Environment-based settings in FastAPI - Mini Project: Build & Apply

Environment-based settings in FastAPI

📖 Scenario: You are building a simple FastAPI application that needs to use different settings depending on the environment it runs in, such as development or production.This is like having different light switches for day and night: you want the app to behave differently without changing the main code.

🎯 Goal: Create a FastAPI app that loads settings from environment variables using pydantic.BaseSettings. You will define a settings class, set a default environment, and use the settings in a route.

📋 What You'll Learn

Create a Settings class inheriting from pydantic.BaseSettings with a debug boolean field

Add a ENVIRONMENT variable to specify the environment name

Load the settings and use the debug value in a FastAPI route response

💡 Why This Matters

🌍 Real World

Many web applications need to behave differently in development, testing, and production. Using environment-based settings helps keep code clean and secure.

💼 Career

Understanding environment-based configuration is essential for backend developers working with FastAPI or any modern web framework.

1

Create the Settings class

Create a class called Settings that inherits from pydantic.BaseSettings. Add a boolean field called debug with a default value False.

FastAPI

from pydantic import BaseSettings

# Create Settings class with debug field
# Your code here

Hint

Use class Settings(BaseSettings): and define debug: bool = False inside.

2

Add environment variable for environment name

Add a variable called ENVIRONMENT and set it to the string 'development'.

FastAPI

from pydantic import BaseSettings

class Settings(BaseSettings):
    debug: bool = False

# Set environment variable
# Your code here

Hint

Just write ENVIRONMENT = 'development' below the class.

3

Load settings and create FastAPI app

Import FastAPI from fastapi. Create a variable called settings by instantiating Settings(). Then create a FastAPI app instance called app.

FastAPI

from pydantic import BaseSettings

class Settings(BaseSettings):
    debug: bool = False

ENVIRONMENT = 'development'

# Import FastAPI and create settings and app
# Your code here

Hint

Use settings = Settings() and app = FastAPI() after importing.

4

Create a route using the settings

Add a GET route at / using @app.get("/"). Define a function called read_root that returns a dictionary with a key debug_mode and value from settings.debug.

FastAPI

from pydantic import BaseSettings
from fastapi import FastAPI

class Settings(BaseSettings):
    debug: bool = False

ENVIRONMENT = 'development'

settings = Settings()
app = FastAPI()

# Add GET route returning debug mode
# Your code here

Hint

Use @app.get("/") and return {"debug_mode": settings.debug} inside the function.

Practice

1. What is the main purpose of using environment-based settings in a FastAPI application?

easy

A. To change app behavior without modifying the code

B. To speed up the app's response time

C. To add more routes automatically

D. To create user interfaces dynamically

Solution

1. Step 1: Understand environment-based settings concept

   Environment-based settings allow configuration changes without changing the code itself.

2. Step 2: Identify the main benefit in FastAPI

   This lets the app behave differently in development, testing, or production by just changing environment variables.

3. Final Answer:

   To change app behavior without modifying the code -> Option A

4. Quick Check:

   Environment-based settings = change behavior without code change [OK]

Hint: Think: change settings without touching code [OK]

Common Mistakes:

• Confusing settings with performance improvements
• Thinking it automatically adds routes
• Assuming it creates UI elements

2. Which of the following is the correct way to define a settings class using Pydantic's BaseSettings in FastAPI?

easy

A. class Settings(BaseModel):\n debug: bool = False

B. class Settings(BaseSettings):\n debug: bool = False

C. class Settings(dict):\n debug: bool = False

D. class Settings(object):\n debug: bool = False

Solution

1. Step 1: Recall correct base class for environment settings

   Pydantic's BaseSettings is designed for environment-based config loading.

2. Step 2: Check class definition syntax

   Using BaseSettings with typed attributes and default values is correct.

3. Final Answer:

   class Settings(BaseSettings):\n debug: bool = False -> Option B

4. Quick Check:

   Use BaseSettings for env config classes [OK]

Hint: Use BaseSettings, not BaseModel, for env configs [OK]

Common Mistakes:

• Using BaseModel instead of BaseSettings
• Inheriting from dict or object directly
• Missing type annotations

3. Given this FastAPI settings class and .env file, what will be the value of settings.debug?

class Settings(BaseSettings):
    debug: bool = False

settings = Settings()

.env file content:

DEBUG=true

medium

A. False

B. Error: missing attribute

C. True

D. None

Solution

1. Step 1: Understand BaseSettings behavior with .env

   BaseSettings reads environment variables and overrides defaults if present.

2. Step 2: Check .env value for DEBUG

   The .env file sets DEBUG=true, which overrides the default False.

3. Final Answer:

   True -> Option C

4. Quick Check:

   .env overrides default values in BaseSettings [OK]

Hint: .env values override defaults in BaseSettings [OK]

Common Mistakes:

• Assuming default stays despite .env
• Confusing string 'true' with boolean
• Expecting error if .env exists

4. What is wrong with this FastAPI settings code that tries to load environment variables?

from pydantic import BaseSettings

class Settings(BaseSettings):
    api_key: str

settings = Settings()

Assuming no environment variable API_KEY is set.

medium

A. It will silently ignore missing api_key

B. It will set api_key to an empty string

C. It will set api_key to None

D. It will raise a validation error because api_key is required but missing

Solution

1. Step 1: Check required fields in BaseSettings

   Fields without defaults are required and must be provided via env or arguments.

2. Step 2: Consider missing environment variable

   Since API_KEY is not set, BaseSettings raises a validation error on instantiation.

3. Final Answer:

   It will raise a validation error because api_key is required but missing -> Option D

4. Quick Check:

   Missing required env vars cause validation errors [OK]

Hint: Required fields without defaults must be set in env [OK]

Common Mistakes:

• Expecting default empty string or None
• Thinking missing vars are ignored
• Assuming no error on missing required field

5. You want to create a FastAPI settings class that loads a database URL from environment variables but uses a default if none is set. Which code correctly implements this with Pydantic's BaseSettings?

hard

A. class Settings(BaseSettings):\n database_url: str = 'sqlite:///default.db'

B. class Settings(BaseSettings):\n database_url: str

C. class Settings(BaseSettings):\n database_url: str = Field(default_factory=lambda: 'sqlite:///default.db')

D. class Settings(BaseSettings):\n database_url: Optional[str] = None

Solution

1. Step 1: Understand default values with environment override

   Using a default value directly allows configuration from environment variables if present, falling back to the default otherwise.

2. Step 2: Compare options for correct default and override behavior

   class Settings(BaseSettings):\n database_url: str = 'sqlite:///default.db' uses a direct default value, overridden by DATABASE_URL env var if set.

3. Final Answer:

   class Settings(BaseSettings):\n database_url: str = 'sqlite:///default.db' -> Option A

4. Quick Check:

   Direct default = env override if present [OK]

Hint: Direct field default: str = 'default' for env override [OK]

Common Mistakes:

• Leaving field required without default
• Using Field(default_factory=...) unnecessarily (requires Field import)
• Using Optional[str] = None (defaults to None)