Feature/exp telemetry (#58)

* Added Accessor (#55)

* Added Accessor with comments

* comment and format change

* fixing log

* fixing log length

* async version with tests

* fix test and pylint issue

* Update featuremanagement/aio/_featuremanager.py

Co-authored-by: Ross Grambo <[email protected]>

* Update _featuremanager.py

---------

Co-authored-by: Ross Grambo <[email protected]>

* New OTel Integration (#54)

* New OTel Integration

* fixing issues

* pylint fixes

* fixing mypy issues

* Update _send_telemetry.py

* Update _send_telemetry.py

* Update dev_requirements.txt

* fixing checks

* Update _send_telemetry.py

* Update _send_telemetry.py

* trying mypy fix

* Update _send_telemetry.py

* Update to use accessor

* remove attach_targeting_info

* added tests

* Adding Quart sample

* Added otel to quart sample

* Update requirements.txt

* Updating Version/Status

* review comments

* Update _version.py

---------

Co-authored-by: Ross Grambo <[email protected]>

Author: mrm9084

dev_requirements.txt

@@ -8,3 +8,5 @@ sphinx
 sphinx_rtd_theme
 sphinx-toolbox
 myst_parser
+opentelemetry-api
+opentelemetry-sdk

featuremanagement/_featuremanager.py

@@ -3,7 +3,8 @@
 # Licensed under the MIT License. See License.txt in the project root for
 # license information.
 # -------------------------------------------------------------------------
-from typing import cast, overload, Any, Optional, Dict, Mapping, List
+import logging
+from typing import cast, overload, Any, Optional, Dict, Mapping, List, Tuple
 from ._defaultfilters import TimeWindowFilter, TargetingFilter
 from ._featurefilters import FeatureFilter
 from ._models import EvaluationEvent, Variant, TargetingContext
@@ -14,6 +15,8 @@
     FEATURE_FILTER_NAME,
 )
 
+logger = logging.getLogger(__name__)
+
 
 class FeatureManager(FeatureManagerBase):
     """
@@ -23,6 +26,8 @@ class FeatureManager(FeatureManagerBase):
     :keyword list[FeatureFilter] feature_filters: Custom filters to be used for evaluating feature flags.
     :keyword Callable[EvaluationEvent] on_feature_evaluated: Callback function to be called when a feature flag is
     evaluated.
+    :keyword Callable[[], TargetingContext] targeting_context_accessor: Callback function to get the current targeting
+    context if one isn't provided.
     """
 
     def __init__(self, configuration: Mapping[str, Any], **kwargs: Any):
@@ -56,7 +61,7 @@ def is_enabled(self, feature_flag_id: str, *args: Any, **kwargs: Any) -> bool:
         :return: True if the feature flag is enabled for the given context.
         :rtype: bool
         """
-        targeting_context = self._build_targeting_context(args)
+        targeting_context: TargetingContext = self._build_targeting_context(args)
 
         result = self._check_feature(feature_flag_id, targeting_context, **kwargs)
         if (
@@ -89,7 +94,7 @@ def get_variant(self, feature_flag_id: str, *args: Any, **kwargs: Any) -> Option
         :return: Variant instance.
         :rtype: Variant
         """
-        targeting_context = self._build_targeting_context(args)
+        targeting_context: TargetingContext = self._build_targeting_context(args)
 
         result = self._check_feature(feature_flag_id, targeting_context, **kwargs)
         if (
@@ -102,6 +107,21 @@ def get_variant(self, feature_flag_id: str, *args: Any, **kwargs: Any) -> Option
             self._on_feature_evaluated(result)
         return result.variant
 
+    def _build_targeting_context(self, args: Tuple[Any]) -> TargetingContext:
+        targeting_context = super()._build_targeting_context(args)
+        if targeting_context:
+            return targeting_context
+        if not targeting_context and self._targeting_context_accessor and callable(self._targeting_context_accessor):
+            targeting_context = self._targeting_context_accessor()
+            if targeting_context and isinstance(targeting_context, TargetingContext):
+                return targeting_context
+            logger.warning(
+                "targeting_context_accessor did not return a TargetingContext. Received type %s.",
+                type(targeting_context),
+            )
+
+        return TargetingContext()
+
     def _check_feature_filters(
         self, evaluation_event: EvaluationEvent, targeting_context: TargetingContext, **kwargs: Any
     ) -> None:

featuremanagement/_featuremanagerbase.py

@@ -6,7 +6,7 @@
 import hashlib
 import logging
 from abc import ABC
-from typing import List, Optional, Dict, Tuple, Any, Mapping
+from typing import List, Optional, Dict, Tuple, Any, Mapping, Callable
 from ._models import FeatureFlag, Variant, VariantAssignmentReason, TargetingContext, EvaluationEvent, VariantReference
 
