ref: Drop set_measurement

Author: sentrivana

MIGRATION_GUIDE.md

@@ -137,6 +137,7 @@ Looking to upgrade from Sentry SDK 2.x to 3.x? Here's a comprehensive list of wh
 - The `enable_tracing` `init` option has been removed. Configure `traces_sample_rate` directly.
 - The `propagate_traces` `init` option has been removed. Use `trace_propagation_targets` instead.
 - The `custom_sampling_context` parameter of `start_transaction` has been removed. Use `attributes` instead to set key-value pairs of data that should be accessible in the traces sampler. Note that span attributes need to conform to the [OpenTelemetry specification](https://opentelemetry.io/docs/concepts/signals/traces/#attributes), meaning only certain types can be set as values.
+- `set_measurement` has been removed.
 - The PyMongo integration no longer sets tags. The data is still accessible via span attributes.
 - The PyMongo integration doesn't set `operation_ids` anymore. The individual IDs (`operation_id`, `request_id`, `session_id`) are now accessible as separate span attributes.
 - `sentry_sdk.metrics` and associated metrics APIs have been removed as Sentry no longer accepts metrics data in this form. See https://sentry.zendesk.com/hc/en-us/articles/26369339769883-Upcoming-API-Changes-to-Metrics

sentry_sdk/__init__.py

@@ -36,7 +36,6 @@
     "set_context",
     "set_extra",
     "set_level",
-    "set_measurement",
     "set_tag",
     "set_tags",
     "set_user",

sentry_sdk/_types.py

@@ -107,7 +107,6 @@ def substituted_because_contains_sensitive_data(cls):
     from typing import Callable
     from typing import Dict
     from typing import Mapping
-    from typing import NotRequired
     from typing import Optional
     from typing import Type
     from typing_extensions import Literal, TypedDict
@@ -120,45 +119,6 @@ class SDKInfo(TypedDict):
     # "critical" is an alias of "fatal" recognized by Relay
     LogLevelStr = Literal["fatal", "critical", "error", "warning", "info", "debug"]
 
-    DurationUnit = Literal[
-        "nanosecond",
-        "microsecond",
-        "millisecond",
-        "second",
-        "minute",
-        "hour",
-        "day",
-        "week",
-    ]
-
-    InformationUnit = Literal[
-        "bit",
-        "byte",
-        "kilobyte",
-        "kibibyte",
-        "megabyte",
-        "mebibyte",
-        "gigabyte",
-        "gibibyte",
-        "terabyte",
-        "tebibyte",
-        "petabyte",
-        "pebibyte",
-        "exabyte",
-        "exbibyte",
-    ]
-
-    FractionUnit = Literal["ratio", "percent"]
-    MeasurementUnit = Union[DurationUnit, InformationUnit, FractionUnit, str]
-
-    MeasurementValue = TypedDict(
-        "MeasurementValue",
-        {
-            "value": float,
-            "unit": NotRequired[Optional[MeasurementUnit]],
-        },
-    )
-
     Event = TypedDict(
         "Event",
         {
@@ -180,7 +140,6 @@ class SDKInfo(TypedDict):
             "level": LogLevelStr,
             "logentry": Mapping[str, object],
             "logger": str,
-            "measurements": dict[str, MeasurementValue],
             "message": str,
             "modules": dict[str, str],
             "monitor_config": Mapping[str, object],

sentry_sdk/ai/monitoring.py

@@ -106,14 +106,14 @@ def record_token_usage(
     if ai_pipeline_name:
         span.set_attribute("ai.pipeline.name", ai_pipeline_name)
     if prompt_tokens is not None:
-        span.set_measurement("ai_prompt_tokens_used", value=prompt_tokens)
+        span.set_attribute("ai.prompt_tokens_used", prompt_tokens)
     if completion_tokens is not None:
-        span.set_measurement("ai_completion_tokens_used", value=completion_tokens)
+        span.set_attribute("ai.completion_tokens_used", completion_tokens)
     if (
         total_tokens is None
         and prompt_tokens is not None
         and completion_tokens is not None
     ):
         total_tokens = prompt_tokens + completion_tokens
     if total_tokens is not None:
-        span.set_measurement("ai_total_tokens_used", total_tokens)
+        span.set_attribute("ai.total_tokens_used", total_tokens)

sentry_sdk/api.py

@@ -59,7 +59,6 @@
     "set_context",
     "set_extra",
     "set_level",
-    "set_measurement",
     "set_tag",
     "set_tags",
     "set_user",
@@ -287,13 +286,6 @@ def start_transaction(
     )
 
