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Pydantic value_error.time

A field expected to be a time received an invalid time format.

Understanding Pydantic

Pydantic is a data validation and settings management library for Python, leveraging Python's type annotations. It is designed to validate data and manage settings using Python's type hints, ensuring that the data conforms to the expected structure and types. Pydantic is widely used in applications where data integrity is crucial, such as web APIs and data processing pipelines.

Identifying the Symptom

When working with Pydantic, you might encounter the error code value_error.time. This error typically arises when a field expected to be a time receives an invalid time format. The error message might look something like this:

{
"loc": ["time_field"],
"msg": "invalid time format",
"type": "value_error.time"
}

Explaining the Issue

The value_error.time error indicates that Pydantic attempted to parse a string as a time but failed due to an incorrect format. Pydantic expects time strings to be in the format HH:MM:SS, where:

  • HH is a two-digit hour (00-23).
  • MM is a two-digit minute (00-59).
  • SS is a two-digit second (00-59).

Any deviation from this format, such as missing digits or incorrect separators, will trigger this error.

Steps to Fix the Issue

Step 1: Validate Your Input

Ensure that the input string adheres to the HH:MM:SS format. You can use Python's datetime module to validate and parse time strings:

from datetime import datetime

def validate_time(time_str):
try:
return datetime.strptime(time_str, "%H:%M:%S")
except ValueError:
raise ValueError("Invalid time format. Expected HH:MM:SS")

Step 2: Update Your Pydantic Model

Ensure that your Pydantic model is correctly defined to expect a time field. Here's an example:

from pydantic import BaseModel, validator

class Event(BaseModel):
time_field: str

@validator('time_field')
def check_time_format(cls, v):
try:
datetime.strptime(v, "%H:%M:%S")
except ValueError:
raise ValueError('Invalid time format. Expected HH:MM:SS')
return v

Step 3: Test Your Changes

After making the necessary changes, test your application to ensure that the error is resolved. You can use unit tests to automate this process:

def test_valid_time():
event = Event(time_field="12:30:45")
assert event.time_field == "12:30:45"

def test_invalid_time():
try:
Event(time_field="25:61:61")
except ValueError as e:
assert str(e) == 'Invalid time format. Expected HH:MM:SS'

Additional Resources

For more information on Pydantic and its features, you can refer to the official Pydantic documentation. Additionally, the Python datetime module documentation provides comprehensive details on handling date and time in Python.

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