Metadata-Version: 1.1
Name: property-manager
Version: 2.3.1
Summary: Useful property variants for Python programming (required properties, writable properties, cached properties, etc)
Home-page: https://property-manager.readthedocs.org
Author: Peter Odding
Author-email: peter@peterodding.com
License: MIT
Description: property-manager: Useful property variants for Python programming
        =================================================================
        
        .. image:: https://travis-ci.org/xolox/python-property-manager.svg?branch=master
           :target: https://travis-ci.org/xolox/python-property-manager
        
        .. image:: https://coveralls.io/repos/xolox/python-property-manager/badge.png?branch=master
           :target: https://coveralls.io/r/xolox/python-property-manager?branch=master
        
        The `property-manager` package defines several custom property_ variants for
        Python programming including required properties, writable properties, cached
        properties, etc. It's currently tested on Python 2.6, 2.7, 3.4, 3.5, 3.6 and
        PyPy. For usage instructions please refer to the documentation_.
        
        .. contents::
           :local:
        
        Status
        ------
        
        The `property-manager` package came into existence as a submodule of my
        executor_ package where I wanted to define classes with a lot of properties
        that had a default value which was computed on demand but also needed to
        support assignment to easily override the default value.
        
        Since I created that module I'd wanted to re-use it in a couple of other
        projects I was working on, but adding an `executor` dependency just for the
        `property_manager` submodule felt kind of ugly.
        
        This is when I decided that it was time for the `property-manager` package to
        be created. When I extracted the submodule from `executor` I significantly
        changed its implementation (making the code more robust and flexible) and
        improved the tests, documentation and coverage in the process.
        
        Installation
        ------------
        
        The `property-manager` package is available on PyPI_ which means installation
        should be as simple as:
        
        .. code-block:: sh
        
           $ pip install property-manager
        
        There's actually a multitude of ways to install Python packages (e.g. the `per
        user site-packages directory`_, `virtual environments`_ or just installing
        system wide) and I have no intention of getting into that discussion here, so
        if this intimidates you then read up on your options before returning to these
        instructions ;-).
        
        Usage
        -----
        
        This section shows how to use the most useful property subclasses. Please refer
        to the documentation_ for more detailed information.
        
        .. contents::
           :local:
        
        Writable properties
        ~~~~~~~~~~~~~~~~~~~
        
        Writable properties with a computed default value are easy to create using the
        writable_property_ decorator:
        
        .. code-block:: python
        
           from random import random
           from property_manager import writable_property
        
           class WritablePropertyDemo(object):
        
               @writable_property
               def change_me(self):
                   return random()
        
        First let's see how the computed default value behaves:
        
        >>> instance = WritablePropertyDemo()
        >>> print(instance.change_me)
        0.13692489329941815
        >>> print(instance.change_me)
        0.8664002331885933
        
        As you can see the value is recomputed each time. Now we'll assign it a value:
        
        >>> instance.change_me = 42
        >>> print(instance.change_me)
        42
        
        From this point onwards `change_me` will be the number 42_ and it's impossible
        to revert back to the computed value:
        
        >>> delattr(instance, 'change_me')
        Traceback (most recent call last):
          File "property_manager/__init__.py", line 584, in __delete__
            raise AttributeError(msg % (obj.__class__.__name__, self.__name__))
        AttributeError: 'WritablePropertyDemo' object attribute 'change_me' is read-only
        
        If you're looking for a property that supports both assignment and deletion
        (clearing the assigned value) you can use mutable_property_.
        
        Required properties
        ~~~~~~~~~~~~~~~~~~~
        
        The required_property_ decorator can be used to create required properties:
        
        .. code-block:: python
        
           from property_manager import PropertyManager, required_property
        
           class RequiredPropertyDemo(PropertyManager):
        
               @required_property
               def important(self):
                   """A very important attribute."""
        
        What does it mean for a property to be required? Let's create an instance of
        the class and find out:
        
        >>> instance = RequiredPropertyDemo()
        Traceback (most recent call last):
          File "property_manager/__init__.py", line 131, in __init__
            raise TypeError("%s (%s)" % (msg, concatenate(missing_properties)))
        TypeError: missing 1 required argument (important)
        
        So the constructor of the class raises an exception when the property hasn't
        been given a value. We can give the property a value by providing keyword
        arguments to the constructor:
        
        >>> instance = RequiredPropertyDemo(important=42)
        >>> print(instance)
        RequiredPropertyDemo(important=42)
        
        We can also assign a new value to the property:
        
        >>> instance.important = 13
        >>> print(instance)
        RequiredPropertyDemo(important=13)
        
        Cached properties
        ~~~~~~~~~~~~~~~~~
        
        Two kinds of cached properties are supported, we'll show both here:
        