 
@@ -21,6 +21,9 @@
 FEATURE_FILTER_PARAMETERS = "parameters"
 
 
+logger = logging.getLogger(__name__)
+
+
 def _get_feature_flag(configuration: Mapping[str, Any], feature_flag_name: str) -> Optional[FeatureFlag]:
     """
     Gets the FeatureFlag json from the configuration, if it exists it gets converted to a FeatureFlag object.
@@ -77,6 +80,9 @@ def __init__(self, configuration: Mapping[str, Any], **kwargs: Any):
         self._cache: Dict[str, Optional[FeatureFlag]] = {}
         self._copy = configuration.get(FEATURE_MANAGEMENT_KEY)
         self._on_feature_evaluated = kwargs.pop("on_feature_evaluated", None)
+        self._targeting_context_accessor: Optional[Callable[[], TargetingContext]] = kwargs.pop(
+            "targeting_context_accessor", None
+        )
 
     @staticmethod
     def _assign_default_disabled_variant(evaluation_event: EvaluationEvent) -> None:
@@ -218,7 +224,7 @@ def _variant_name_to_variant(self, feature_flag: FeatureFlag, variant_name: Opti
                 return Variant(variant_reference.name, variant_reference.configuration_value)
         return None
 
-    def _build_targeting_context(self, args: Tuple[Any]) -> TargetingContext:
+    def _build_targeting_context(self, args: Tuple[Any]) -> Optional[TargetingContext]:
         """
         Builds a TargetingContext, either returns a provided context, takes the provided user_id to make a context, or
         returns an empty context.
@@ -229,10 +235,12 @@ def _build_targeting_context(self, args: Tuple[Any]) -> TargetingContext:
         if len(args) == 1:
             arg = args[0]
             if isinstance(arg, str):
+                # If the user_id is provided, return a TargetingContext with the user_id
                 return TargetingContext(user_id=arg, groups=[])
             if isinstance(arg, TargetingContext):
+                # If a TargetingContext is provided, return it
                 return arg
-        return TargetingContext()
+        return None
 
     def _assign_allocation(self, evaluation_event: EvaluationEvent, targeting_context: TargetingContext) -> None:
         feature_flag = evaluation_event.feature
@@ -271,7 +279,7 @@ def _check_feature_base(self, feature_flag_id: str) -> Tuple[EvaluationEvent, bo
 
         evaluation_event = EvaluationEvent(feature_flag)
         if not feature_flag:
-            logging.warning("Feature flag %s not found", feature_flag_id)
+            logger.warning("Feature flag %s not found", feature_flag_id)
             # Unknown feature flags are disabled by default
             return evaluation_event, True
 

featuremanagement/aio/_featuremanager.py

@@ -4,7 +4,8 @@
 # license information.
 # -------------------------------------------------------------------------
 import inspect
-from typing import cast, overload, Any, Optional, Dict, Mapping, List
+import logging
+from typing import cast, overload, Any, Optional, Dict, Mapping, List, Tuple
 from ._defaultfilters import TimeWindowFilter, TargetingFilter
 from ._featurefilters import FeatureFilter
 from .._models import EvaluationEvent, Variant, TargetingContext
@@ -15,6 +16,8 @@
     FEATURE_FILTER_NAME,
 )
 
+logger = logging.getLogger(__name__)
+
 
 class FeatureManager(FeatureManagerBase):
     """
@@ -24,6 +27,8 @@ class FeatureManager(FeatureManagerBase):
     :keyword list[FeatureFilter] feature_filters: Custom filters to be used for evaluating feature flags.
     :keyword Callable[EvaluationEvent] on_feature_evaluated: Callback function to be called when a feature flag is
     evaluated.
+    :keyword Callable[[], TargetingContext] targeting_context_accessor: Callback function to get the current targeting
+    context if one isn't provided.
     """
 
     def __init__(self, configuration: Mapping[str, Any], **kwargs: Any):
@@ -57,7 +62,7 @@ async def is_enabled(self, feature_flag_id: str, *args: Any, **kwargs: Any) -> b
         :return: True if the feature flag is enabled for the given context.
         :rtype: bool
         """
-        targeting_context = self._build_targeting_context(args)
+        targeting_context: TargetingContext = await self._build_targeting_context_async(args)
 
