ConfigFramework.rst ConfigFramework.loaders.rst ConfigFramework.abstract.rst
A small and simple framework to build your configs.
This project been created mostly because of me myself needing some simplistic and at the same time powerful enough tool to create configs, validate them through have simple interface.
Pypi link: https://pypi.org/project/ConfigFramework
pip install ConfigFramework
from ConfigFramework import loaders, variables, BaseConfig
first_loader = loaders.JsonStringLoader.load('{"Is it simple?": true}', defaults={"useful?": "maybe", "pi": 2.74})
second_loader = loaders.JsonStringLoader.load('{"Is it simple?": false, "Var": "value"}')
composite_loader = loaders.CompositeLoader.load(first_loader, second_loader)
class Config(BaseConfig):
is_simple = variables.BoolVar("Is it simple?", first_loader)
is_useful = variables.ConfigVar("useful?", first_loader, validator=lambda v: v == "maybe")
pi = variables.FloatVar("pi", first_loader, default=3.14, constant=True, validator=lambda v: v == 3.14)
class NestedConfig(BaseConfig):
are_composite_loaders_simple = variables.BoolVar("Is it simple?", composite_loader)
def __post_init__(self, *args, **kwargs):
yes_or_no = 'Yes' if self.are_composite_loaders_simple.value else 'No'
print(f"Is it simple to use composite loaders? {yes_or_no}")
print("Nested config:", kwargs['phrase'])
def __post_init__(self, *args, **kwargs):
is_simple_to_str = 'simple' if self.is_simple.value else 'hard'
print(f"ConfigFramework is {is_simple_to_str} and {self.is_useful.value} useful")
print(f"Here's pi = {self.pi.value}")
print("Main config:", kwargs['phrase'])
config = Config(phrase="Here's a way to pass variables")
try:
print("pi is constant:", config.pi.is_constant)
config.pi.value = 2.22
except NotImplementedError:
print("You can not set value to constants on runtime")
And this is how you can get typehints for your variables. .. code-block:: python
from ConfigFramework import BaseConfig from ConfigFramework.loaders import DictLoader from ConfigFramework.variables import ConfigVar from ConfigFramework.custom_types import VariableType
loader = DictLoader.load({"a": 1, "b": 2.22})
- class Config(BaseConfig):
a: VariableType[int] = ConfigVar("a", loader) b: VariableType[float] = ConfigVar("b", loader)
conf = Config() # You will get float functions suggestions from IDE if you use it like that! conf.b.value.as_integer_ratio()
See examples with explanation here
- Yaml
- Json (strings or files)
- Environment variables
- Pythons dictionaries
- Composite loading from multiple simple loaders
- Loading configs from multiple sources
- Creating custom loaders and variables types
- Nested configs
- Flexible configs definition
- Config values validations
- Casting variables values to specific types using functions
- Casting to acceptable variable type before dumping variable to loader
- Default values for per loader or per variable
- Translating one config loaders data to other (with or without including default values for each one)
- Composite loaders that allow you to define where to look up values using only one loader, that handles combining others
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