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.

Practice

1. In FastAPI, what is the main purpose of using Field() in a Pydantic model?

easy

A. To define API routes

B. To create database tables automatically

C. To add validation rules and metadata to model fields

D. To handle HTTP requests directly

Solution

1. Step 1: Understand the role of Pydantic models in FastAPI

   Pydantic models define the data structure and validation for request and response data.

2. Step 2: Identify what Field() adds

   Field() allows adding constraints like min/max length, default values, and descriptions to model fields.

3. Final Answer:

   To add validation rules and metadata to model fields -> Option C

4. Quick Check:

   Field() = validation and metadata [OK]

Hint: Field() is for validation and extra info on model fields [OK]

Common Mistakes:

• Thinking Field() creates routes or handles requests
• Confusing Field() with database table creation
• Assuming Field() is for HTTP methods

2. Which of the following is the correct way to require a string field with a minimum length of 3 in a Pydantic model using Field()?

easy

A. name: str = Field(required=True, length=3)

B. name: str = Field(min=3)

C. name: str = Field(length=3)

D. name: str = Field(min_length=3)

Solution

1. Step 1: Recall the correct parameter for minimum length in Field()

   The correct parameter to set minimum string length is min_length.

2. Step 2: Check each option for correct syntax

   name: str = Field(min_length=3) uses min_length=3, which is correct. Others use invalid or incorrect parameters.

3. Final Answer:

   name: str = Field(min_length=3) -> Option D

4. Quick Check:

   Minimum string length uses min_length [OK]

Hint: Use min_length for string length constraints in Field() [OK]

Common Mistakes:

• Using min instead of min_length for strings
• Using length instead of min_length
• Adding required=True which is not a Field() parameter

3. Given this Pydantic model snippet:

from pydantic import BaseModel, Field

class Item(BaseModel):
    price: float = Field(gt=0)
    name: str = Field(min_length=2, max_length=10)

What happens if you create Item(price=-5, name='A')?

medium

A. Validation error because price is not greater than 0 and name is too short

B. Item is created successfully with given values

C. Validation error only for price, name is accepted

D. Validation error only for name, price is accepted

Solution

1. Step 1: Check the constraints on price

   Price must be greater than 0 (gt=0). Given price is -5, which fails this.

2. Step 2: Check the constraints on name

   Name must have length between 2 and 10. Given name is 'A' (length 1), which fails min_length=2.

3. Final Answer:

   Validation error because price is not greater than 0 and name is too short -> Option A

4. Quick Check:

   Both price and name fail constraints [OK]

Hint: Check all Field constraints; both price and name fail here [OK]

Common Mistakes:

• Assuming only one field causes error
• Ignoring min_length constraint on strings
• Thinking negative price passes gt=0

4. What is wrong with this FastAPI Pydantic model field definition?

from pydantic import BaseModel, Field

class User(BaseModel):
    age: int = Field(min_length=18)

medium

A. Field cannot be used with integers

B. min_length is invalid for integer fields

C. Missing default value for age

D. Age should be a string, not int

Solution

1. Step 1: Understand Field constraints for int type

   Integer fields use gt or ge for minimum value, not min_length.

2. Step 2: Identify the error in the code

   Using min_length on an int field causes a validation error because it applies only to strings or collections.

3. Final Answer:

   min_length is invalid for integer fields -> Option B

4. Quick Check:

   min_length applies to strings, not ints [OK]

Hint: Use gt/ge for numbers, min_length for strings only [OK]

Common Mistakes:

• Using string constraints on numeric fields
• Thinking Field() can't be used with int
• Confusing default value requirement

5. You want to create a FastAPI model for a product with a tags field that must be a list of strings, each string at least 2 characters long. Which is the best way to enforce this using Pydantic Field()?

hard

A. from typing import List
from pydantic import BaseModel, Field, conlist, constr

class Product(BaseModel):
tags: conlist(constr(min_length=2))

B. from typing import List
from pydantic import BaseModel, Field

class Product(BaseModel):
tags: List[str] = Field(min_length=2)

C. from typing import List
from pydantic import BaseModel, Field

class Product(BaseModel):
tags: List[str] = Field(min_items=2)

D. from typing import List
from pydantic import BaseModel, Field

class Product(BaseModel):
tags: List[str] = Field(min_length=2, max_length=10)

Solution

1. Step 1: Understand the requirement for list of strings with string length constraints

   We need to enforce each string in the list to have at least 2 characters.

2. Step 2: Identify how to apply constraints on list items

   Pydantic's constr can constrain strings, and conlist can constrain lists of constrained types.

3. Step 3: Evaluate options

   from typing import List from pydantic import BaseModel, Field, conlist, constr class Product(BaseModel): tags: conlist(constr(min_length=2)) uses conlist(constr(min_length=2)) which correctly enforces each string's min length inside the list. Others either apply min_length to the list itself or incorrectly.

4. Final Answer:

   Use conlist with constr to enforce string length inside list -> Option A

5. Quick Check:

   conlist(constr(min_length=2)) = correct nested constraints [OK]

Hint: Use conlist with constr for list of strings with length limits [OK]

Common Mistakes:

• Applying min_length to the list instead of strings inside
• Not using constr for string constraints
• Confusing min_items with min_length