        .. code-block:: python
        
           from random import random
           from property_manager import cached_property, lazy_property
        
           class CachedPropertyDemo(object):
        
               @cached_property
               def expensive(self):
                   print("Calculating expensive property ..")
                   return random()
        
               @lazy_property
               def non_idempotent(self):
                   print("Calculating non-idempotent property ..")
                   return random()
        
        The properties created by the cached_property_ decorator compute the
        property's value on demand and cache the result:
        
        >>> instance = CachedPropertyDemo()
        >>> print(instance.expensive)
        Calculating expensive property ..
        0.763863180683
        >>> print(instance.expensive)
        0.763863180683
        
        The property's cached value can be invalidated in order to recompute its value:
        
        >>> del instance.expensive
        >>> print(instance.expensive)
        Calculating expensive property ..
        0.396322737214
        >>> print(instance.expensive)
        0.396322737214
        
        Now that you understand cached_property_, explaining lazy_property_ is very
        simple: It simply doesn't support invalidation of cached values! Here's how
        that works in practice:
        
        >>> instance.non_idempotent
        Calculating non-idempotent property ..
        0.27632566561900895
        >>> instance.non_idempotent
        0.27632566561900895
        >>> del instance.non_idempotent
        Traceback (most recent call last):
          File "property_manager/__init__.py", line 499, in __delete__
            raise AttributeError(msg % (obj.__class__.__name__, self.__name__))
        AttributeError: 'CachedPropertyDemo' object attribute 'non_idempotent' is read-only
        >>> instance.non_idempotent
        0.27632566561900895
        
        Properties based on environment variables
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        The constructor of the custom_property_ class (and its subclasses) accepts the
        keyword argument `environment_variable` which can be provided to get the
        property's value from the environment:
        
        .. code-block:: python
        
           from random import random
           from property_manager import mutable_property
        
           class EnvironmentPropertyDemo(object):
        
               @mutable_property(environment_variable='WHATEVER_YOU_WANT')
               def environment_based(self):
                   return 'some-default-value'
        
        By default the property's value is computed as expected:
        
        >>> instance = EnvironmentPropertyDemo()
        >>> print(instance.environment_based)
        some-default-value
        
        When the environment variable is set it overrides the computed value:
        
        >>> os.environ['WHATEVER_YOU_WANT'] = '42'
        >>> print(instance.environment_based)
        42
        
        Assigning a value to the property overrides the value from the environment:
        
        >>> instance.environment_based = '13'
        >>> print(instance.environment_based)
        13
        
        Deleting the property clears the assigned value so that the property falls back
        to the environment:
        
        >>> delattr(instance, 'environment_based')
        >>> print(instance.environment_based)
        42
        
        If we now clear the environment variable as well then the property falls back
        to the computed value:
        
        >>> os.environ.pop('WHATEVER_YOU_WANT')
        '42'
        >>> print(instance.environment_based)
        some-default-value
        
        Support for setters and deleters
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        All of the custom property classes support setters and deleters just like
        Python's ``property`` decorator does.
        
        The `PropertyManager` class
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        When you define a class that inherits from the PropertyManager_ class the
        following behavior is made available to your class:
        
        - Required properties raise an exception if they're not set.
        
        - The values of writable properties can be set by passing
          keyword arguments to the constructor of your class.
        
        - The `repr()` of your objects will render the name of the class and the names
          and values of all properties. Individual properties can easily be excluded
          from the `repr()` output.
        
        - The `clear_cached_properties()`_ method can be used to invalidate the cached
          values of all cached properties at once.
        
        Additionally you can use the property_manager.sphinx_ module as a Sphinx
        extension to automatically generate boilerplate documentation that provides an
        overview of base classes, properties, public methods and special methods.
        
        Similar projects
        ----------------
        
        The Python Package Index contains quite a few packages that provide custom
        properties with similar semantics:
        
        `cached-property <https://pypi.python.org/pypi/cached-property>`_
         My personal favorite until I wrote my own :-). This package provides several
         cached property variants. It supports threading and time based cache
         invalidation which `property-manager` doesn't support.
        
        `lazy-property <https://pypi.python.org/pypi/lazy-property>`_
         This package provides two cached property variants: a read only property and
         a writable property. Both variants cache computed values indefinitely.
        
        `memoized-property <https://pypi.python.org/pypi/memoized-property>`_
         This package provides a single property variant which simply caches computed
         values indefinitely.
        
        `property-caching <https://pypi.python.org/pypi/property-caching>`_
         This package provides several cached property variants supporting class
         properties, object properties and cache invalidation.
        
