feat: experimentation surface — track_event, track_exposure_event, get_experiment_flag

flagsmith/__init__.py

@@ -1,6 +1,6 @@
 from flagsmith import webhooks
-from flagsmith.analytics import PipelineAnalyticsConfig
+from flagsmith.analytics import EventProcessorConfig
 from flagsmith.flagsmith import Flagsmith
 from flagsmith.version import __version__
 
-__all__ = ("Flagsmith", "PipelineAnalyticsConfig", "webhooks", "__version__")
+__all__ = ("Flagsmith", "EventProcessorConfig", "webhooks", "__version__")

flagsmith/analytics.py

@@ -2,7 +2,6 @@
 import json
 import logging
 import threading
-import time
 import typing
 from dataclasses import dataclass
 from datetime import datetime
@@ -18,6 +17,10 @@
 # Used to control how often we send data(in seconds)
 ANALYTICS_TIMER: typing.Final[int] = 10
 
+FLAG_EXPOSURE_EVENT: typing.Final[str] = "$flag_exposure"
+
+DEFAULT_EVENT_API_URL: typing.Final[str] = "https://events.api.flagsmith.com/"
+
 session = FuturesSession(max_workers=4)
 
 
@@ -72,92 +75,95 @@ def track_feature(self, feature_name: str) -> None:
 
 
 @dataclass
-class PipelineAnalyticsConfig:
-    analytics_server_url: str
+class EventProcessorConfig:
+    events_api_url: str = DEFAULT_EVENT_API_URL
     max_buffer_items: int = 1000
     flush_interval_seconds: float = 10.0
 
 
-class PipelineAnalyticsProcessor:
+class EventProcessor:
     """
-    Buffered analytics processor that sends per-evaluation and custom events
-    to the Flagsmith pipeline analytics endpoint in batches.
-
-    Evaluation events are deduplicated within each flush window. Events are
-    flushed periodically via a background timer or when the buffer is full.
+    Buffered event processor that batches custom events and POSTs them to the
+    Flagsmith event endpoint. Flushes on a background timer or when the buffer
+    fills.
     """
 
     def __init__(
         self,
-        config: PipelineAnalyticsConfig,
+        config: EventProcessorConfig,
         environment_key: str,
     ) -> None:
-        url = config.analytics_server_url
+        url = config.events_api_url
         if not url.endswith("/"):
             url = f"{url}/"
-        self._batch_endpoint = f"{url}v1/analytics/batch"
+        self._batch_endpoint = f"{url}v1/events"
         self._environment_key = environment_key
         self._max_buffer = config.max_buffer_items
         self._flush_interval_seconds = config.flush_interval_seconds
 
         self._buffer: typing.List[typing.Dict[str, typing.Any]] = []
-        self._dedup_keys: typing.Dict[str, str] = {}
         self._lock = threading.Lock()
         self._timer: typing.Optional[threading.Timer] = None
 
-    def record_evaluation_event(
+    def track_event(
         self,
-        flag_key: str,
-        enabled: bool,
-        value: typing.Any,
-        identity_identifier: typing.Optional[str] = None,
+        event: str,
+        identifier: typing.Optional[str] = None,
+        value: typing.Optional[typing.Union[str, int, float]] = None,
         traits: typing.Optional[typing.Dict[str, typing.Any]] = None,
+        metadata: typing.Optional[typing.Dict[str, typing.Any]] = None,
+        timestamp: typing.Optional[datetime] = None,
     ) -> None:
-        fingerprint = f"{identity_identifier or 'none'}|{enabled}|{value}"
-        should_flush = False
-
-        with self._lock:
-            if self._dedup_keys.get(flag_key) == fingerprint:
-                return
-            self._dedup_keys[flag_key] = fingerprint
-            self._buffer.append(
-                {
-                    "event_id": flag_key,
-                    "event_type": "flag_evaluation",
-                    "evaluated_at": int(time.time() * 1000),
-                    "identity_identifier": identity_identifier,
-                    "enabled": enabled,
-                    "value": value,
-                    "traits": dict(traits) if traits else None,
-                    "metadata": {"sdk_version": __version__},
-                }
-            )
-            if len(self._buffer) >= self._max_buffer:
-                should_flush = True
-
-        if should_flush:
-            self.flush()
+        self._buffer_event(
+            event=event,
+            feature_name=None,
+            identifier=identifier,
+            value=value,
+            traits=traits,
+            metadata=metadata,
+            timestamp=timestamp,
+        )
 
-    def record_custom_event(
+    def track_exposure_event(
         self,
-        event_name: str,
-        identity_identifier: typing.Optional[str] = None,
+        feature_name: str,
+        identifier: typing.Optional[str] = None,
+        value: typing.Optional[str] = None,
         traits: typing.Optional[typing.Dict[str, typing.Any]] = None,
         metadata: typing.Optional[typing.Dict[str, typing.Any]] = None,
+        timestamp: typing.Optional[datetime] = None,
     ) -> None:
-        should_flush = False
+        self._buffer_event(
+            event=FLAG_EXPOSURE_EVENT,
+            feature_name=feature_name,
+            identifier=identifier,
+            value=value,
+            traits=traits,
+            metadata=metadata,
+            timestamp=timestamp,
+        )
 
+    def _buffer_event(
+        self,
+        event: str,
+        feature_name: typing.Optional[str],
+        identifier: typing.Optional[str],
+        value: typing.Optional[typing.Union[str, int, float]],
+        traits: typing.Optional[typing.Dict[str, typing.Any]],
+        metadata: typing.Optional[typing.Dict[str, typing.Any]],
+        timestamp: typing.Optional[datetime],
+    ) -> None:
+        should_flush = False
         with self._lock:
             self._buffer.append(
                 {
-                    "event_id": event_name,
-                    "event_type": "custom_event",
-                    "evaluated_at": int(time.time() * 1000),
-                    "identity_identifier": identity_identifier,
-                    "enabled": None,
-                    "value": None,
+                    "event": event,
+                    "feature_name": feature_name,
+                    "identifier": identifier,
+                    "value": value,
                     "traits": dict(traits) if traits else None,
                     "metadata": {**(metadata or {}), "sdk_version": __version__},
+                    "timestamp": int((timestamp or datetime.now()).timestamp() * 1000),
                 }
             )
             if len(self._buffer) >= self._max_buffer:
@@ -172,11 +178,8 @@ def flush(self) -> None:
                 return
             events = self._buffer
             self._buffer = []
-            self._dedup_keys.clear()
 
-        payload = json.dumps(
-            {"events": events, "environment_key": self._environment_key}
-        )
+        payload = json.dumps({"events": events})
         try:
             future = session.post(
                 self._batch_endpoint,