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[loop-generated] [performance] Implement async/await patterns for I/O operations #1408

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opened 2026-03-24 13:01:12 +00:00 by Timmy · 1 comment
Timmy commented 2026-03-24 13:01:12 +00:00
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Problem

Many I/O operations in the codebase are synchronous and blocking, causing performance bottlenecks:

  • Database queries block request threads
  • HTTP API calls to Gitea/external services block processing
  • File system operations (reading large logs, configs) cause delays
  • Subprocess calls (git, tox) block agent loops

Analysis

Current bottlenecks identified:

  • src/infrastructure/router/cascade.py - API calls block routing
  • src/dashboard/routes/*.py - Database queries block web responses
  • src/timmy/tools/gitea_integration.py - Gitea API calls block agent work
  • src/timmy/agents/kimi_agent.py - Git operations block delegation

Proposed Solution

Implement async/await patterns systematically:

  1. Database Layer (src/infrastructure/database/)

    • Convert SQLAlchemy queries to async
    • Add connection pooling with async drivers
    • Implement async transaction management

  2. HTTP Client Layer (src/infrastructure/http/)

    • Replace requests with aiohttp
    • Add async retry policies
    • Implement connection pooling

  3. Agent Operations (src/timmy/agents/)

    • Async git operations
    • Concurrent API calls
    • Non-blocking subprocess execution

  4. Web Framework (src/dashboard/)

    • Convert Flask routes to async
    • Or migrate to FastAPI for native async support
    • Async template rendering

Benefits

  • 30-50% performance improvement on I/O-heavy operations
  • Better resource utilization - threads not blocked on I/O
  • Improved user experience - faster web interface responses
  • Higher throughput - more concurrent operations possible

Implementation Strategy

Phase 1: Core infrastructure (database, HTTP client)
Phase 2: Agent operations (git, API calls)
Phase 3: Web interface (routes, templates)
Phase 4: Performance testing and optimization

Acceptance Criteria

  • Database queries are non-blocking
  • HTTP API calls are asynchronous
  • Web interface responds faster (< 500ms typical)
  • Agent loops process more work concurrently
  • All existing functionality preserved
  • Performance benchmarks show >25% improvement
  • Memory usage remains stable

Priority

HIGH - Performance improvements directly impact user experience and system scalability.

Lines of code is a liability. Delete as much as you create.

## Problem Many I/O operations in the codebase are synchronous and blocking, causing performance bottlenecks: - Database queries block request threads - HTTP API calls to Gitea/external services block processing - File system operations (reading large logs, configs) cause delays - Subprocess calls (git, tox) block agent loops ## Analysis Current bottlenecks identified: - `src/infrastructure/router/cascade.py` - API calls block routing - `src/dashboard/routes/*.py` - Database queries block web responses - `src/timmy/tools/gitea_integration.py` - Gitea API calls block agent work - `src/timmy/agents/kimi_agent.py` - Git operations block delegation ## Proposed Solution Implement async/await patterns systematically: 1. **Database Layer** (`src/infrastructure/database/`) - Convert SQLAlchemy queries to async - Add connection pooling with async drivers - Implement async transaction management 2. **HTTP Client Layer** (`src/infrastructure/http/`) - Replace requests with aiohttp - Add async retry policies - Implement connection pooling 3. **Agent Operations** (`src/timmy/agents/`) - Async git operations - Concurrent API calls - Non-blocking subprocess execution 4. **Web Framework** (`src/dashboard/`) - Convert Flask routes to async - Or migrate to FastAPI for native async support - Async template rendering ## Benefits - **30-50% performance improvement** on I/O-heavy operations - **Better resource utilization** - threads not blocked on I/O - **Improved user experience** - faster web interface responses - **Higher throughput** - more concurrent operations possible ## Implementation Strategy Phase 1: Core infrastructure (database, HTTP client) Phase 2: Agent operations (git, API calls) Phase 3: Web interface (routes, templates) Phase 4: Performance testing and optimization ## Acceptance Criteria - [ ] Database queries are non-blocking - [ ] HTTP API calls are asynchronous - [ ] Web interface responds faster (< 500ms typical) - [ ] Agent loops process more work concurrently - [ ] All existing functionality preserved - [ ] Performance benchmarks show >25% improvement - [ ] Memory usage remains stable ## Priority **HIGH** - Performance improvements directly impact user experience and system scalability. Lines of code is a liability. Delete as much as you create.
Timmy commented 2026-03-24 13:11:36 +00:00
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Implementation Plan

This is a performance optimization issue to implement async/await patterns for I/O operations.

Files to Modify:

  1. src/infrastructure/router/cascade.py - Add async request handling
  2. src/timmy/tools/_registry.py - Make tool loading async
  3. src/dashboard/services/scoring/ - Async database operations
  4. src/infrastructure/hermes/monitor.py - Async monitoring calls

Implementation Steps:

  1. Audit Current I/O Patterns: Identify synchronous file I/O, HTTP requests, database calls
  2. Add asyncio Dependencies: Update imports and function signatures
  3. Convert Functions: Transform sync functions to async/await pattern
  4. Update Callers: Ensure all callers use await properly
  5. Add Async Context Managers: For file operations and HTTP sessions
  6. Test Performance: Benchmark before/after with concurrent operations

Acceptance Criteria:

  • All file I/O operations use async file handles
  • HTTP requests use aiohttp or httpx
  • Database operations use async drivers
  • No blocking I/O calls in main thread
  • Performance tests show improvement with concurrent operations
  • All existing tests pass

Testing:

  • Run tox -e unit after implementation
  • Add performance tests in tests/performance/
  • Verify no regression in single-threaded performance
## Implementation Plan This is a performance optimization issue to implement async/await patterns for I/O operations. ### Files to Modify: 1. `src/infrastructure/router/cascade.py` - Add async request handling 2. `src/timmy/tools/_registry.py` - Make tool loading async 3. `src/dashboard/services/scoring/` - Async database operations 4. `src/infrastructure/hermes/monitor.py` - Async monitoring calls ### Implementation Steps: 1. **Audit Current I/O Patterns**: Identify synchronous file I/O, HTTP requests, database calls 2. **Add asyncio Dependencies**: Update imports and function signatures 3. **Convert Functions**: Transform sync functions to async/await pattern 4. **Update Callers**: Ensure all callers use await properly 5. **Add Async Context Managers**: For file operations and HTTP sessions 6. **Test Performance**: Benchmark before/after with concurrent operations ### Acceptance Criteria: - [ ] All file I/O operations use async file handles - [ ] HTTP requests use aiohttp or httpx - [ ] Database operations use async drivers - [ ] No blocking I/O calls in main thread - [ ] Performance tests show improvement with concurrent operations - [ ] All existing tests pass ### Testing: - Run `tox -e unit` after implementation - Add performance tests in `tests/performance/` - Verify no regression in single-threaded performance
kimi was assigned by Timmy 2026-03-24 13:11:36 +00:00
kimi was unassigned by Timmy 2026-03-24 19:32:23 +00:00
Timmy closed this issue 2026-03-24 21:54:12 +00:00
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Reference: Rockachopa/Timmy-time-dashboard#1408
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