Metadata-Version: 2.1
Name: Py-Meta-Utils
Version: 0.7.8
Summary: Metaclass utilities for Python
Home-page: https://github.com/briancappello/py-meta-utils
Author: Brian Cappello
License: MIT
Description: # Py Meta Utils
        
        ## Useful Links
        
        * [Official Documentation on Read The Docs](http://py-meta-utils.readthedocs.io/)
        * [Source Code on GitHub](https://github.com/briancappello/py-meta-utils)
        * [PyPI](https://pypi.org/project/Py-Meta-Utils/)
        
        ## The Meta Options Factory Pattern as a library, and related metaclass utilities
        
        When you as a library or framework author want your end users to be able to write something like this:
        
        ```python
        class SomeClass(YourBaseClass):
            class Meta:
                option1 = 'value1'
                option2 = 'value2'
                option3 = 'value3'
        ```
        
        And you need a way to define each of these option/value pairs, and a way to "attach" custom behavior to them (ie, code that manipulates code using a custom `metaclass` on `YourBaseClass`). There are a couple common-ish patterns to accomplish this. Django and Graphene have one way, Marshmallow another, and Factory Boy another (and no doubt probably others). But Factory Boy's implementation is by far the most powerful and flexible one I've come across.
        
        I discovered this pattern while reading the source code of [factory_boy](https://factoryboy.readthedocs.io/en/latest/) (specifically, [this file](https://github.com/FactoryBoy/factory_boy/blob/master/factory/base.py)).
        
        And I decided to extract it and turn it into a reusable library. In the process, I ended up refactoring a few things and adding a couple niceties to improve upon its usage.
        
        Let's take a look at a silly example to allow your end users to be able to optionally enable logging of the actions of a class from a library you're writing:
        
        ```python
        class EndUserClass(YourLoggableService):
            class Meta:
                debug: bool = True
                verbosity: int = 2
                log_destination: str = '/tmp/end-user-class.log'
        ```
        
        The first step is to define your custom [MetaOption](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.MetaOption) subclasses:
        
        - All that's absolutely required to implement is the constructor and its `name` argument. That said, it's recommended to also specify the `default` and `inherit` arguments for the sake of being explicit.
        - The `check_value` method is optional, but useful for making sure your users aren't giving you garbage.
        - The `get_value` method has a default implementation that normally you shouldn't need to override, unless your default value is mutable or you have advanced logic.
        - There's also a `contribute_to_class` method that we'll cover later on.
        
        ```python
        import os
        import sys
        
        # first we have to import what we need from py_meta_utils
        from py_meta_utils import (McsArgs, MetaOption, MetaOptionsFactory,
                                   process_factory_meta_options, _missing)
        
        # then we have to declare the meta options the meta options factory should support
        class DebugMetaOption(MetaOption):
            def __init__(self):
                super().__init__(name='debug', default=False, inherit=True)
        
            def check_value(self, value, mcs_args: McsArgs):
                if not isinstance(value, bool):
                    raise TypeError(f'The {self.name} Meta option must be a bool')
        
        
        class VerbosityMetaOption(MetaOption):
            def __init__(self):
                super().__init__(name='verbosity', default=1, inherit=True)
        
            def check_value(self, value, mcs_args: McsArgs):
                if value not in {1, 2, 3}:
                    raise ValueError(f'The {self.name} Meta option must either 1, 2, or 3')
        
        
        class LogDestinationMetaOption(MetaOption):
            def __init__(self):
                super().__init__(name='log_destination', default=_missing, inherit=True)
        
            # this pattern is useful if you need a mutable default value like [] or {}
            def get_value(self, Meta, base_classes_meta, mcs_args: McsArgs):
                value = super().get_value(Meta, base_classes_meta, mcs_args)
                return value if value != _missing else 'stdout'
        
            def check_value(self, value, mcs_args: McsArgs):
                if value in {'stdout', 'stderr'}:
                    return
        
                try:
                    dir_exists = os.path.exists(os.path.dirname(value))
                except:
                    dir_exists = False
        
                if not dir_exists:
                    raise ValueError(f'The {self.name} Meta option must be one of `stdout`, '
                                     '`stderr`, or a valid filepath')
        ```
        
        The next step is to subclass [MetaOptionsFactory](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.MetaOptionsFactory) and specify the [MetaOption](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.MetaOption) subclasses you want:
        
        ```python
        class LoggingMetaOptionsFactory(MetaOptionsFactory):
            _options = [
                DebugMetaOption,
                VerbosityMetaOption,
                LogDestinationMetaOption,
            ]
        ```
        
        Then you need a metaclass to actually apply the factory options:
        