 
-def set_measurement(name, value, unit=""):
-    # type: (str, float, sentry_sdk._types.MeasurementUnit) -> None
-    transaction = get_current_scope().root_span
-    if transaction is not None:
-        transaction.set_measurement(name, value, unit)
-
-
 def get_current_span(scope=None):
     # type: (Optional[Scope]) -> Optional[sentry_sdk.tracing.Span]
     """

sentry_sdk/opentelemetry/consts.py

@@ -26,7 +26,6 @@ class SentrySpanAttribute:
     DESCRIPTION = "sentry.description"
     OP = "sentry.op"
     ORIGIN = "sentry.origin"
-    MEASUREMENT = "sentry.measurement"
     TAG = "sentry.tag"
     NAME = "sentry.name"
     SOURCE = "sentry.source"

sentry_sdk/opentelemetry/span_processor.py

@@ -304,10 +304,6 @@ def _common_span_transaction_attributes_as_json(self, span):
             "timestamp": convert_from_otel_timestamp(span.end_time),
         }  # type: Event
 
-        measurements = extract_span_attributes(span, SentrySpanAttribute.MEASUREMENT)
-        if measurements:
-            common_json["measurements"] = measurements
-
         tags = extract_span_attributes(span, SentrySpanAttribute.TAG)
         if tags:
             common_json["tags"] = tags

sentry_sdk/opentelemetry/utils.py

@@ -309,15 +309,7 @@ def extract_span_attributes(span, namespace):
     for attr, value in (span.attributes or {}).items():
         if attr.startswith(namespace):
             key = attr[len(namespace) + 1 :]
-
-            if namespace == SentrySpanAttribute.MEASUREMENT:
-                value = cast("tuple[str, str]", value)
-                extracted_attrs[key] = {
-                    "value": float(value[0]),
-                    "unit": value[1],
-                }
-            else:
-                extracted_attrs[key] = value
+            extracted_attrs[key] = value
 
     return extracted_attrs
 

sentry_sdk/tracing.py

@@ -65,7 +65,6 @@
     R = TypeVar("R")
 
     from sentry_sdk._types import (
-        MeasurementUnit,
         SamplingContext,
     )
 
@@ -150,10 +149,6 @@ def finish(
         # type: (...) -> None
         pass
 
-    def set_measurement(self, name, value, unit=""):
-        # type: (str, float, MeasurementUnit) -> None
-        pass
-
     def set_context(self, key, value):
         # type: (str, dict[str, Any]) -> None
         pass
@@ -540,13 +535,6 @@ def set_status(self, status):
         else:
             self._otel_span.set_status(Status(otel_status, otel_description))
 
-    def set_measurement(self, name, value, unit=""):
-        # type: (str, float, MeasurementUnit) -> None
-        # Stringify value here since OTel expects all seq items to be of one type
-        self.set_attribute(
-            f"{SentrySpanAttribute.MEASUREMENT}.{name}", (str(value), unit)
-        )
-
     def set_thread(self, thread_id, thread_name):
         # type: (Optional[int], Optional[str]) -> None
         if thread_id is not None:

tests/integrations/anthropic/test_anthropic.py

@@ -127,9 +127,9 @@ def test_nonstreaming_create_message(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 20
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 30
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.completion_tokens_used"] == 20
+    assert span["data"]["ai.total_tokens_used"] == 30
     assert span["data"]["ai.streaming"] is False
 
 
@@ -197,9 +197,9 @@ async def test_nonstreaming_create_message_async(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 20
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 30
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.completion_tokens_used"] == 20
+    assert span["data"]["ai.total_tokens_used"] == 30
     assert span["data"]["ai.streaming"] is False
 
 
@@ -299,9 +299,9 @@ def test_streaming_create_message(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 30
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 40
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.completion_tokens_used"] == 30
+    assert span["data"]["ai.total_tokens_used"] == 40
     assert span["data"]["ai.streaming"] is True
 
 
@@ -404,9 +404,9 @@ async def test_streaming_create_message_async(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 30
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 40
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.completion_tokens_used"] == 30
+    assert span["data"]["ai.total_tokens_used"] == 40
     assert span["data"]["ai.streaming"] is True
 
 
@@ -536,9 +536,9 @@ def test_streaming_create_message_with_input_json_delta(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 366
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 51
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 417
+    assert span["data"]["ai.prompt_tokens_used"] == 366
+    assert span["data"]["ai.completion_tokens_used"] == 51
+    assert span["data"]["ai.total_tokens_used"] == 417
     assert span["data"]["ai.streaming"] is True
 
