Request Body
Part of: FastAPI Basics
Learn to handle POST requests with data in the request body using Pydantic models. Create endpoints that can receive and validate complex data structures.
What You'll Learn
- Understand what request bodies are and when to use them
- Create Pydantic models for data validation
- Handle POST requests with request bodies
- Use automatic data validation and serialization
- Combine request bodies with path and query parameters
Theory and Concepts
Request Body
🎯 What You'll Learn
Request bodies allow you to send complex data to your API through POST, PUT, and other HTTP methods. Following the official FastAPI tutorial, you'll learn how to handle structured data with automatic validation.
By the end of this lesson, you'll understand how to:
- Understand what request bodies are and when to use them
- Create Pydantic models for data validation
- Handle POST requests with request bodies
- Use automatic data validation and serialization
- Combine request bodies with path and query parameters
📦 What are Request Bodies?
A request body is data sent by the client to your API. Unlike query parameters that go in the URL, request bodies can contain large amounts of structured data like JSON objects.
When to Use Request Bodies
- Creating data: POST requests to create new items
- Updating data: PUT/PATCH requests to modify existing items
- Complex data: When you need to send more than simple parameters
- Sensitive data: Data that shouldn't appear in URLs
Real-World Examples
- User registration: Sending user details (name, email, password)
- Creating posts: Sending blog post content and metadata
- File uploads: Sending file data and descriptions
- API calls: Sending complex query parameters to search APIs
🏗️ Pydantic Models
FastAPI uses Pydantic models to define the structure of request bodies. This provides automatic validation, serialization, and documentation.
Basic Model Definition
From the official tutorial:
[Code Example]
Key features:
- Type hints: Define the expected data types
- Optional fields: Use | None = None for optional fields
- Automatic validation: FastAPI validates the data automatically
- JSON conversion: Automatically converts to/from JSON
Using the Model
[Code Example]
What happens:
1. Client sends JSON data
2. FastAPI validates it against the Item model
3. Creates an Item instance
4. Passes it to your function
5. Automatically converts the response back to JSON
💡 Official Tutorial Examples
Example 1: Basic Request Body
[Code Example]
Test with JSON:
[Code Example]
Example 2: Request Body + Path Parameters
[Code Example]
URL: POST /items/123
Body: Same JSON as above
Response: Includes both the item_id and all item fields
Example 3: Request Body + Path + Query Parameters
[Code Example]
URL: PUT /items/123?q=search
Body: Item JSON
Response: Combines all three parameter types
🎨 Advanced Pydantic Features
Field Validation
[Code Example]
Nested Models
[Code Example]
Model Configuration
[Code Example]
✨ Best Practices
1. Use Descriptive Model Names
[Code Example]
2. Add Field Descriptions
[Code Example]
3. Use Appropriate Defaults
[Code Example]
🚫 Common Beginner Mistakes
Mistake 1: Forgetting to Import BaseModel
[Code Example]
Mistake 2: Wrong Optional Syntax
[Code Example]
Mistake 3: Not Using the Model Parameter
[Code Example]
Mistake 4: Wrong HTTP Method
[Code Example]
🔍 How FastAPI Handles Request Bodies
Automatic Validation
FastAPI automatically:
1. Reads the request body as JSON
2. Validates the data against your Pydantic model
3. Converts to the appropriate types
4. Creates an instance of your model
5. Passes it to your function
Error Handling
If validation fails, FastAPI automatically returns a detailed error response:
[Code Example]
Interactive Documentation
FastAPI automatically generates interactive docs that show:
- The expected request body structure
- Field types and requirements
- Example values
- Try-it-out functionality
🎉 What's Next?
Congratulations! You now understand how to handle request bodies with Pydantic models. This is essential for building APIs that can create and update data.
You've learned:
- How to create Pydantic models for data validation
- Using POST endpoints with request bodies
- Combining request bodies with path parameters
- Automatic validation and serialization
Coming up next: Query Parameters and String Validations - learning advanced query parameter features with validation!
📖 Additional Resources
- FastAPI Request Body Guide
- Pydantic Documentation
- HTTP Methods Explained
Helpful Hint
Create a Pydantic BaseModel class to define your data structure, then use it as a parameter type in your POST endpoint function!