        ```python
        class LoggingMetaclass(type):
            def __new__(mcs, name, bases, clsdict):
                mcs_args = McsArgs(mcs, name, bases, clsdict)
                process_factory_meta_options(mcs_args, LoggingMetaOptionsFactory)
                return super().__new__(*mcs_args)
        ```
        
        And lastly, create the public class, using the metaclass just defined:
        
        ```python
        class YourLoggableService(metaclass=LoggingMetaclass):
            def do_important_stuff(self):
                if self.Meta.verbosity < 2:
                    self._log('doing important stuff')
                else:
                    self._log('doing really detailed important stuff like so')
        
            def _log(self, msg):
                if not self.Meta.debug:
                    return
        
                if self.Meta.log_destination == 'stdout':
                    print(msg)
                elif self.Meta.log_destination == 'stderr':
                    sys.stderr.write(msg)
                    sys.stderr.flush()
                elif self.Meta.log_destination:
                    with open(self.Meta.log_destination, 'a') as f:
                        f.write(msg)
        ```
        
        The options factory automatically adds the `Meta` attribute to the class-under-construction (in this example, `YourLoggableService`). (In this case the `Meta` attribute will be populated with the default values as supplied by the [MetaOption](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.MetaOption) subclasses specified by the factory.) In the case where the class-under-construction has a partial `Meta` class, the missing meta options will be added to it.(*)
        
        (*) In effect that's what happens, and for all practical purposes is probably how you should think about it, but technically speaking, the class-under-construction's `Meta` attribute actually gets replaced with a populated instance of the specified [MetaOptionsFactory](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.MetaOptionsFactory) subclass.
        
        The one thing we didn't cover is `MetaOption.contribute_to_class`. This is an optional callback hook that allows `MetaOption` subclasses to, well, contribute something to the class-under-construction. Most likely it adds/removes attributes to/from the class, or perhaps it wraps some method(s) with a decorator or something else entirely. 
        
        A good simple example can be found in the source code for the included [AbstractMetaOption](https://py-meta-utils.readthedocs.io/en/latest/api.html#py_meta_utils.AbstractMetaOption):
        
        ```python
        ABSTRACT_ATTR = '__abstract__'
        
        
        class AbstractMetaOption(MetaOption):
            def __init__(self):
                super().__init__(name='abstract', default=False, inherit=False)
        
            def get_value(self, Meta, base_classes_meta, mcs_args: McsArgs):
                # class attributes take precedence over the class Meta's value
                if mcs_args.clsdict.get(ABSTRACT_ATTR, False) is True:
                    return True
                return super().get_value(Meta, base_classes_meta, mcs_args) is True
        
            def contribute_to_class(self, mcs_args: McsArgs, value):
                if value is True:
                    mcs_args.clsdict[ABSTRACT_ATTR] = True
                else:
                    mcs_args.clsdict[ABSTRACT_ATTR] = False
        ```
        
        A number of libraries use the `__abstract__` class attribute to determine whether or not the class-under-construction should be considered concrete or not, but they won't understand class `Meta` options. Therefore, we implement `MetaOption.contribute_to_class` to set the `__abstract__` class attribute to the appropriate value for backwards compatibility with such libraries.
        
        ## Included Metaclass Utilities
        
        ### Singleton
        
        [Singleton](http://localhost:8000/api.html#singleton) is an included metaclass that makes any class utilizing it a singleton:
        
        ```python
        from py_meta_utils import Singleton
        
        
        class YourSingleton(metaclass=Singleton):
            pass
        
        
        instance = YourSingleton()
        assert instance == YourSingleton()
        ```
        
        Classes using [Singleton](http://localhost:8000/api.html#singleton) can be subclassed, however, you must inform the base class of your subclass:
        
        ```python
        from py_meta_utils import Singleton
        
        class BaseSingleton(metaclass=Singleton):
            pass
        
        class Extended(BaseSingleton):
            pass
        
        BaseSingleton.set_singleton_class(Extended)
        base_instance = BaseSingleton()
        extended_instance = Extended()
        assert base_instance == extended_instance == BaseSingleton() == Extended()
        ```
        
        ### deep_getattr
        
        ```python
        deep_getattr(clsdict, bases, 'attr_name', [default])
        ```
        
        `deep_getattr` acts just like `getattr` would on a constructed class object, except this operates on the pre-class-construction class dictionary and base classes. In other words, first we look for the attribute in the class dictionary, and then we search all the base classes (in method resolution order), finally returning the default value if the attribute was not found in any of the class dictionary or base classes (or it raises `AttributeError` if `default` not given).
        
        
        ### OptionalMetaclass and OptionalClass
        
        ```python
        try:
            from optional_dependency import SomeClass
        except ImportError:
            from py_meta_utils import OptionalClass as SomeClass
        
        
        class Optional(SomeClass):
            pass
        ```
        
        ## License
        
        MIT
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: docs
