feat(jade): JadeFlow Week 1 foundation — DAG engine, CLI, persistence#4
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alex-jadecli wants to merge 1 commit into
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feat(jade): JadeFlow Week 1 foundation — DAG engine, CLI, persistence#4alex-jadecli wants to merge 1 commit into
alex-jadecli wants to merge 1 commit into
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…LI, and persistence Complete Week 1 deliverable from the JadeFlow Bible: define workflows in Python and run them via CLI. Includes: - Core DAG engine with @flow/@task decorators and topological sort (Kahn's algorithm) - Sequential executor with retry logic, upstream failure propagation, and result passing - Task/flow state machines with validated transitions - SQLAlchemy ORM models (6 tables: workflows, runs, tasks, instances, logs, config) - Repository pattern for data access - Typer CLI: jade init, run, status, validate, graph, version - Feature flag system (defaults + file + env var override, cached) - Per-module CLAUDE.md files enforcing scope boundaries - 3 example workflows (hello_world, etl_pipeline, parallel_tasks) - 90 unit tests covering all modules (100% pass rate) https://claude.ai/code/session_01MsF8rLi2Q2BHcdvdvNfjeC
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Summary
@flow/@taskdecorators, topological sort (Kahn's algorithm), sequential executor with retries, upstream failure propagation, and result passing between tasksjade init,run,status,validate,graph,version) — define workflows in Python and execute from the command line~/.jade/flags.json→ env vars) and cached loadingcore/,cli/,db/,ai/,plugins/Test plan
pytest tests/jade/ -v— 90 tests passruff check jade/ tests/jade/ examples/— cleanjade run examples/hello_world.py hello_world— executes successfullyjade validate examples/etl_pipeline.py etl_pipeline— validates DAGjade graph examples/parallel_tasks.py parallel_pipeline— renders ASCII DAGhttps://claude.ai/code/session_01MsF8rLi2Q2BHcdvdvNfjeC