 
@@ -675,9 +675,9 @@ async def test_streaming_create_message_with_input_json_delta_async(
         assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
         assert SPANDATA.AI_RESPONSES not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 366
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 51
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 417
+    assert span["data"]["ai.prompt_tokens_used"] == 366
+    assert span["data"]["ai.completion_tokens_used"] == 51
+    assert span["data"]["ai.total_tokens_used"] == 417
     assert span["data"]["ai.streaming"] is True
 
 
@@ -822,11 +822,6 @@ def test_add_ai_data_to_span_with_input_json_delta(sentry_init, capture_events):
                 content_blocks=["{'test': 'data',", "'more': 'json'}"],
             )
 
-            # assert span._data.get("ai.streaming") is True
-            # assert span._measurements.get("ai_prompt_tokens_used")["value"] == 10
-            # assert span._measurements.get("ai_completion_tokens_used")["value"] == 20
-            # assert span._measurements.get("ai_total_tokens_used")["value"] == 30
-
     (event,) = events
 
     assert len(event["spans"]) == 1
@@ -836,6 +831,6 @@ def test_add_ai_data_to_span_with_input_json_delta(sentry_init, capture_events):
         [{"type": "text", "text": "{'test': 'data','more': 'json'}"}]
     )
     assert span["data"]["ai.streaming"] is True
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 20
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 30
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.completion_tokens_used"] == 20
+    assert span["data"]["ai.total_tokens_used"] == 30

tests/integrations/cohere/test_cohere.py

@@ -64,9 +64,9 @@ def test_nonstreaming_chat(
         assert "ai.input_messages" not in span["data"]
         assert "ai.responses" not in span["data"]
 
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 20
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 30
+    assert span["data"]["ai.completion_tokens_used"] == 10
+    assert span["data"]["ai.prompt_tokens_used"] == 20
+    assert span["data"]["ai.total_tokens_used"] == 30
 
 
 # noinspection PyTypeChecker
@@ -136,9 +136,9 @@ def test_streaming_chat(sentry_init, capture_events, send_default_pii, include_p
         assert "ai.input_messages" not in span["data"]
         assert "ai.responses" not in span["data"]
 
-    assert span["measurements"]["ai_completion_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 20
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 30
+    assert span["data"]["ai.completion_tokens_used"] == 10
+    assert span["data"]["ai.prompt_tokens_used"] == 20
+    assert span["data"]["ai.total_tokens_used"] == 30
 
 
 def test_bad_chat(sentry_init, capture_events):
@@ -200,8 +200,8 @@ def test_embed(sentry_init, capture_events, send_default_pii, include_prompts):
     else:
         assert "ai.input_messages" not in span["data"]
 
-    assert span["measurements"]["ai_prompt_tokens_used"]["value"] == 10
-    assert span["measurements"]["ai_total_tokens_used"]["value"] == 10
+    assert span["data"]["ai.prompt_tokens_used"] == 10
+    assert span["data"]["ai.total_tokens_used"] == 10
 
 
 def test_span_origin_chat(sentry_init, capture_events):

tests/integrations/huggingface_hub/test_huggingface_hub.py

@@ -74,7 +74,7 @@ def test_nonstreaming_chat_completion(
         assert "ai.responses" not in span["data"]
 
     if details_arg:
-        assert span["measurements"]["ai_total_tokens_used"]["value"] == 10
+        assert span["data"]["ai.total_tokens_used"] == 10
 
 
 @pytest.mark.parametrize(
@@ -133,7 +133,7 @@ def test_streaming_chat_completion(
         assert "ai.responses" not in span["data"]
 
     if details_arg:
-        assert span["measurements"]["ai_total_tokens_used"]["value"] == 10
+        assert span["data"]["ai.total_tokens_used"] == 10
 
 
 def test_bad_chat_completion(sentry_init, capture_events):

tests/integrations/langchain/test_langchain.py

@@ -179,12 +179,13 @@ def test_langchain_agent(
     assert len(list(x for x in tx["spans"] if x["op"] == "ai.run.langchain")) > 0
 
     if use_unknown_llm_type:
-        assert "ai_prompt_tokens_used" in chat_spans[0]["measurements"]
-        assert "ai_total_tokens_used" in chat_spans[0]["measurements"]
+        assert "ai.prompt_tokens_used" in chat_spans[0]["data"]
+        assert "ai.total_tokens_used" in chat_spans[0]["data"]
     else:
         # important: to avoid double counting, we do *not* measure
         # tokens used if we have an explicit integration (e.g. OpenAI)
-        assert "measurements" not in chat_spans[0]
+        assert "ai.prompt_tokens_used" not in chat_spans[0]["data"]
+        assert "ai.total_tokens_used" not in chat_spans[0]["data"]
 
     if send_default_pii and include_prompts:
         assert "You are very powerful" in chat_spans[0]["data"]["ai.input_messages"]