python-sdk

The best way to structure Python SDK integrations is using a three-layer architecture that provides a clear separation of concerns. This design simplifies the creation of Opik API integrations and message processing workflows.

To handle async operations and error handling in the Opik Python SDK, apply critical gotchas and reference files provided by the skill. These resources offer guidance on proper use of Python's async and sync capabilities alongside robust error management.

Yes, the Opik Python SDK works with OpenAI and Anthropic integrations. It provides specific integration patterns and best practices for connecting these external services into your application's message processing workflow.

To optimize HTTP overhead when processing messages with the Python SDK, utilize the message batching system. This approach groups messages together, significantly reducing the network overhead associated with individual Opik API calls.

For CRUD operations and search functionality in the Opik API, use the provided API method naming conventions. These guidelines maintain consistency and readability across your Python SDK implementation.

To manage dependencies when building Python SDK integrations, follow the advised dependency policy. This approach helps maintain flexibility and avoids unnecessary new additions to your project's environment setup.