When span streaming is enabled, `get_start_span_function()` returns `sentry_sdk.traces.start_span`, which has signature `start_span(name: str, attributes: Optional[Attributes] = None, parent_span: Optional[StreamedSpan] = None)`. However, all existing callers (anthropic.py, litellm.py, google_genai, langchain.py, mcp.py, openai_agents, pydantic_ai) invoke the returned function with keyword arguments `op=...`, `name=...`, `origin=...` which the new API doesn't accept. This will cause a TypeError at runtime when span streaming is enabled.

In streaming mode, spans are created via `sentry_sdk.traces.start_span()` but are not used as context managers nor explicitly started via `.start()`. When `.finish()` is called later, it invokes `__exit__()` which tries to access `self._context_manager_state` that was never set (since `__enter__` was never called). This causes an `AttributeError` that is silently caught by `capture_internal_exceptions()`, preventing the span from being properly ended and sent to Sentry.

In streaming mode, spans are created via `sentry_sdk.traces.start_span()` but are not used as context managers nor explicitly started via `.start()`. When `.finish()` is called later, it invokes `__exit__()` which tries to access `self._context_manager_state` that was never set (since `__enter__` was never called). This causes an `AttributeError` that is silently caught by `capture_internal_exceptions()`, preventing the span from being properly ended and sent to Sentry.

The `get_start_span_function()` returns `sentry_sdk.traces.start_span` when streaming mode is enabled, but this function only accepts `name`, `attributes`, and `parent_span` parameters. All callers (in litellm, anthropic, google_genai, langchain, mcp, pydantic_ai, openai_agents integrations) pass additional kwargs like `op=...` and `origin=...` which will cause `TypeError: start_span() got an unexpected keyword argument 'op'`. This breaks all AI integrations when span streaming is enabled.

The `get_start_span_function()` returns `sentry_sdk.traces.start_span` when streaming mode is enabled, but this function only accepts `name`, `attributes`, and `parent_span` parameters. All callers (in litellm, anthropic, google_genai, langchain, mcp, pydantic_ai, openai_agents integrations) pass additional kwargs like `op=...` and `origin=...` which will cause `TypeError: start_span() got an unexpected keyword argument 'op'`. This breaks all AI integrations when span streaming is enabled.

In the `finally` block (line 143-150), the code references `value` when calling `_set_cache_data(cache_span, self, cache_properties, value)` on line 148. However, if `old_execute_command` on line 142 raises an exception, `value` is never assigned, causing an `UnboundLocalError`. This will crash the Redis instrumentation when any Redis operation fails, breaking error handling.

In the `finally` block (line 143-150), the code references `value` when calling `_set_cache_data(cache_span, self, cache_properties, value)` on line 148. However, if `old_execute_command` on line 142 raises an exception, `value` is never assigned, causing an `UnboundLocalError`. This will crash the Redis instrumentation when any Redis operation fails, breaking error handling.

The `graphql_span` is created via `sentry_sdk.traces.start_span()` in span streaming mode (line 192) but is never started before `yield`. When `self.graphql_span.finish()` is called at line 234, it will trigger `__exit__` which accesses `self._context_manager_state` - an attribute that is only set by `__enter__`/`start()`. This will cause an `AttributeError: 'StreamedSpan' object has no attribute '_context_manager_state'` at runtime when span streaming is enabled.

The `graphql_span` is created via `sentry_sdk.traces.start_span()` in span streaming mode (line 192) but is never started before `yield`. When `self.graphql_span.finish()` is called at line 234, it will trigger `__exit__` which accesses `self._context_manager_state` - an attribute that is only set by `__enter__`/`start()`. This will cause an `AttributeError: 'StreamedSpan' object has no attribute '_context_manager_state'` at runtime when span streaming is enabled.

The `graphql_span` is created via `sentry_sdk.traces.start_span()` in span streaming mode (line 192) but is never started before `yield`. When `self.graphql_span.finish()` is called at line 234, it will trigger `__exit__` which accesses `self._context_manager_state` - an attribute that is only set by `__enter__`/`start()`. This will cause an `AttributeError: 'StreamedSpan' object has no attribute '_context_manager_state'` at runtime when span streaming is enabled.

