| Name | plugnparse JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | Python utilities package for plugin style architectures with parsable classes for parameters. |
| upload_time | 2024-04-15 01:22:32 |
| maintainer | Dylan DeSantis |
| docs_url | None |
| author | Dylan DeSantis |
| requires_python | >=3.8 |
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| keywords |
plugin
parsing
json
|
| VCS |
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# Plug-n-Parse
Python utilities package for plugin style architectures with parsable classes for parameters.
- [Setting Up](#setting-up)
- [Testing](#testing)
- [Coverage](#coverage)
- [Usage](#usage)
## Setting Up
### Setting Up Local Environment
Install python >3.8 if it is not already installed.
#### Set Up the Virtual Environment
Set up the local environment and install pre-commit so that the hooks are automatically run locally:
```shell
python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
```
#### Setting Up for the Build
To build the python wheels and distribution package, use the `build` python packages.
To install the `build` package use the following command:
```shell
pip install --upgrade build
```
#### Building the Packages
To execute the build, follow the commands below. More detailed instructions on using `build` can be found [here](https://pypa-build.readthedocs.io/en/latest/).
```shell
python -m build
```
This should generate `plugnparse-<version>.tar.gz` and `plugnparse-<version>-py3-none-any.whl` files in either the current working
directory, `<cwd>/dist/`, or to a desired output directory using the argument `--outdir OUTDIR` in the build command
above.
#### Installing the Built Packages
Use `pip` to install the generated package in another virtual environment or computer. This can be done using the
following command:
```shell
pip install OUTDIR/plugnparse-<verison>-py3-none-any.whl
```
The `OUTDIR` is the directory location of the generated python wheel.
## Testing
To run the tests follow the below commands
```shell
cd plugnparse/src
pytest ./tests
```
## Coverage
To generate coverage reports follow the below commands
```shell
pip install -U coverage
coverage run --rcfile=./.coveragerc -m pytest ./src/tests
coverage html
google-chrome ./artifacts/coverage_report/html/index.html
```
## Usage
- [Using the Parsable Class](#using-the-parsable-class)
- [Using the Plugin and Parameters Classes](#using-the-plugin-and-parameters-classes)
### Using the Parsable Class
The `Parsable` class allows for automatic serialization and deserialization of entire classes in a JSON format.
The following example demonstrates a basic usage of the `Parsable` class.
```python
# --- external imports ---
from enum import Enum, auto
from typing import Optional
# --- internal imports ---
from plugnparse import Parsable, enum_setter, logger
class EnumClass(Enum):
Foo = auto()
Bar = auto()
Baz = auto()
class ClassA(Parsable):
def __init__(self, *args, **kwargs):
# --- init the parent ---
super().__init__(*args, **kwargs)
# --- update the lists of serializable attributes ---
self._serializable_attributes.extend(['foo'])
self._enum_attributes.extend(['bar'])
self._specialized_attributes.extend(['baz'])
# --- set the properties ---
self.foo = kwargs.get('foo')
self.bar = kwargs.get('bar')
self.baz = kwargs.get('baz')
##########################################################################
# Foo Properties
##########################################################################
@property
def has_foo(self):
return self._foo is not None
@property
def foo(self) -> int:
if self._foo is None:
logger.log_and_raise(AttributeError, "foo has not been set")
return self._foo
@foo.setter
def foo(self, input_value: Optional[int]):
if input_value is None or isinstance(input_value, int):
self._foo = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
##########################################################################
# Bar Properties
##########################################################################
@property
def has_bar(self):
return self._bar is not None
@property
def bar(self) -> EnumClass:
if self._bar is None:
logger.log_and_raise(AttributeError, "bar has not been set")
return self._bar
@bar.setter
@enum_setter(EnumClass)
def bar(self, input_value: Optional[EnumClass]):
if input_value is None or isinstance(input_value, EnumClass):
self._bar = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
##########################################################################
# Baz Properties
##########################################################################
@property
def has_baz(self):
return self._baz is not None
@property
def baz(self) -> float:
if self._baz is None:
logger.log_and_raise(AttributeError, "baz has not been set.")
return self._baz
@baz.setter
def baz(self, input_value: Optional[float]):
if input_value is None or isinstance(input_value, float):
self._baz = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
def baz_encode(self) -> dict:
"""Special encoder function for baz"""
return {"baz_keyword": self.baz}
def baz_decode(self, input_value: dict):
"""Special decoder function."""
self.baz = input_value.get('baz_keyword')
```
You should then provide a json dictionary of serializable values with the `from_dict()` function.
