Python Configuration Management

Externalize configuration from code using environment variables and typed settings. Well-managed configuration enables the same code to run in any environment without modification.

When to Use This Skill

• Setting up a new project's configuration system
• Migrating from hardcoded values to environment variables
• Implementing pydantic-settings for typed configuration
• Managing secrets and sensitive values
• Creating environment-specific settings (dev/staging/prod)
• Validating configuration at application startup

Core Concepts

1. Externalized Configuration

All environment-specific values (URLs, secrets, feature flags) come from environment variables, not code.

2. Typed Settings

Parse and validate configuration into typed objects at startup, not scattered throughout code.

3. Fail Fast

Validate all required configuration at application boot. Missing config should crash immediately with a clear message.

4. Sensible Defaults

Provide reasonable defaults for local development while requiring explicit values for sensitive settings.

Quick Start

from pydantic_settings import BaseSettings
from pydantic import Field

class Settings(BaseSettings):
    database_url: str = Field(alias="DATABASE_URL")
    api_key: str = Field(alias="API_KEY")
    debug: bool = Field(default=False, alias="DEBUG")

settings = Settings()  # Loads from environment

Fundamental Patterns

Pattern 1: Typed Settings with Pydantic

Create a central settings class that loads and validates all configuration.

from pydantic_settings import BaseSettings
from pydantic import Field, PostgresDsn, ValidationError
import sys

class Settings(BaseSettings):
    """Application configuration loaded from environment variables."""

    # Database
    db_host: str = Field(alias="DB_HOST")
    db_port: int = Field(default=5432, alias="DB_PORT")
    db_name: str = Field(alias="DB_NAME")
    db_user: str = Field(alias="DB_USER")
    db_password: str = Field(alias="DB_PASSWORD")

    # Redis
    redis_url: str = Field(default="redis://localhost:6379", alias="REDIS_URL")

    # API Keys
    api_secret_key: str = Field(alias="API_SECRET_KEY")

    # Feature flags
    enable_new_feature: bool = Field(default=False, alias="ENABLE_NEW_FEATURE")

    model_config = {
        "env_file": ".env",
        "env_file_encoding": "utf-8",
    }

# Create singleton instance at module load
try:
    settings = Settings()
except ValidationError as e:
    print(f"Configuration error:\n{e}")
    sys.exit(1)

Import settings throughout your application:

from myapp.config import settings

def get_database_connection():
    return connect(
        host=settings.db_host,
        port=settings.db_port,
        database=settings.db_name,
    )

Pattern 2: Fail Fast on Missing Configuration

Required settings should crash the application immediately with a clear error.

from pydantic_settings import BaseSettings
from pydantic import Field, ValidationError
import sys

class Settings(BaseSettings):
    # Required - no default means it must be set
    api_key: str = Field(alias="API_KEY")
    database_url: str = Field(alias="DATABASE_URL")

    # Optional with defaults
    log_level: str = Field(default="INFO", alias="LOG_LEVEL")

try:
    settings = Settings()
except ValidationError as e:
    print("=" * 60)
    print("CONFIGURATION ERROR")
    print("=" * 60)
    for error in e.errors():
        field = error["loc"][0]
        print(f"  - {field}: {error['msg']}")
    print("\nPlease set the required environment variables.")
    sys.exit(1)

A clear error at startup is better than a cryptic None failure mid-request.

Pattern 3: Local Development Defaults

Provide sensible defaults for local development while requiring explicit values for secrets.

class Settings(BaseSettings):
    # Has local default, but prod will override
    db_host: str = Field(default="localhost", alias="DB_HOST")
    db_port: int = Field(default=5432, alias="DB_PORT")

    # Always required - no default for secrets
    db_password: str = Field(alias="DB_PASSWORD")
    api_secret_key: str = Field(alias="API_SECRET_KEY")

    # Development convenience
    debug: bool = Field(default=False, alias="DEBUG")

    model_config = {"env_file": ".env"}

Create a .env file for local development (never commit this):

# .env (add to .gitignore)
DB_PASSWORD=local_dev_password
API_SECRET_KEY=dev-secret-key
DEBUG=true

Pattern 4: Namespaced Environment Variables

Prefix related variables for clarity and easy debugging.

# Database configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=myapp
DB_USER=admin
DB_PASSWORD=secret

# Redis configuration
REDIS_URL=redis://localhost:6379
REDIS_MAX_CONNECTIONS=10

# Authentication
AUTH_SECRET_KEY=your-secret-key
AUTH_TOKEN_EXPIRY_SECONDS=3600
AUTH_ALGORITHM=HS256

# Feature flags
FEATURE_NEW_CHECKOUT=true
FEATURE_BETA_UI=false

Makes env | grep DB_ useful for debugging.

Advanced Patterns

Pattern 5: Type Coercion

Pydantic handles common conversions automatically.

from pydantic_settings import BaseSettings
from pydantic import Field, field_validator

class Settings(BaseSettings):
    # Automatically converts "true", "1", "yes" to True
    debug: bool = 
how to use python-configuration
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use python-configuration on Cursor
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1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add python-configuration
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/wshobson/agents --skill python-configurationcopy
The skills CLI fetches python-configuration from GitHub repository wshobson/agents and configures it for Cursor.
3
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│   • Amp
│   • Antigravity
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│ ●Cursor(selected)
│   • Cursor
│   • Windsurf
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/python-configuration
Reload or restart Cursor to activate python-configuration. Access the skill through slash commands (e.g., /python-configuration) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?