Individual stats for account rate limits

RATE_LIMITER_ENHANCEMENTS.md

@@ -24,7 +24,7 @@ Tracks application-level rate limits across all users.
 ```
 
 ### 2. **X-Ad-Account-Usage** (Ad Account Specific)
-Tracks rate limits for specific ad accounts.
+Tracks rate limits for specific ad accounts. **Stored per account ID** to support multiple accounts.
 
 **Fields:**
 - `acc_id_util_pct`: Percentage of ad account usage (0-100)
@@ -40,6 +40,8 @@ Tracks rate limits for specific ad accounts.
 }
 ```
 
+**Note:** Metrics are tracked separately for each ad account in a dictionary keyed by account ID (e.g., `act_123456789`).
+
 ### 3. **X-Business-Use-Case-Usage** (Business Use Case Limits)
 Tracks rate limits per business use case (ads_insights, ads_management, etc.).
 
@@ -156,6 +158,17 @@ logging.basicConfig(
 )
 ```
 
+### Updating Usage with Account ID
+When calling `update_usage()`, you can optionally provide an account ID to track per-account metrics:
+
+```python
+# Option 1: Provide account_id explicitly
+limiter.update_usage(response, account_id='act_123456789')
+
+# Option 2: Let the limiter try to extract it from the response
+limiter.update_usage(response)  # Will attempt to extract account_id
+```
+
 ### Access New Metrics
 All metrics are available through the `get_stats()` method:
 
@@ -163,10 +176,14 @@ All metrics are available through the `get_stats()` method:
 stats = limiter.get_stats()
 
 print(f"App call count: {stats['app_call_count']}%")
-print(f"Ad account usage: {stats['ad_account_usage_pct']}%")
-print(f"Reset in: {stats['reset_time_duration']}s")
 print(f"Regain access in: {stats['estimated_time_to_regain_access']} min")
-print(f"API tier: {stats['ads_api_access_tier']}")
+
+# Per-account metrics
+for account_id, usage in stats['ad_account_usage'].items():
+    print(f"Account {account_id}:")
+    print(f"  Usage: {usage['acc_id_util_pct']}%")
+    print(f"  Reset in: {usage['reset_time_duration']}s")
+    print(f"  API tier: {usage['ads_api_access_tier']}")
 
 # Business use case details
 for buc in stats['buc_usage']: