Why Numeric validation (gt, lt, ge, le) in FastAPI? - Purpose & Use Cases

The Big Idea

What if your app could instantly reject wrong numbers without extra code?

The Scenario

Imagine you build a web form where users enter their age. You want to make sure the age is between 18 and 99. Without automatic checks, you have to write code to check these limits everywhere.

The Problem

Manually checking numbers everywhere is tiring and easy to forget. If you miss a check, users might enter invalid data, causing errors or wrong results. It also clutters your code with repeated checks.

The Solution

FastAPI lets you declare numeric limits like "greater than" or "less than or equal" right in your data model. It automatically checks these rules for you before your code runs.

Before vs After

✗ Before

if age < 18 or age > 99:
    return {'error': 'Age must be between 18 and 99'}

✓ After

from pydantic import BaseModel, conint

class User(BaseModel):
    age: conint(gt=17, le=99)

What It Enables

This makes your code cleaner and safer by catching invalid numbers early, so you can focus on real features.

Real Life Example

When building a signup form, you can ensure users enter a valid age without writing extra checks, improving user experience and data quality.

Key Takeaways

Manual numeric checks are repetitive and error-prone.

FastAPI's numeric validation handles limits automatically.

This leads to cleaner code and better data validation.

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