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Pydantic A number is less than the specified minimum value.
Understanding Pydantic and Its Purpose
Pydantic is a data validation and settings management library for Python, leveraging Python's type hints. It is widely used for ensuring that data conforms to defined types and constraints, making it invaluable for applications that require strict data validation. Pydantic models are used to define the structure and constraints of data, which can then be validated automatically.
Identifying the Symptom
When using Pydantic, you might encounter the error code value_error.number.not_ge. This error indicates that a number provided in the data does not meet the minimum value constraint specified in the Pydantic model. The symptom is typically observed when the application raises a validation error, preventing the data from being processed further.
Explaining the Issue
What Does value_error.number.not_ge Mean?
The error code value_error.number.not_ge stands for "value error: number not greater than or equal to." This occurs when a numeric field in your Pydantic model has a constraint specifying a minimum value, and the input data provides a number less than this minimum.
Why Does This Error Occur?
This error typically arises when the input data does not adhere to the constraints defined in the Pydantic model. For instance, if a field is defined to accept numbers greater than or equal to 10, providing a value of 9 will trigger this error.
Steps to Fix the Issue
Review the Pydantic Model
First, examine the Pydantic model to understand the constraints applied to the numeric field. Look for the ge (greater than or equal to) constraint in the model definition. Here is an example:
from pydantic import BaseModel, conint
class ExampleModel(BaseModel):
number: conint(ge=10)
In this example, the number field must be greater than or equal to 10.
Validate the Input Data
Ensure that the input data meets the minimum value constraint. If the model requires a number greater than or equal to 10, verify that the data being passed is 10 or higher. Here is how you can validate the data:
data = {'number': 12}
model_instance = ExampleModel(**data)
In this case, the data is valid because 12 is greater than or equal to 10.
Adjust the Input Data
If the input data does not meet the constraint, adjust it accordingly. For example, if the input is 9, change it to a value that satisfies the constraint, such as 10 or higher.
Additional Resources
For more information on Pydantic and its constraints, you can refer to the official Pydantic documentation. Additionally, for a deeper understanding of Python's type hints, visit the Python typing module documentation.
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Pydantic A number is less than the specified minimum value.
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