pyproprop 0.4.10

Package for aiding writing classes with lots of similar simple properties without the boilerplate

Package for aiding writing classes with lots of similar simple properties without the boilerplate.

Status

Latest Release		Docs
PyPI		Anaconda
Coverage		License

What is Pyproprop?

Do you often find yourself writing classes with properties such as:

from some_other_module import DefaultObject, some_type

class ExampleClass:

    def __init__(self,
                 type_checked_value,
                 bounded_numeric_value,
                 specific_length_sequence_value,
                 obj_with_method_applied_value,
                 ):
        self.type_check_attr = type_checked_value
        self.bounded_numeric_attr = bounded_numeric_value
        self.specific_length_sequence_attr = specific_length_sequence_value
        self.obj_with_method_applied_attr = obj_with_method_applied_value
        self.instantiate_default_if_none_attr = None

    @property
    def type_checked_attr(self):
        return self._type_checked_attr

    @type_checked_attr.setter
    def type_checked_attr(self, val):
        if not isinstance(val, some_type):
            msg = "`type_checked_attr` must be of `some_type`"
            raise TypeError(msg)
        self._type_checked_attr = val

    @property
    def bounded_numeric_attr(self):
        return self._bounded_numeric_attr

    @bounded_numeric_attr.setter
    def bounded_numeric_attr(self, val):
        val = float(val)
        lower_bound = -1.0
        upper_bound = 2.5
        if val < lower_bound:
            msg = f"`bounded_numeric_attr` must be greater than {lower_bound}"
            raise ValueError(msg)
        if val >= upper_bound:
            msg = (f"`bounded_numeric_attr` must be less than or equal to "
                   f"{upper_bound}.")
            raise ValueError(msg)
        self._type_checked_attr = val

    @property
    def specific_length_sequence_attr(self):
        return self._specific_length_sequence_attr

    @specific_length_sequence_attr.setter
    def specific_length_sequence_attr(self, val):
        if len(val) != 2:
            msg = "`specific_length_sequence` must be an iterable of length 2."
            raise ValueError(msg)
        self._specific_length_sequence_attr = val

    @property
    def obj_with_method_applied_value(self):
        return self._obj_with_method_applied_value

    @obj_with_method_applied_value.setter
    def obj_with_method_applied_value(self, val):
        val = str(val)
        self._obj_with_method_applied_value = val.title()

    @property
    def instantiate_default_if_none_attr(self):
        return self._instantiate_default_if_none_attr

    @instantiate_default_if_none_attr.setter
    def instantiate_default_if_none_attr(self, val):
        if val is None:
            val = DefaultObject()
        self._instantiate_default_if_none_attr = val

With Pyproprop all of this boilerplate can be removed and instead the exact same class can be rewritten as:

from pyproprop import processed_property
from some_other_module import DefaultObject, some_type

class ExampleClass:

    type_checked_attr = processed_property(
        "type_checked_attr",
        description="property with enforced type of `some_type`",
        type=some_type,
    )
    bounded_numeric_attr = processed_property(
        "bounded_numeric_attr",
        description="numerical attribute with upper and lower bounds"
        type=float,
        cast=True,
        min=-1.0,
        max=2.5,
    )
    specific_length_sequence_attr = processed_property(
        "specific_length_sequence_attr",
        description="sequence of length exactly 2",
        len=2,
    )
    obj_with_method_applied_attr = processed_property(
        "obj_with_method_applied_attr",
        description="sting formatted to use title case"
        type=str,
        cast=True,
        method="title",
    )
    instantiate_default_if_none_attr = processed_property(
        "instantiate_default_if_none_attr",
        default=DefaultObject,
    )

    def __init__(self,
                 type_checked_value,
                 bounded_numeric_value,
                 specific_length_sequence_value,
                 obj_with_method_applied_value,
                 ):
        self.type_check_attr = type_checked_value
        self.bounded_numeric_attr = bounded_numeric_value
        self.specific_length_sequence_attr = specific_length_sequence_value
        self.obj_with_method_applied_attr = obj_with_method_applied_value
        self.instantiate_default_if_none_attr = None

Installation

The easiest way to install Pyproprop is using the Anaconda Python distribution and its included Conda package management system. To install Pyproprop and its required dependencies, enter the following command at a command prompt:

conda install pyproprop

To install using pip, enter the following command at a command prompt:

pip install pyproprop

For more information, refer to the installation documentation.

Contribute

• Issue Tracker: https://github.com/brocksam/pyproprop/issues

• Source Code: https://github.com/brocksam/pyproprop

License

This project is licensed under the terms of the MIT license.