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Pydantic is a data validation and settings management library for Python, leveraging Python's type annotations. It is widely used for data parsing and validation, ensuring that the data conforms to a specified schema. By using Pydantic, developers can define data models with clear constraints and receive automatic validation, making it an essential tool for robust Python applications.
When working with Pydantic, you might encounter the error value_error.frozenset
. This error typically arises during the validation process when a field defined as a frozenset
receives data of a different type. The error message might look something like this:
pydantic.error_wrappers.ValidationError: 1 validation error for ModelName
field_name
value is not a valid frozenset (type=value_error.frozenset)
The value_error.frozenset
error occurs because Pydantic expects the data to match the type specified in the model. A frozenset
is an immutable set in Python, meaning once it is created, it cannot be modified. If the input data is not a frozenset
, Pydantic raises this error to indicate a type mismatch.
frozenset
.To resolve the value_error.frozenset
, follow these steps:
Ensure that the field in your Pydantic model is correctly defined as a frozenset
. Here is an example:
from pydantic import BaseModel
from typing import FrozenSet
class MyModel(BaseModel):
field_name: FrozenSet[int]
Before passing data to the Pydantic model, convert it to a frozenset
if necessary. For example:
input_data = [1, 2, 3]
converted_data = frozenset(input_data)
Pass the converted data to the Pydantic model:
model_instance = MyModel(field_name=converted_data)
For more information on Pydantic and its features, consider visiting the following resources:
By following these steps, you should be able to resolve the value_error.frozenset
and ensure that your data validation process runs smoothly.
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