Numeric validation (gt, lt, ge, le) in FastAPI

Introduction

Numeric validation helps make sure numbers meet rules like being bigger or smaller than a value. This keeps data clean and safe.

When you want to accept only ages greater than 18 in a form.

When you need to limit a price to be less than 1000 in an online store.

When you want to ensure a rating is at least 1 and at most 5.

When you want to check that a quantity is not negative.

When you want to validate that a discount percentage is between 0 and 50.

Syntax

FastAPI

from pydantic import BaseModel, Field

class Item(BaseModel):
    price: float = Field(..., gt=0, lt=100)
    quantity: int = Field(..., ge=1, le=10)

Use gt for 'greater than', lt for 'less than'.

Use ge for 'greater or equal', le for 'less or equal'.

Examples

This means age must be greater than 18 (not 18 itself).

FastAPI

from pydantic import BaseModel, Field

class UserAge(BaseModel):
    age: int = Field(..., gt=18)

Price must be between 0 and 1000, including 0 and 1000.

FastAPI

from pydantic import BaseModel, Field

class Product(BaseModel):
    price: float = Field(..., ge=0, le=1000)

Score must be between 1 and 5 inclusive.

FastAPI

from pydantic import BaseModel, Field

class Rating(BaseModel):
    score: int = Field(..., ge=1, le=5)

Sample Program

This FastAPI app defines an Item model with numeric validation rules. The price must be greater than 0 and less than 100. The quantity must be between 1 and 10 inclusive. If invalid data is sent, FastAPI returns a clear error message.

FastAPI

from fastapi import FastAPI, Request
from pydantic import BaseModel, Field
from fastapi.responses import JSONResponse
from fastapi.exceptions import RequestValidationError

app = FastAPI()

class Item(BaseModel):
    price: float = Field(..., gt=0, lt=100)
    quantity: int = Field(..., ge=1, le=10)

@app.exception_handler(RequestValidationError)
async def validation_exception_handler(request: Request, exc: RequestValidationError):
    return JSONResponse(
        status_code=422,
        content={"detail": exc.errors(), "body": exc.body},
    )

@app.post("/items/")
async def create_item(item: Item):
    return {"price": item.price, "quantity": item.quantity}

Important Notes

Validation errors automatically return HTTP 422 with details.

Use Field(...) to mark fields as required with validation.

These validations happen before your code runs, so you get clean data.

Summary

Numeric validation ensures numbers meet rules like greater than or less than.

Use gt, lt, ge, and le in Pydantic Field to set these rules.

FastAPI uses these validations automatically to protect your app from bad data.

Practice

1. In FastAPI, which parameter would you use in a Pydantic Field to ensure a number is strictly greater than 10?

easy

A. gt=10

B. lt=10

C. ge=10

D. le=10

Solution

1. Step 1: Understand the meaning of gt

   The gt parameter means "greater than" and excludes the value itself.

2. Step 2: Match the requirement

   Since the question asks for strictly greater than 10, gt=10 is the correct choice.

3. Final Answer:

   gt=10 -> Option A

4. Quick Check:

   Strictly greater than 10 = gt=10 [OK]

Hint: Use gt for strictly greater than, ge for greater or equal [OK]

Common Mistakes:

• Confusing gt with ge and using ge=10 instead
• Using lt or le which mean less than
• Thinking gt includes the number 10

2. Which of the following is the correct syntax to validate a number field in FastAPI to be less than or equal to 100 using Pydantic?

easy

A. Field(ge=100)

B. Field(lt=100)

C. Field(le=100)

D. Field(gt=100)

Solution

1. Step 1: Identify the parameter for less than or equal

   The parameter le stands for "less than or equal to".

2. Step 2: Check the syntax

   The correct syntax is Field(le=100) to enforce the value to be at most 100.

3. Final Answer:

   Field(le=100) -> Option C

4. Quick Check:

   Less than or equal to 100 = le=100 [OK]

Hint: Use le for less or equal, lt for strictly less [OK]

Common Mistakes:

• Using lt=100 which excludes 100
• Using ge or gt which are for greater values
• Writing Field(le100) without equals sign

3. Given this FastAPI model snippet:

from pydantic import BaseModel, Field

class Item(BaseModel):
    price: float = Field(gt=0, le=100)

What happens if you send a request with price=0?

medium

A. Accepted because price is a float

B. Accepted because price is less than or equal to 100

C. Validation error because price must be less than or equal to 0

D. Validation error because price must be greater than 0

Solution

1. Step 1: Analyze the validation rules

   The field has gt=0 (greater than 0) and le=100 (less or equal to 100).

2. Step 2: Check the input value

   Input price is 0, which is not greater than 0, so it violates the gt=0 rule.

3. Final Answer:

   Validation error because price must be greater than 0 -> Option D

4. Quick Check:

   Price 0 fails gt=0 validation [OK]

Hint: gt excludes the number itself; 0 is not > 0 [OK]

Common Mistakes:

• Thinking 0 passes because it is less than 100
• Confusing gt with ge and allowing 0
• Ignoring validation errors in FastAPI

4. You wrote this FastAPI model:

from pydantic import BaseModel, Field

class User(BaseModel):
    age: int = Field(ge=18, lt=65)

But when you send age=65, it passes validation. Why?

medium

A. Because lt=65 means less than 65, so 65 should fail but it passes because you used le=65 instead of lt=65

B. Because lt=65 means less than 65, so 65 should fail but it passes because you used ge incorrectly

C. Because lt=65 means less than 65, so 65 should fail but it passes because the validation is not enforced on int

D. Because lt=65 means age must be less than 65, so 65 should fail but it passes due to a bug

Solution

1. Step 1: Understand the meaning of lt and le

   lt=65 means strictly less than 65, so 65 should fail validation.

2. Step 2: Identify the cause of passing validation

   If 65 passes, likely the code uses le=65 (less or equal) instead of lt=65, allowing 65.

3. Final Answer:

   Because lt=65 means less than 65, so 65 should fail but it passes because you used le=65 instead of lt=65 -> Option A

4. Quick Check:

   lt excludes value; le includes it [OK]

Hint: lt excludes value; le includes it. Check which you used [OK]

Common Mistakes:

• Confusing lt and le parameters
• Assuming validation is not enforced on integers
• Thinking ge affects upper bound

5. You want to create a FastAPI model for a product rating that must be between 1 and 5 inclusive. Which is the correct way to define this field using Pydantic validation?

hard

A. rating: int = Field(gt=1, lt=5)

B. rating: int = Field(ge=1, le=5)

C. rating: int = Field(gt=1, le=5)

D. rating: int = Field(ge=1, lt=5)

Solution

1. Step 1: Understand inclusive range requirements

   Inclusive means the value can be equal to the limits, so use ge (greater or equal) and le (less or equal).

2. Step 2: Match parameters to the range 1 to 5 inclusive

   Use ge=1 and le=5 to allow 1 and 5 as valid values.

3. Final Answer:

   rating: int = Field(ge=1, le=5) -> Option B

4. Quick Check:

   Inclusive range uses ge and le [OK]

Hint: Use ge and le for inclusive ranges, gt and lt for exclusive [OK]

Common Mistakes:

• Using gt or lt excludes boundary values
• Mixing gt with le or ge with lt incorrectly
• Forgetting to include both bounds