The type annotation `dict[str, Any]` uses PEP 585 syntax which is only available in Python 3.9+. However, the SDK supports Python >= 3.6 (as declared in setup.py). On Python 3.6-3.8, this will cause a `TypeError` at runtime when the annotation is evaluated. The rest of the codebase consistently uses `Dict[str, Any]` from the `typing` module (e.g., lines 384, 453, 536 in this file).

When using the new span streaming mode (`_experiments={"trace_lifecycle": "stream"}`), if an exception occurs during Anthropic API calls, the StreamedSpan created in `_sentry_patched_create_common` will not be properly closed. The span is started via `span.__enter__()` but the error cleanup in the `finally` block only handles legacy `Span` objects (via `isinstance(span, Span)`), leaving `StreamedSpan` objects open. This results in spans without end timestamps and potential data loss.

When using the new span streaming mode (`_experiments={"trace_lifecycle": "stream"}`), if an exception occurs during Anthropic API calls, the StreamedSpan created in `_sentry_patched_create_common` will not be properly closed. The span is started via `span.__enter__()` but the error cleanup in the `finally` block only handles legacy `Span` objects (via `isinstance(span, Span)`), leaving `StreamedSpan` objects open. This results in spans without end timestamps and potential data loss.

When using the new span streaming mode (`_experiments={"trace_lifecycle": "stream"}`), if an exception occurs during Anthropic API calls, the StreamedSpan created in `_sentry_patched_create_common` will not be properly closed. The span is started via `span.__enter__()` but the error cleanup in the `finally` block only handles legacy `Span` objects (via `isinstance(span, Span)`), leaving `StreamedSpan` objects open. This results in spans without end timestamps and potential data loss.

When a Celery task raises control flow exceptions (Retry, Ignore, Reject), the `_set_status("aborted")` call sets `SpanStatus.ERROR` for StreamedSpan. However, these are not actual errors - they are expected control flow mechanisms in Celery. A Retry indicates the task will be retried, Ignore means the result is intentionally ignored, and Reject means the task was rejected. Marking these as ERROR may cause misleading error counts in monitoring dashboards.

In the `_wrap_tracer` function's span streaming path (lines 330-337), the `celery_job` custom sampling context containing task name, args, and kwargs is not set, unlike the legacy path which passes it to `start_transaction`. Users with custom traces_sampler functions that make decisions based on celery job information will not receive this context in span streaming mode, potentially causing unexpected sampling behavior.

In the `finally` block (lines 143-150), when `old_execute_command` raises an exception, `value` is never assigned. The subsequent call to `_set_cache_data(cache_span, self, cache_properties, value)` on line 148 references the undefined variable `value`, causing an `UnboundLocalError`. While this is caught by `capture_internal_exceptions()`, it's a regression from the old code that only called `_set_cache_data` after successful command execution.

In the `finally` block (lines 143-150), when `old_execute_command` raises an exception, `value` is never assigned. The subsequent call to `_set_cache_data(cache_span, self, cache_properties, value)` on line 148 references the undefined variable `value`, causing an `UnboundLocalError`. While this is caught by `capture_internal_exceptions()`, it's a regression from the old code that only called `_set_cache_data` after successful command execution.

The `NoOpStreamedSpan.to_traceparent()` method (line 770-775) returns the real trace_id and span_id from the propagation context, but the `span_id` (line 778-779) and `trace_id` (line 782-783) properties return hardcoded `"000000"` values. This inconsistency means code accessing `.trace_id` or `.span_id` directly gets different data than code parsing `to_traceparent()`. This could cause subtle bugs in trace correlation or header propagation where different parts of the system see different trace identifiers for the same span.

In streaming mode, `span.end()` captures and queues the span for sending via `scope._capture_span(self)` before returning. The `add_http_request_source()` call on line 189 happens after `span.end()` completes, so any attributes it sets (source code information like `code.lineno`, `code.filepath`, etc.) will not be included in the sent span data. This is different from the legacy path where spans are only sent when the transaction finishes.