counterweight/arbret

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Author	SHA1	Message	Date
counterweight	7beb213cf5	Phase 3: Outcome storage - Add RandomNumberOutcome model to models.py - Update worker.py to execute job logic: - Generate random number 0-100 - Record execution duration - Store outcome in database - Add test_jobs.py with unit tests for job handler logic	2025-12-21 22:50:35 +01:00
counterweight	10c0316603	Phase 1: Add pgqueuer infrastructure - Add pgqueuer dependency to pyproject.toml - Create worker.py with schema installation and job handler registration - Add make worker command to Makefile - Update make dev to run worker alongside backend/frontend - Use has_table() check for idempotent schema installation - Register 'random_number' job handler (placeholder that logs for now)	2025-12-21 22:37:04 +01:00
counterweight	15bae15731	Phase 1: Add pgqueuer infrastructure and worker skeleton - Add pgqueuer dependency to pyproject.toml - Create worker.py with basic setup: - Independent database connection using asyncpg - Install pgqueuer schema on startup - Register dummy job handler - Start consumer loop - Add 'make worker' command - Update 'make dev' to run worker alongside backend/frontend Validation: - Worker starts successfully - pgqueuer tables exist in database - All existing tests pass	2025-12-21 22:25:37 +01:00

Author

SHA1

Message

Date

counterweight

7beb213cf5

Phase 3: Outcome storage

- Add RandomNumberOutcome model to models.py
- Update worker.py to execute job logic:
  - Generate random number 0-100
  - Record execution duration
  - Store outcome in database
- Add test_jobs.py with unit tests for job handler logic

2025-12-21 22:50:35 +01:00

counterweight

10c0316603

Phase 1: Add pgqueuer infrastructure

- Add pgqueuer dependency to pyproject.toml
- Create worker.py with schema installation and job handler registration
- Add make worker command to Makefile
- Update make dev to run worker alongside backend/frontend
- Use has_table() check for idempotent schema installation
- Register 'random_number' job handler (placeholder that logs for now)

2025-12-21 22:37:04 +01:00

counterweight

15bae15731

Phase 1: Add pgqueuer infrastructure and worker skeleton

- Add pgqueuer dependency to pyproject.toml
- Create worker.py with basic setup:
  - Independent database connection using asyncpg
  - Install pgqueuer schema on startup
  - Register dummy job handler
  - Start consumer loop
- Add 'make worker' command
- Update 'make dev' to run worker alongside backend/frontend

Validation:
- Worker starts successfully
- pgqueuer tables exist in database
- All existing tests pass

2025-12-21 22:25:37 +01:00

3 commits