feat: impact metrics

Author: kwasniew

README.md

@@ -363,7 +363,8 @@ Histograms measure value distribution (request duration, response size):
 ```python
 client.impact_metrics.define_histogram(
     "request_time_ms",
-    "Time taken to process a request in milliseconds"
+    "Time taken to process a request in milliseconds",
+    [50, 100, 200, 500, 1000]
 )
 
 client.impact_metrics.observe_histogram("request_time_ms", 125)

tests/integration_tests/integration.py

@@ -1,11 +1,9 @@
 # ---
 import logging
-import random
 import sys
 import time
 
 from UnleashClient import UnleashClient
-from UnleashClient.impact_metrics import MetricFlagContext
 
 root = logging.getLogger()
 root.setLevel(logging.DEBUG)
@@ -17,48 +15,10 @@
 root.addHandler(handler)
 # ---
 
-my_client = UnleashClient(
-    url="https://sandbox.getunleash.io/enterprise/api/",
-    app_name="pyIvan",
-    environment="development",
-    custom_headers={
-        "Authorization": "impact-metrics:development.6d70e55dd70dd79f5be3ce97835996000db94ed997c492421effe935"
-    },
-)
+my_client = UnleashClient(url="http://localhost:4242/api", app_name="pyIvan")
 
 my_client.initialize_client()
 
-# Define impact metrics
-my_client.impact_metrics.define_counter("purchases", "Number of purchases made")
-my_client.impact_metrics.define_gauge("active_users", "Current number of active users")
-my_client.impact_metrics.define_histogram(
-    "request_latency", "Request latency in seconds", [0.01, 0.05, 0.1, 0.5, 1.0, 5.0]
-)
-
-# Track active users count
-active_users = 100
-
 while True:
     time.sleep(10)
-    print(f"Demo enabled: {my_client.is_enabled('Demo')}")
-
-    # Create flag context for metrics (ties metrics to feature flag state)
-    flag_context = MetricFlagContext(
-        flag_names=["Demo"],
-        context={"userId": "integration-test-user"},
-    )
-
-    # Increment counter (simulate a purchase)
-    my_client.impact_metrics.increment_counter("purchases", 1, flag_context)
-    print("Incremented purchases counter")
-
-    # Update gauge (simulate active users changing)
-    active_users += random.randint(-10, 15)
-    active_users = max(0, active_users)  # Don't go negative
-    my_client.impact_metrics.update_gauge("active_users", active_users, flag_context)
-    print(f"Updated active_users gauge to {active_users}")
-
-    # Observe histogram (simulate request latency)
-    latency = random.uniform(0.01, 2.0)
-    my_client.impact_metrics.observe_histogram("request_latency", latency, flag_context)
-    print(f"Observed request_latency: {latency:.3f}s")
+    print(my_client.is_enabled("Demo"))