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Pydantic A URL field received a URL with an invalid port.

The URL provided in a Pydantic model includes a port number that is not valid.

Understanding Pydantic and Its Purpose

Pydantic is a data validation and settings management library for Python, leveraging Python's type annotations. It is designed to provide data validation and parsing using Python type hints. Pydantic is widely used for ensuring that the data conforms to a specific schema, making it invaluable for applications that require strict data validation, such as web APIs and data processing pipelines.

Identifying the Symptom: value_error.url.port

When working with Pydantic, you might encounter the error code value_error.url.port. This error typically arises when a URL field in your Pydantic model receives a URL with an invalid port number. The symptom is usually a validation error message indicating that the port is not valid.

Details About the Issue

What Causes value_error.url.port?

The value_error.url.port error is triggered when the URL provided includes a port number that does not conform to the expected format. This could be due to a non-numeric port, a port number that is out of the valid range (0-65535), or a malformed URL.

Understanding URL Port Validation

In Pydantic, URL fields are validated to ensure they meet the standard URL format, including the port number. The port must be a valid integer within the range of 0 to 65535. Any deviation from this results in a validation error.

Steps to Fix the Issue

Step 1: Verify the URL Format

Ensure that the URL you are providing is correctly formatted. Check that the port number is a valid integer and falls within the acceptable range. For example, a valid URL with a port might look like http://example.com:8080.

Step 2: Update the Pydantic Model

If the URL is dynamically generated or comes from user input, consider adding additional validation logic to sanitize and verify the URL before it is passed to the Pydantic model. This can be done using Python's built-in URL parsing libraries, such as urllib.parse.

Step 3: Test the Validation

After making changes, test the validation by running your application and providing various URLs to ensure that the error is resolved. You can use unit tests to automate this process and ensure consistent validation.

Additional Resources

For more information on Pydantic and URL validation, consider visiting the official Pydantic documentation. Additionally, the Python urllib.parse documentation provides useful insights into URL parsing and validation.

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