configargparse-yaml-env-layeringlisted

Standardize service configuration using a three-layer hierarchy with YAML defaults, configargparse CLI/env merging, and a Pydantic BaseSettings singleton. ## When to use - Setting up configuration for a new Python backend service or microservice - Building services with multiple runtime modes (server, consumer, temporal_worker, cron) - Implementing precedence-ordered configuration (YAML defaults < environment variables < CLI arguments) - Migrating from flat .env files to structured, type-safe configuration - Configuring services that need different entrypoints based on MODE environment variable - Setting up mode-specific dispatch via entrypoint.py pattern - Building container-deployable services that override defaults via environment variables - Needing a module-level config singleton accessible throughout the codebase - Implementing auto-prefixed environment variable parsing for all config keys - Setting up services with database, Kafka, Temporal, Redis, and other infrastructure dependencies ## Core conventions 1. **Three-layer config hierarchy**: (1) `config/default.yaml` contains structured defaults for all environments; (2) `configargparse.ArgParser` with `auto_env_var_prefix=""` merges CLI args and env vars over YAML; (3) `config/docker_config.py` wraps parsed args in Pydantic `BaseSettings` and exports a module-level singleton `loaded_config`. Precedence: YAML < env vars < CLI args. 2. **YAML defaults in `config/default.yaml`**: define all config keys with developm