wirio-settings 0.1.0

Powerful settings library for Python

Overview

Lightning-fast, strongly typed, and zero boilerplate settings library for Python:

• Great defaults from day one: It automatically looks for settings files and environment variables, with recommended configurations and zero boilerplate.
• Rust-powered core: Built with Rust under the hood for speed, reliability, and low runtime overhead.
• Cloud secrets when we need them: Azure Key Vault, AWS Secrets Manager and GCP Secret Manager integrations are available with one line of code, with safe authentication.
• Works naturally with Pydantic models: Load your app settings directly into models.
• Async-ready by design: Built to work smoothly with modern async Python apps and cloud SDKs.
• A practical replacement: Replace pydantic-settings and python-dotenv with one unified settings library.
• Roadmap: Planned capabilities include automatic reload on settings changes (events, sentinels, time, async), pluggable configuration stores, feature flags, lifetimes, prefixes, custom delimiters and aliases.

📦 Installation

uv add wirio-settings

✨ Quickstart with Pydantic models

from pydantic import BaseModel
from wirio_settings import SettingsManager


class ApplicationSettings(BaseModel):
    database_password: str


application_settings = SettingsManager().get_model(ApplicationSettings)

Source priority

wirio-settings supports multiple sources. When the same key exists in multiple sources, the last added sources have more priority.

The following sources are loaded, by default, in this order:

1. settings.yaml
2. settings.{environment}.yaml.
3. Environment variables

Considerations:

• Files are optional. If a file is not found, it's skipped.

• {environment} is the value of the WIRIO_ENVIRONMENT environment variable. If the variable is not set, its value is local. This would load, for example, settings.production.yaml if WIRIO_ENVIRONMENT=production. It standardizes the environment detection and allows us to store all settings in code, with version control.

• In the default settings, environment variables have higher priority than YAML files because the source is added after them. This means that if a key exists in both settings.yaml and environment variables, the value from environment variables will be used.

• If we add more sources, those will have higher priority than the defaults. For example, if we add Azure Key Vault as a source, it will override the defaults.

  SettingsManager().add_azure_key_vault("https://example.vault.azure.net/")
  

Naming convention

Each source (environment variables, YAML, Azure Key Vault...) has its own naming convention for keys. wirio-settings uses snake case for settings keys. When loading from sources, keys are normalized to snake case. For example, the APP_NAME environment variable maps to app_name.

Recommended usage

It depends on your usage, but the recommended setup is having the following files:

• settings.yaml with the shared settings.
• settings.{environment}.yaml with the environment-specific settings. For example, settings.production.yaml, settings.staging.yaml, settings.local.yaml, etc.

Then, we declare the settings manager, loading the default sources:

settings_manager = SettingsManager()

Now, settings_manager has settings loaded.

Let's say our API is deployed in production, so we have read the key_vault_url setting from settings.production.yaml. We can now add Azure Key Vault as a source and read the rest of the settings from there:

settings_manager.add_azure_key_vault(
    settings_manager.get_required_value("key_vault_url")
)

After that, we have all settings to construct our Pydantic model:

application_settings = settings_manager.get_model(ApplicationSettings)

Read one value

• Use get_required_value when the key must exist.

openai_api_key = settings_manager.get_required_value("openai_api_key")

By default, the settings system returns values as strings. To validate and convert to another type, pass the type as a second argument.

timeout_seconds = settings_manager.get_required_value("maximum_retries", int)

• Use get_value for optional keys.

openai_api_key = settings_manager.get_value("openai_api_key")
timeout_seconds = settings_manager.get_value("maximum_retries", int)

Defaults and required fields

If a model field has a default, that default is used when no value is found.

from pydantic import BaseModel


class ApplicationSettings(BaseModel):
    app_name: str
    port: int | None = None

Here, port defaults to None when missing. If a required field is missing, get_model raises KeyError.

Sections

Use get_section to read a section. For example, we can read the next YAML:

logging:
  log_level: WARNING

log_level = settings_manager.get_section("logging").get_required_value(
    "log_level"
)

SettingsSection supports:

• The section value itself with section.get_required_value() or section.get_required_value(type).
• A child value with section.get_required_value("child.key") or section.get_required_value("child.key", type).

If a section has only children and no value at its own path, section.get_value() returns None.

Nested keys

Nested keys use .:

• database.host
• database.port
• logging.log_level.default

Other sources

Azure Key Vault

uv add wirio-settings[azure-key-vault]

settings_manager.add_azure_key_vault(
    "https://example.vault.azure.net",
)

If no credential is provided, DefaultAzureCredential is used. We can also pass a custom async Azure credential with the credential parameter.

AWS Secrets Manager

uv add wirio-settings[aws-secrets-manager]

settings_manager.add_aws_secrets_manager(
    "SecretName"
)

The secret value must be a JSON object. wirio-settings reads and flattens that JSON into settings keys.

GCP Secret Manager

uv add wirio-settings[gcp-secret-manager]

settings_manager.add_gcp_secret_manager(
    "project-id"
)

If no credentials are provided, Application Default Credentials (ADC) are used. We can also pass custom GCP credentials with the credentials parameter.