ddtrace 4.6.0rc3

on Python PyPI

New Features

• azure-api-management: This introduces inferred proxy support for Azure API Management.

• Stats computation: Enable stats computation by default for python 3.14 and above.

• LLM Observability: Adds LLMObs.publish_evaluator() to sync a locally-defined
  LLMJudge evaluator to the Datadog UI as a custom LLM-as-Judge evaluation.

• LLM Observability: Experiments now report their execution status to the backend. Status transitions to running when execution starts, completed on success, failed when tasks or evaluators error with raise_errors=False, and interrupted when the experiment is stopped by an exception. #16713

Bug Fixes

• celery: Propagate distributed tracing headers for tasks that are not registered locally so traces link correctly across workers. #16662

• profiling: This fix resolves an issue where the lock profiler's wrapper class did not support PEP 604 type union syntax (e.g., asyncio.Condition | None). This was causing a TypeError at import time for libraries such as kopf that use union type annotations at class definition time.

• Fix for a potential race condition affecting internal periodic worker threads that could have caused a RuntimeError during forks.

• profiling: Fix lock contention in the profiler's greenlet stack sampler that could cause connection pool exhaustion in gevent-based applications (e.g. gunicorn + gevent + psycopg2). #16657

• Add a timeout to Unix socket connections to prevent thread I/O hangs during pre-fork shutdown.

Other Changes

• LLM Observability: Exports LLMJudge, BooleanStructuredOutput, ScoreStructuredOutput, and CategoricalStructuredOutput to the public ddtrace.llmobs module level.