name == "java.util.HashMap":
               # We can handle this class description
               return JavaMap()
           else:
               # Return None if the class is not handled
               return None


