Welcome to Simple Config Builder

This is a simple tool to help you build a configuration file for your project.

Installation

pip install simple_config_builder

Getting Started

When writing your library configuration files are often a necessity. Instead of using a dictionary or a class to store your configuration, you can build config classes using this tool.

from simple_config_builder import Configclass, Field

class MyConfig(Configclass):
    name: str = "John Doe"
    age: int = 30
    is_student: bool = False
    grades: int = Field(gt=0, lt=100)

This will create a class with the specified fields and default values and validation rules.

For IO, you can use

from simple_config_builder.configparser import Configparser
from simple_config_builder import Configclass, Field

@configclass
class MyConfig:
    name: str = "John Doe"
    age: int = 30
    is_student: bool = False
    grades: int = Field(gt=0, lt=100, default=90)

# Load and parse the configuration file
config = Configparser("config.json")

# Save the configuration file
config.save()

# reload the configuration file
config.reload()

# Set a config object
config['my_config'] = MyConfig("John Doe", 30, False, 90)

Apart from that autosave and autoreload is supported.

Callables

You can also use callables as fields in the config class.

from simple_config_builder import Field, Configclass
from collections.abc import Callable

@configclass
class MyConfig:
    name: str = "John Doe"
    age: int = 30
    is_student: bool = False
    grades: int = Field(gt=0, lt=100, default=90)
    student_name_calling: Callable

The callables are saved in the configuration files as package.module name and function name. If the module is not in the python path, a file_path is saved additionally.

{
    "name": "John Doe",
    "age": 30,
    "is_student": false,
    "grades": 90,
    "student_name_calling": 
    {
      "module": "package.module",
      "function": "function_name",
      "file_path": "path/to/file"
    }
}

Typing

Because the Configclass is based on pydantic, you can use all the features of pydantic, like type hints, validation, and more. You can use the Field from pydantic to define constraints on the fields.

from simple_config_builder import Configclass


class MyConfig(Configclass):
    name: str = "John Doe"
    age: int = 30
    is_student: bool = False
    grades: int = config_field(gt=0, lt=100)


c = MyConfig(
    name="John Doe",
    age=30,
    is_student=False,
    grades=90
)    

c.name = "Jane Doe"

def my_function(config: Configclass):
    print(config.name)

my_function(MyConfig())

License

This project is licensed under the MIT License - see the LICENSE file for details.