dj_settings: Project Settings the UNIX Way
dj_settings provides a robust, UNIX-inspired approach to managing application configuration. It reads settings from multiple locations with a clear priority order, supporting environment variables, .d directory overrides, and multiple configuration formats.
Originally designed for Django projects, it has evolved into a versatile configuration management solution suitable for any Python application.
Key Features
- UNIX-style configuration hierarchy: Read from
/etc/,~/.config/, project directory, and environment variables .ddirectory overrides: Override configuration files with drop-in directories (e.g.,config.yml.d/*.yml)- Multiple format support: YAML, TOML, JSON, INI, and environment files
- Type-safe settings classes: Create typed configuration objects with decorators
- Environment variable integration: Seamlessly blend file-based and environment-based configuration
- Array merging: Optionally merge arrays instead of overwriting them
Quick Start
from dj_settings import ConfigParser
parser = ConfigParser("/path/to/project/config.yml")
# Get a setting with the full fallback chain
database_url = parser.get_setting(
"url",
sections=["database"],
default="sqlite:///db.sqlite3",
)
Or use type-safe settings classes:
from dj_settings import config_value, settings_class
@settings_class("/path/to/project/config.yml", merge_arrays=True)
class Settings:
debug: bool = config_value("DEBUG", default=False)
database_url: str = config_value("url", sections=["database"])
allowed_hosts: list[str] = config_value(
"allowed_hosts", sections=["server"], default=["localhost"]
)
settings = Settings()
print(settings.debug) # Type-safe access
Documentation
- Installation Guide - How to install dj_settings
- Usage Guide - Comprehensive usage documentation
- Config Parsers - Using ConfigParser and get_setting
- Settings Classes - Type-safe settings with decorators
- Changelog - Version history and changes
- License - BSD-3-Clause license
- Code of Conduct - Community guidelines
Why dj_settings?
Managing configuration across different environments (development, staging, production) is challenging. dj_settings solves this by:
- Following UNIX conventions: Uses the well-understood pattern of system-wide (
/etc/), user-specific (~/.config/), and project-local configuration - Supporting overrides: The
.ddirectory pattern allows incremental configuration without modifying base files - Being format-agnostic: Works with YAML, TOML, JSON, INI, and environment variables
- Providing type safety: Modern Python type hints and dataclasses for better IDE support and error detection
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