Field types and constraints in FastAPI - Step-by-Step Execution

Concept Flow - Field types and constraints

Define Pydantic Model

↓

Add Fields with Types

↓

Apply Constraints (e.g., min_length, gt)

↓

Use Model in FastAPI Endpoint

↓

Receive Request Data

↓

Validate Data Against Types & Constraints

↓

Accept or Reject Request Based on Validation

This flow shows how you define fields with types and constraints in a Pydantic model, then FastAPI uses it to validate incoming request data.

Execution Sample

FastAPI

from pydantic import BaseModel, Field

class User(BaseModel):
    name: str = Field(..., min_length=3)
    age: int = Field(..., gt=0)

Defines a User model with a name that must be at least 3 characters and an age greater than 0.

Execution Table

Step	Field	Input Value	Validation Check	Result
1	name	"Al"	min_length=3	Fail: length 2 < 3
2	age	25	gt=0	Pass
3	name	"Alex"	min_length=3	Pass
4	age	-1	gt=0	Fail: -1 not > 0
5	name	"Bob"	min_length=3	Pass
6	age	30	gt=0	Pass

💡 Validation fails if any field does not meet its constraints; otherwise, data is accepted.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6
name	undefined	"Al" (fail)	"Al" (fail)	"Alex" (pass)	"Alex" (pass)	"Bob" (pass)	"Bob" (pass)
age	undefined	undefined	25 (pass)	25 (pass)	-1 (fail)	-1 (fail)	30 (pass)

Key Moments - 3 Insights

Why does the name "Al" fail validation even though it is a string?

Because the min_length constraint requires at least 3 characters, and "Al" has only 2 characters, as shown in execution_table step 1.

What happens if the age is negative like -1?

The gt=0 constraint means age must be greater than 0, so -1 fails validation as shown in execution_table step 4.

Can a field be missing if it uses Field(...)?

No, Field(...) means the field is required. Missing it will cause validation to fail before these steps.

Visual Quiz - 3 Questions

Look at the execution table, what is the validation result for name at step 3?

A Pass

B Fail: length too short

C Fail: wrong type

D Not validated

💡 Hint

Check the 'Result' column for step 3 in the execution_table.

At which step does the age field fail validation?

A Step 2

B Step 4

C Step 6

D No failure

💡 Hint

Look at the 'Validation Check' and 'Result' columns for age in the execution_table.

If the min_length for name was changed to 2, which step's validation result would change?

A Step 3

B Step 4

C Step 1

D Step 6

💡 Hint

Refer to the 'min_length' constraint and the 'name' field validation results in execution_table.

Concept Snapshot

Define fields in Pydantic models with types and constraints.
Use Field(...) to set rules like min_length, gt (greater than).
FastAPI uses these models to check incoming data.
If data breaks rules, FastAPI rejects the request.
Constraints help keep data clean and safe.

Full Transcript

In FastAPI, you define data models using Pydantic. Each field has a type like string or integer. You can add constraints such as minimum length for strings or greater-than for numbers using Field. When FastAPI receives data, it checks each field against these rules. If any field fails, the request is rejected. For example, a name must be at least 3 characters, and age must be greater than zero. This process helps ensure your app only works with valid data.