Package for aiding writing classes with lots of similar simple properties without the boilerplate
Project description
Package for aiding writing classes with lots of similar simple properties without the boilerplate.
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Anaconda |
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.
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