```python
json_dictionary = {'foo': 1, 'bar': "Foo", 'baz': {'baz_keyword': 10.0}}
class_a = ClassA()
class_a.from_dict(json_dictionary)
```
To then get the original json dictionary from the updated class you use the `to_dict()` function
```python
print(class_a.to_dict())
>>> {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo', 'baz': {'baz_keyword': 10.0}}
```
Notice that the additional key-value pairs, `parsable_type` and `parsable_module`. These two key-values allow for generic
creation and parsing directly from the json object without needing to know the class type that is being parsed. To leverage
this type of functionality you can utilize the plugnparse properties module and specifically its `parse()` function.
```python
from plugnparse import properties
full_json_dictionary = class_a.to_dict()
new_class_a = properties.parse(full_json_dictionary)
print("parsed type: ", type(new_class_a))
print("parsed information: ", new_class_a.to_dict())
>>> parsed type: <class '__main__.ClassA'>
>>> parsed information: {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo', 'baz': {'baz_keyword': 10.0}}
```
Once there is a single `Parsable` implementation then other `Parsable` classes can have attributes which can also be `Parsable` types.
The class below demonstrates the additional type of attributes that can be automatically parsed which are:
- Parsable attributes
- A dictionary of parsable key-value pairs, specifically where the values are subclasses of `Parsable`.
- A list of parsable values.
```python
from typing import Dict
class ClassB(Parsable):
def __init__(self, *args, **kwargs):
# --- init the parent ---
super().__init__(*args, **kwargs)
# --- update the attributes ---
self._parsable_attributes.extend(['bingo'])
self._dict_of_parsables.extend(['bingo_dictionary'])
self._list_of_parsables.extend(['bango_list'])
# --- set the components ---
self.bingo = kwargs.get('bingo')
self.bingo_dictionary = kwargs.get('bingo_dictionary')
self.bango_list = kwargs.get('bango_list')
##########################################################################
# Bingo Properties
##########################################################################
@property
def has_bingo(self):
return self._bingo is not None
@property
def bingo(self) -> ClassA:
if self._bingo is None:
logger.log_and_raise(AttributeError, "bingo has not been set")
return self._bingo
@bingo.setter
@ClassA.static_class_setter()
def bingo(self, input_value: Optional[ClassA]):
if input_value is None or isinstance(input_value, ClassA):
self._bingo = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
##########################################################################
# Bingo Dictionary Properties
##########################################################################
@property
def has_bingo_dictionary(self):
return self._bingo_dictionary is not None
@property
def bingo_dictionary(self) -> Dict[str, ClassA]:
if self._bingo_dictionary is None:
logger.log_and_raise(AttributeError, "bingo_dictionary has not been set")
return self._bingo_dictionary
@bingo_dictionary.setter
def bingo_dictionary(self, input_value: Optional[Dict[str, ClassA]]):
if input_value is None:
self._bingo_dictionary = None
elif isinstance(input_value, dict):
for key, value in input_value.items():
if not (isinstance(key, str) and isinstance(value, ClassA)):
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
self._bingo_dictionary = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
##########################################################################
# Bango List Properties
##########################################################################
@property
def has_bango_list(self):
return self._bango_list is not None
@property
def bango_list(self) -> List[ClassA]:
if self._bango_list is None:
logger.log_and_raise(AttributeError, "bango_list has not been set")
return self._bango_list
@bango_list.setter
def bango_list(self, input_value: Optional[List[ClassA]]):
if input_value is None:
self._bango_list = None
elif isinstance(input_value, list):
for value in input_value:
if not isinstance(value, ClassA):
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
self._bango_list = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
```
Again to populate the `ClassB`, you would provide it a serialized form of the json dictionary.
```python
class_b_json_dictionary = {'bingo': {'foo': 1, 'bar': "Foo"},
'bingo_dictionary': {'a': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 5}},
'bango_list': [{'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 10}]}
class_b = ClassB()
class_b.from_dict(class_b_json_dictionary)
print(class_b.to_dict())
>>> {'parsable_type': 'ClassB', 'parsable_module': '__main__', 'bingo': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo'}, 'bingo_dictionary': {'a': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 5}}, 'bango_list': [{'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 10}]}
```
### Using the Plugin and Parameters Classes
Together the `Parameters` and the `Plugin` classes can be utilized to generate a plugin architecture very simply.