        `propertylib <https://pypi.python.org/pypi/propertylib>`_
         This package uses metaclasses to implement an alternative syntax for defining
         computed properties. It defines several property variants with semantics that
         are similar to those defined by the `property-manager` package.
        
        `rwproperty <https://pypi.python.org/pypi/rwproperty>`_
         This package implements computed, writable properties using an alternative
         syntax to define the properties.
        
        Distinguishing features
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        Despite all of the existing Python packages discussed above I decided to create
        and publish the `property-manager` package because it was fun to get to know
        Python's `descriptor protocol`_ and I had several features in mind I couldn't
        find anywhere else:
        
        - A superclass that sets writable properties based on constructor arguments.
        
        - A superclass that understands required properties and raises a clear
          exception if a required property is not properly initialized.
        
        - Clear disambiguation between lazy properties (whose computed value is cached
          but cannot be invalidated because it would compromise internal state) and
          cached properties (whose computed value is cached but can be invalidated to
          compute a fresh value).
        
        - An easy way to quickly invalidate all cached properties of an object.
        
        - An easy way to change the semantics of custom properties, e.g. what if the
          user wants a writable cached property? With `property-manager` it is trivial
          to define new property variants by combining existing semantics:
        
          .. code-block:: python
        
             from property_manager import cached_property
        
             class WritableCachedPropertyDemo(object):
        
                 @cached_property(writable=True)
                 def expensive_overridable_attribute(self):
                     """Expensive calculations go here."""
        
          The example above creates a new anonymous class and then immediately uses
          that to decorate the method. We could have given the class a name though:
        
          .. code-block:: python
        
             from property_manager import cached_property
        
             writable_cached_property = cached_property(writable=True)
        
             class WritableCachedPropertyDemo(object):
        
                 @writable_cached_property
                 def expensive_overridable_attribute(self):
                     """Expensive calculations go here."""
        
          By giving the new property variant a name it can be reused. We can go one
          step further and properly document the new property variant:
        
          .. code-block:: python
        
             from property_manager import cached_property
        
             class writable_cached_property(cached_property):
        
                 """A cached property that supports assignment."""
        
                 writable = True
        
             class WritableCachedPropertyDemo(object):
        
                 @writable_cached_property
                 def expensive_overridable_attribute(self):
                     """Expensive calculations go here."""
        
          I've used computed properties for years in Python and over those years I've
          learned that different Python projects have different requirements from
          custom property variants. Defining every possible permutation up front is
          madness, but I think that the flexibility with which the `property-manager`
          package enables adaptation gets a long way. This was the one thing that
          bothered me the most about all of the other Python packages that implement
          property variants: They are not easily adapted to unanticipated use cases.
        
        Contact
        -------
        
        The latest version of `property-manager` is available on PyPI_ and GitHub_. The
        documentation is hosted on `Read the Docs`_ and includes a changelog_. For bug
        reports please create an issue on GitHub_. If you have questions, suggestions,
        etc. feel free to send me an e-mail at `peter@peterodding.com`_.
        
        License
        -------
        
        This software is licensed under the `MIT license`_.
        
        © 2018 Peter Odding.
        
        
        .. External references:
        .. _42: https://en.wikipedia.org/wiki/42_(number)#The_Hitchhiker.27s_Guide_to_the_Galaxy
        .. _cached_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.cached_property
        .. _changelog: https://property-manager.readthedocs.org/en/latest/changelog.html
        .. _clear_cached_properties(): https://property-manager.readthedocs.org/en/latest/api.html#property_manager.PropertyManager.clear_cached_properties
        .. _custom_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.custom_property
        .. _descriptor protocol: https://docs.python.org/2/howto/descriptor.html
        .. _documentation: https://property-manager.readthedocs.org
        .. _executor: https://executor.readthedocs.org/en/latest/
        .. _GitHub: https://github.com/xolox/python-property-manager
        .. _lazy_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.lazy_property
        .. _MIT license: http://en.wikipedia.org/wiki/MIT_License
        .. _mutable_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.mutable_property
        .. _per user site-packages directory: https://www.python.org/dev/peps/pep-0370/
        .. _peter@peterodding.com: peter@peterodding.com
        .. _property: https://docs.python.org/2/library/functions.html#property
        .. _property_manager.sphinx: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.sphinx
        .. _PropertyManager: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.PropertyManager
        .. _PyPI: https://pypi.python.org/pypi/property-manager
        .. _Read the Docs: https://property-manager.readthedocs.org
        .. _required_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.required_property
        .. _virtual environments: http://docs.python-guide.org/en/latest/dev/virtualenvs/
        .. _writable_property: https://property-manager.readthedocs.org/en/latest/api.html#property_manager.writable_property
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Documentation :: Sphinx
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Documentation
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