         result = await self._check_feature(feature_flag_id, targeting_context, **kwargs)
         if (
@@ -93,7 +98,7 @@ async def get_variant(self, feature_flag_id: str, *args: Any, **kwargs: Any) ->
         :return: Variant instance.
         :rtype: Variant
         """
-        targeting_context = self._build_targeting_context(args)
+        targeting_context: TargetingContext = await self._build_targeting_context_async(args)
 
         result = await self._check_feature(feature_flag_id, targeting_context, **kwargs)
         if (
@@ -109,6 +114,25 @@ async def get_variant(self, feature_flag_id: str, *args: Any, **kwargs: Any) ->
                 self._on_feature_evaluated(result)
         return result.variant
 
+    async def _build_targeting_context_async(self, args: Tuple[Any]) -> TargetingContext:
+        targeting_context = super()._build_targeting_context(args)
+        if targeting_context:
+            return targeting_context
+        if not targeting_context and self._targeting_context_accessor and callable(self._targeting_context_accessor):
+
+            if inspect.iscoroutinefunction(self._targeting_context_accessor):
+                # If a targeting_context_accessor is provided, return the TargetingContext from it
+                targeting_context = await self._targeting_context_accessor()
+            else:
+                targeting_context = self._targeting_context_accessor()
+            if targeting_context and isinstance(targeting_context, TargetingContext):
+                return targeting_context
+            logger.warning(
+                "targeting_context_accessor did not return a TargetingContext. Received type %s.",
+                type(targeting_context),
+            )
+        return TargetingContext()
+
     async def _check_feature_filters(
         self, evaluation_event: EvaluationEvent, targeting_context: TargetingContext, **kwargs: Any
     ) -> None:

featuremanagement/azuremonitor/__init__.py

@@ -3,10 +3,11 @@
 # Licensed under the MIT License. See License.txt in the project root for
 # license information.
 # -------------------------------------------------------------------------
-from ._send_telemetry import publish_telemetry, track_event
+from ._send_telemetry import publish_telemetry, track_event, TargetingSpanProcessor
 
 
 __all__ = [
     "publish_telemetry",
     "track_event",
+    "TargetingSpanProcessor",
 ]

featuremanagement/azuremonitor/_send_telemetry.py

@@ -4,25 +4,38 @@
 # license information.
 # --------------------------------------------------------------------------
 import logging
-from typing import Dict, Optional
-from .._models import EvaluationEvent
+import inspect
+from typing import Any, Callable, Dict, Optional
+from .._models import VariantAssignmentReason, EvaluationEvent, TargetingContext
+
+logger = logging.getLogger(__name__)
 
 try:
     from azure.monitor.events.extension import track_event as azure_monitor_track_event  # type: ignore
+    from opentelemetry.context.context import Context
+    from opentelemetry.sdk.trace import Span, SpanProcessor
 
     HAS_AZURE_MONITOR_EVENTS_EXTENSION = True
 except ImportError:
     HAS_AZURE_MONITOR_EVENTS_EXTENSION = False
-    logging.warning(
+    logger.warning(
         "azure-monitor-events-extension is not installed. Telemetry will not be sent to Application Insights."
     )
+    SpanProcessor = object  # type: ignore
+    Span = object  # type: ignore
+    Context = object  # type: ignore
 
 FEATURE_NAME = "FeatureName"
 ENABLED = "Enabled"
 TARGETING_ID = "TargetingId"
 VARIANT = "Variant"
 REASON = "VariantAssignmentReason"
 
+DEFAULT_WHEN_ENABLED = "DefaultWhenEnabled"
+VERSION = "Version"
+VARIANT_ASSIGNMENT_PERCENTAGE = "VariantAssignmentPercentage"
+MICROSOFT_TARGETING_ID = "Microsoft.TargetingId"
+
 EVENT_NAME = "FeatureEvaluation"
 
 EVALUATION_EVENT_VERSION = "1.0.0"
@@ -64,7 +77,7 @@ def publish_telemetry(evaluation_event: EvaluationEvent) -> None:
     event: Dict[str, Optional[str]] = {
         FEATURE_NAME: feature.name,
         ENABLED: str(evaluation_event.enabled),
-        "Version": EVALUATION_EVENT_VERSION,
+        VERSION: EVALUATION_EVENT_VERSION,
     }
 
     reason = evaluation_event.reason
@@ -75,9 +88,67 @@ def publish_telemetry(evaluation_event: EvaluationEvent) -> None:
     if variant:
         event[VARIANT] = variant.name
 