The example below demonstrates the bare minimum implementations needed to create a plugin architecture.
```python
# --- external imports ---
from typing import Optional
from abc import ABC, abstractmethod
# --- internal imports ---
from plugnparse import Plugin, Parameters, logger
class ExampleParameters(Parameters):
plugin_property_name = 'plugin_type'
plugin_module_property_name = 'plugin_module'
def __init__(self, *args, **kwargs):
# --- init the parent ---
super().__init__(*args, **kwargs)
# --- update the attributes ---
self._serializable_attributes.extend(['plugin_type', 'plugin_module'])
# --- set components ---
self.plugin_type = kwargs.get('plugin_type')
self.plugin_module = kwargs.get('plugin_module')
##########################################################################
# Plugin Type Properties
##########################################################################
@property
def has_plugin_type(self):
return self._plugin_type is not None
@property
def plugin_type(self) -> str:
if self._plugin_type is None:
logger.log_and_raise(AttributeError, "plugin_type has not been set")
return self._plugin_type
@plugin_type.setter
def plugin_type(self, input_value: Optional[str]):
if input_value is None or isinstance(input_value, str):
self._plugin_type = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
##########################################################################
# Plugin Module Properties
##########################################################################
@property
def has_plugin_module(self):
return self._plugin_module is not None
@property
def plugin_module(self) -> str:
if self._plugin_module is None:
logger.log_and_raise(AttributeError, "plugin_module has not been set")
return self._plugin_module
@plugin_module.setter
def plugin_module(self, input_value: Optional[str]):
if input_value is None or isinstance(input_value, str):
self._plugin_module = input_value
else:
logger.log_and_raise(TypeError, "Invalid input type [", type(input_value), "].")
class BasePlugin(Plugin, ABC):
parameters_cls = ExampleParameters
def __init__(self, **kwargs):
super().__init__(**kwargs)
##########################################################################
# Dynamic Function
##########################################################################
@abstractmethod
def execute(self):
pass # pragma: no cover
class PluginExampleA(BasePlugin):
def __init__(self, **kwargs):
super().__init__(**kwargs)
##########################################################################
# Dynamic Function
##########################################################################
def execute(self):
print("PluginExampleA: Foo!")
class PluginExampleB(BasePlugin):
def __init__(self, **kwargs):
super().__init__(**kwargs)
##########################################################################
# Dynamic Function
##########################################################################
def execute(self):
print("PluginExampleB: Bar!")
```
To then utilize the architecture you would populate your parameters class and construct the desired plugins from it.
```python
parameters = ExampleParameters(plugin_type="PluginExampleA", plugin_module="__main__")
generated_plugin = BasePlugin.construct_from_parameters(parameters)
generated_plugin.execute()
>>> PluginExampleA: Foo!
```
To create a different plugin all you need to do is update the parameters used to generate the plugin (generally the module is also updated but since this code is all in one file the module is the same).
```python
parameters.plugin_type = "PluginExampleB"
second_generated_plugin = BasePlugin.construct_from_parameters(parameters)
second_generated_plugin.execute()
>>> PluginExampleB: Bar!
