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Avoiding Mutable Default Errors in Dataclasses with Deepgram SDKs

In Python, mutable default arguments in functions or dataclasses can lead to unintended behavior and errors. This generally occurs in Deepgram's SDKs when a mutable object is used as a default value. To prevent such issues, understand how to properly configure dataclass defaults, particularly if you're using Python SDKs with configurable settings like Deepgram’s unstable or development versions.

Common Error: ValueError in Dataclasses

A ValueError occurs when an attempt is made to use a mutable object (like a list) as a default value in a dataclass field. This can happen when using Deepgram's SDKs, due to some mutable defaults being improperly handled. The error message may look like:

ValueError: mutable default <type> for field 'provider' is not allowed: use default_factory

How To Resolve Mutable Default Errors

To address this, you can:

  1. Upgrade to the Latest Stable SDK Version:

    • Ensure you are using the latest stable version of the Deepgram Python SDK. Refer to the Python SDK releases page for the latest version.

  2. Utilize default_factory:

    • Replace any mutable default arguments in your dataclass fields with default_factory. This is an alternative approach for specifying defaults that involve functions.

Example

Assume you're defining a dataclass field for AgentOptions that currently uses a list in a manner that causes the error:

from dataclasses import dataclass, field
from typing import List

@dataclass
class AgentOptions:
    allowed_providers: List[str] = field(default_factory=list)

Here, field(default_factory=list) ensures a new list is created for each instance.

  1. Review the SDK Documentation:

Troubleshooting Tips

If after upgrading and adjusting your dataclass fields, the issue persists:

  • Consult SDK Documentation: Double-check the Deepgram SDK's documentation for any additional configuration guidance.
  • Reach Out for Support: If problems continue, connect with the Deepgram community on Discord or reach out to support for tailored assistance.

Conclusion

Understanding how to properly manage defaults in Python dataclasses is critical when working with configurable options in SDKs like Deepgram's. By ensuring you are using default_factory for mutable types, you can effectively avoid common pitfalls related to mutable default arguments.

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