+    # VariantAllocationPercentage
+    allocation_percentage = 0
+    if reason == VariantAssignmentReason.DEFAULT_WHEN_ENABLED:
+        event[VARIANT_ASSIGNMENT_PERCENTAGE] = str(100)
+        if feature.allocation:
+            for allocation in feature.allocation.percentile:
+                allocation_percentage += allocation.percentile_to - allocation.percentile_from
+            event[VARIANT_ASSIGNMENT_PERCENTAGE] = str(100 - allocation_percentage)
+    elif reason == VariantAssignmentReason.PERCENTILE:
+        if feature.allocation and feature.allocation.percentile:
+            for allocation in feature.allocation.percentile:
+                if variant and allocation.variant == variant.name:
+                    allocation_percentage += allocation.percentile_to - allocation.percentile_from
+            event[VARIANT_ASSIGNMENT_PERCENTAGE] = str(allocation_percentage)
+
+    # DefaultWhenEnabled
+    if feature.allocation and feature.allocation.default_when_enabled:
+        event[DEFAULT_WHEN_ENABLED] = feature.allocation.default_when_enabled
+
     if feature.telemetry:
         for metadata_key, metadata_value in feature.telemetry.metadata.items():
             if metadata_key not in event:
                 event[metadata_key] = metadata_value
 
     track_event(EVENT_NAME, evaluation_event.user, event_properties=event)
+
+
+class TargetingSpanProcessor(SpanProcessor):
+    """
+    A custom SpanProcessor that attaches the targeting ID to the span and baggage when a new span is started.
+    :keyword Callable[[], TargetingContext] targeting_context_accessor: Callback function to get the current targeting
+    context if one isn't provided.
+    """
+
+    def __init__(self, **kwargs: Any) -> None:
+        self._targeting_context_accessor: Optional[Callable[[], TargetingContext]] = kwargs.pop(
+            "targeting_context_accessor", None
+        )
+
+    def on_start(self, span: Span, parent_context: Optional[Context] = None) -> None:
+        """
+        Attaches the targeting ID to the span and baggage when a new span is started.
+
+        :param Span span: The span that was started.
+        :param parent_context: The parent context of the span.
+        """
+        if not HAS_AZURE_MONITOR_EVENTS_EXTENSION:
+            logger.warning("Azure Monitor Events Extension is not installed.")
+            return
+        if self._targeting_context_accessor and callable(self._targeting_context_accessor):
+            if inspect.iscoroutinefunction(self._targeting_context_accessor):
+                logger.warning("Async targeting_context_accessor is not supported.")
+                return
+            targeting_context = self._targeting_context_accessor()
+            if not targeting_context or not isinstance(targeting_context, TargetingContext):
+                logger.warning(
+                    "targeting_context_accessor did not return a TargetingContext. Received type %s.",
+                    type(targeting_context),
+                )
+                return
+            if not targeting_context.user_id:
+                logger.debug("TargetingContext does not have a user ID.")
+                return
+            span.set_attribute(TARGETING_ID, targeting_context.user_id)

project-words.txt

@@ -12,3 +12,4 @@ featuremanagerbase
 quickstart
 rtype
 usefixtures
+urandom

samples/feature_variant_sample_with_targeting_accessor.py

@@ -0,0 +1,36 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import json
+import os
+import sys
+from random_filter import RandomFilter
+from featuremanagement import FeatureManager, TargetingContext
+
+
+script_directory = os.path.dirname(os.path.abspath(sys.argv[0]))
+
+with open(script_directory + "/formatted_feature_flags.json", "r", encoding="utf-8") as f:
+    feature_flags = json.load(f)
+
+USER_ID = "Adam"
+
+
+def my_targeting_accessor() -> TargetingContext:
+    return TargetingContext(user_id=USER_ID)
+
+
+feature_manager = FeatureManager(
+    feature_flags, feature_filters=[RandomFilter()], targeting_context_accessor=my_targeting_accessor
+)
+
+print(feature_manager.is_enabled("TestVariants"))
+print(feature_manager.get_variant("TestVariants").configuration)
+
+USER_ID = "Ellie"
+
+print(feature_manager.is_enabled("TestVariants"))
+print(feature_manager.get_variant("TestVariants").configuration)

samples/formatted_feature_flags.json

@@ -218,6 +218,7 @@
                     },
                     {
                         "name": "False_Override",
+                        "configuration_value": "The Variant False_Override overrides to True",
                         "status_override": "True"
                     }
                 ]