```
Raw data
{
"_id": null,
"home_page": null,
"name": "plugnparse",
"maintainer": "Dylan DeSantis",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "plugin, parsing, json",
"author": "Dylan DeSantis",
"author_email": null,
"download_url": null,
"platform": null,
"description": "# Plug-n-Parse\nPython utilities package for plugin style architectures with parsable classes for parameters.\n\n- [Setting Up](#setting-up)\n- [Testing](#testing)\n- [Coverage](#coverage)\n- [Usage](#usage)\n\n## Setting Up\n\n### Setting Up Local Environment\nInstall python >3.8 if it is not already installed.\n\n#### Set Up the Virtual Environment\nSet up the local environment and install pre-commit so that the hooks are automatically run locally:\n```shell\npython3 -m venv venv\nsource venv/bin/activate\npip install --upgrade pip\npip install -r requirements.txt\n```\n\n#### Setting Up for the Build\nTo build the python wheels and distribution package, use the `build` python packages.\n\nTo install the `build` package use the following command:\n\n```shell\npip install --upgrade build\n```\n\n#### Building the Packages\nTo execute the build, follow the commands below. More detailed instructions on using `build` can be found [here](https://pypa-build.readthedocs.io/en/latest/).\n\n```shell\npython -m build\n```\n\nThis should generate `plugnparse-<version>.tar.gz` and `plugnparse-<version>-py3-none-any.whl` files in either the current working \ndirectory, `<cwd>/dist/`, or to a desired output directory using the argument `--outdir OUTDIR` in the build command \nabove. \n\n#### Installing the Built Packages\nUse `pip` to install the generated package in another virtual environment or computer. This can be done using the\nfollowing command:\n\n```shell\npip install OUTDIR/plugnparse-<verison>-py3-none-any.whl\n```\n\nThe `OUTDIR` is the directory location of the generated python wheel.\n\n## Testing\nTo run the tests follow the below commands\n```shell\ncd plugnparse/src\npytest ./tests\n```\n\n## Coverage\nTo generate coverage reports follow the below commands\n```shell\npip install -U coverage\ncoverage run --rcfile=./.coveragerc -m pytest ./src/tests\ncoverage html\ngoogle-chrome ./artifacts/coverage_report/html/index.html\n```\n\n## Usage\n- [Using the Parsable Class](#using-the-parsable-class)\n- [Using the Plugin and Parameters Classes](#using-the-plugin-and-parameters-classes)\n\n### Using the Parsable Class\nThe `Parsable` class allows for automatic serialization and deserialization of entire classes in a JSON format.\nThe following example demonstrates a basic usage of the `Parsable` class.\n\n```python\n# --- external imports ---\nfrom enum import Enum, auto\nfrom typing import Optional\n# --- internal imports ---\nfrom plugnparse import Parsable, enum_setter, logger\n\n\nclass EnumClass(Enum):\n Foo = auto()\n Bar = auto()\n Baz = auto()\n\n\nclass ClassA(Parsable):\n\n def __init__(self, *args, **kwargs):\n # --- init the parent ---\n super().__init__(*args, **kwargs)\n # --- update the lists of serializable attributes ---\n self._serializable_attributes.extend(['foo'])\n self._enum_attributes.extend(['bar'])\n self._specialized_attributes.extend(['baz'])\n\n # --- set the properties ---\n self.foo = kwargs.get('foo')\n self.bar = kwargs.get('bar')\n self.baz = kwargs.get('baz')\n\n ##########################################################################\n # Foo Properties\n ##########################################################################\n @property\n def has_foo(self):\n return self._foo is not None\n\n @property\n def foo(self) -> int:\n if self._foo is None:\n logger.log_and_raise(AttributeError, \"foo has not been set\")\n return self._foo\n\n @foo.setter\n def foo(self, input_value: Optional[int]):\n if input_value is None or isinstance(input_value, int):\n self._foo = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n ##########################################################################\n # Bar Properties\n ##########################################################################\n @property\n def has_bar(self):\n return self._bar is not None\n\n @property\n def bar(self) -> EnumClass:\n if self._bar is None:\n logger.log_and_raise(AttributeError, \"bar has not been set\")\n return self._bar\n\n @bar.setter\n @enum_setter(EnumClass)\n def bar(self, input_value: Optional[EnumClass]):\n if input_value is None or isinstance(input_value, EnumClass):\n self._bar = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n ##########################################################################\n # Baz Properties\n ##########################################################################\n @property\n def has_baz(self):\n return self._baz is not None\n\n @property\n def baz(self) -> float:\n if self._baz is None:\n logger.log_and_raise(AttributeError, \"baz has not been set.