⚡ Bolt: Remove lock contention in rule synchronization#120
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😎 Merged manually by Abhi Mehrotra (@abhimehro) - details. |
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| assert "h1" in existing_rules |
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| assert "h1" in existing_rules | ||
| assert "h2" in existing_rules |
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test_main.py
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test_main.py
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| existing_rules_lock = threading.Lock() | ||
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| # CRITICAL FIX: Switch to Serial Processing (1 worker) | ||
| # This prevents API rate limits and ensures stability for large folders. |
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| hostnames = ["h1", "h2"] | ||
| existing_rules = set() | ||
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| m.push_rules( |
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| all_rules.update(result) | ||
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| folder_id = future_to_folder[future] | ||
| log.warning(f"Failed to fetch rules for folder ID {folder_id}: {e}") |
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| return None | ||
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| # Optimization 3: Parallelize batch processing |
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| client # Pass the persistent client | ||
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| for folder_data in folder_data_list |
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main.py
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| hostnames = ["h1", "h2"] | ||
| existing_rules = set() | ||
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| m.push_rules( |
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| existing_rules = set() | ||
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| m.push_rules( | ||
| profile_id="p1", |
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Pull request overview
This PR refactors the rule synchronization logic to eliminate lock contention by implementing a scatter-gather pattern. Worker threads now return data instead of updating shared sets under locks, with the main thread aggregating results. This simplifies the code and improves parallelism potential.
Changes:
- Removed all
threading.Lockusage fromget_all_existing_rulesandpush_rules - Refactored worker functions to return results instead of updating shared state
- Updated tests to reflect lock removal and verify correct behavior
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| main.py | Refactored get_all_existing_rules and push_rules to use scatter-gather pattern; removed threading import and lock-related parameters |
| test_main.py | Removed lock-related test assertions; added new test case to verify existing_rules update behavior; updated comments |
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get_all_existing_rulesandpush_rulesto use a scatter-gather pattern. Workers now return data instead of updating a shared set under a lock. The main thread aggregates the results.threading.Lockeliminates lock contention between worker threads, allowing for better parallelism and CPU utilization during rule processing.pytest test_main.pypasses. Verify sync functionality works as expected.PR created automatically by Jules for task 6965379817159253390 started by @abhimehro