\")\n return self._baz\n\n @baz.setter\n def baz(self, input_value: Optional[float]):\n if input_value is None or isinstance(input_value, float):\n self._baz = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n \n def baz_encode(self) -> dict:\n \"\"\"Special encoder function for baz\"\"\"\n return {\"baz_keyword\": self.baz}\n \n def baz_decode(self, input_value: dict):\n \"\"\"Special decoder function.\"\"\"\n self.baz = input_value.get('baz_keyword')\n```\n\nYou should then provide a json dictionary of serializable values with the `from_dict()` function.\n\n```python\njson_dictionary = {'foo': 1, 'bar': \"Foo\", 'baz': {'baz_keyword': 10.0}}\nclass_a = ClassA()\nclass_a.from_dict(json_dictionary)\n```\n\nTo then get the original json dictionary from the updated class you use the `to_dict()` function\n\n```python\nprint(class_a.to_dict())\n>>> {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo', 'baz': {'baz_keyword': 10.0}}\n```\n\nNotice that the additional key-value pairs, `parsable_type` and `parsable_module`. These two key-values allow for generic\ncreation and parsing directly from the json object without needing to know the class type that is being parsed. To leverage\nthis type of functionality you can utilize the plugnparse properties module and specifically its `parse()` function.\n\n```python\nfrom plugnparse import properties\n\nfull_json_dictionary = class_a.to_dict()\nnew_class_a = properties.parse(full_json_dictionary)\nprint(\"parsed type: \", type(new_class_a))\nprint(\"parsed information: \", new_class_a.to_dict())\n\n>>> parsed type: <class '__main__.ClassA'>\n>>> parsed information: {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo', 'baz': {'baz_keyword': 10.0}}\n```\n\nOnce there is a single `Parsable` implementation then other `Parsable` classes can have attributes which can also be `Parsable` types.\nThe class below demonstrates the additional type of attributes that can be automatically parsed which are:\n- Parsable attributes\n- A dictionary of parsable key-value pairs, specifically where the values are subclasses of `Parsable`.\n- A list of parsable values.\n\n```python\nfrom typing import Dict\n\n\nclass ClassB(Parsable):\n\n def __init__(self, *args, **kwargs):\n # --- init the parent ---\n super().__init__(*args, **kwargs)\n # --- update the attributes ---\n self._parsable_attributes.extend(['bingo'])\n self._dict_of_parsables.extend(['bingo_dictionary'])\n self._list_of_parsables.extend(['bango_list'])\n\n # --- set the components ---\n self.bingo = kwargs.get('bingo')\n self.bingo_dictionary = kwargs.get('bingo_dictionary')\n self.bango_list = kwargs.get('bango_list')\n\n ##########################################################################\n # Bingo Properties\n ##########################################################################\n @property\n def has_bingo(self):\n return self._bingo is not None\n\n @property\n def bingo(self) -> ClassA:\n if self._bingo is None:\n logger.log_and_raise(AttributeError, \"bingo has not been set\")\n return self._bingo\n\n @bingo.setter\n @ClassA.static_class_setter()\n def bingo(self, input_value: Optional[ClassA]):\n if input_value is None or isinstance(input_value, ClassA):\n self._bingo = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n ##########################################################################\n # Bingo Dictionary Properties\n ##########################################################################\n @property\n def has_bingo_dictionary(self):\n return self._bingo_dictionary is not None\n\n @property\n def bingo_dictionary(self) -> Dict[str, ClassA]:\n if self._bingo_dictionary is None:\n logger.log_and_raise(AttributeError, \"bingo_dictionary has not been set\")\n return self._bingo_dictionary\n\n @bingo_dictionary.setter\n def bingo_dictionary(self, input_value: Optional[Dict[str, ClassA]]):\n if input_value is None:\n self._bingo_dictionary = None\n elif isinstance(input_value, dict):\n for key, value in input_value.items():\n if not (isinstance(key, str) and isinstance(value, ClassA)):\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n self._bingo_dictionary = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n ##########################################################################\n # Bango List Properties\n ##########################################################################\n @property\n def has_bango_list(self):\n return self._bango_list is not None\n\n @property\n def bango_list(self) -> List[ClassA]:\n if self._bango_list is None:\n logger.log_and_raise(AttributeError, \"bango_list has not been set\")\n return self._bango_list\n\n @bango_list.setter\n def bango_list(self, input_value: Optional[List[ClassA]]):\n if input_value is None:\n self._bango_list = None\n elif isinstance(input_value, list):\n for value in input_value:\n if not isinstance(value, ClassA):\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n self._bango_list = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n```\n\nAgain to populate the `ClassB`, you would provide it a serialized form of the json dictionary.\n\n```python\nclass_b_json_dictionary = {'bingo': {'foo': 1, 'bar': \"Foo\"},\n 'bingo_dictionary': {'a': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 5}},\n 'bango_list': [{'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 10}]}\nclass_b = ClassB()\nclass_b.from_dict(class_b_json_dictionary)\nprint(class_b.to_dict())\n>>> {'parsable_type': 'ClassB', 'parsable_module': '__main__', 'bingo': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 1, 'bar': 'Foo'}, 'bingo_dictionary': {'a': {'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 5}}, 'bango_list': [{'parsable_type': 'ClassA', 'parsable_module': '__main__', 'foo': 10}]}\n```\n\n### Using the Plugin and Parameters Classes\nTogether the `Parameters` and the `Plugin` classes can be utilized to generate a plugin architecture very simply.\nThe example below demonstrates the bare minimum implementations needed to create a plugin architecture.\n\n```python\n# --- external imports ---\nfrom typing import Optional\nfrom abc import ABC, abstractmethod\n# --- internal imports ---\nfrom plugnparse import Plugin, Parameters, logger\n\n\nclass ExampleParameters(Parameters):\n plugin_property_name = 'plugin_type'\n plugin_module_property_name = 'plugin_module'\n \n def __init__(self, *args, **kwargs):\n # --- init the parent ---\n super().__init__(*args, **kwargs)\n # --- update the attributes ---\n self._serializable_attributes.extend(['plugin_type', 'plugin_module'])\n \n # --- set components ---\n self.plugin_type = kwargs.get('plugin_type')\n self.plugin_module = kwargs.get('plugin_module')\n \n ##########################################################################\n # Plugin Type Properties\n ##########################################################################\n @property\n def has_plugin_type(self):\n return self._plugin_type is not None\n\n @property\n def plugin_type(self) -> str:\n if self._plugin_type is None:\n logger.log_and_raise(AttributeError, \"plugin_type has not been set\")\n return self._plugin_type\n\n @plugin_type.setter\n def plugin_type(self, input_value: Optional[str]):\n if input_value is None or isinstance(input_value, str):\n self._plugin_type = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n ##########################################################################\n # Plugin Module Properties\n ##########################################################################\n @property\n def has_plugin_module(self):\n return self._plugin_module is not None\n\n @property\n def plugin_module(self) -> str:\n if self._plugin_module is None:\n logger.log_and_raise(AttributeError, \"plugin_module has not been set\")\n return self._plugin_module\n\n @plugin_module.setter\n def plugin_module(self, input_value: Optional[str]):\n if input_value is None or isinstance(input_value, str):\n self._plugin_module = input_value\n else:\n logger.log_and_raise(TypeError, \"Invalid input type [\", type(input_value), \"].\")\n\n\nclass BasePlugin(Plugin, ABC):\n parameters_cls = ExampleParameters\n\n def __init__(self, **kwargs):\n super().__init__(**kwargs)\n\n ##########################################################################\n # Dynamic Function\n ##########################################################################\n @abstractmethod\n def execute(self):\n pass # pragma: no cover\n\n\nclass PluginExampleA(BasePlugin):\n\n def __init__(self, **kwargs):\n super().__init__(**kwargs)\n\n ##########################################################################\n # Dynamic Function\n ##########################################################################\n def execute(self):\n print(\"PluginExampleA: Foo!\")\n\n\nclass PluginExampleB(BasePlugin):\n\n def __init__(self, **kwargs):\n super().__init__(**kwargs)\n\n ##########################################################################\n # Dynamic Function\n ##########################################################################\n def execute(self):\n print(\"PluginExampleB: Bar!\")\n```\n\nTo then utilize the architecture you would populate your parameters class and construct the desired plugins from it.\n```python \nparameters = ExampleParameters(plugin_type=\"PluginExampleA\", plugin_module=\"__main__\")\ngenerated_plugin = BasePlugin.construct_from_parameters(parameters)\ngenerated_plugin.execute()\n>>> PluginExampleA: Foo!\n```\n\nTo create a different plugin all you need to do is update the parameters used to generate the plugin (generally the module is also updated but since this code is all in one file the module is the same).\n\n```python\nparameters.plugin_type = \"PluginExampleB\"\nsecond_generated_plugin = BasePlugin.construct_from_parameters(parameters)\nsecond_generated_plugin.execute()\n>>> PluginExampleB: Bar!\n```\n",
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