Build complete Market Data Backend

[jkirkmannz]

@claude
Read all the documents in the planning directory, then build the complete Market data backend directory. This should include:

1. The Massive API Interface
2. The unified market data interface
3. The market data simulator
4. include full unit tests

[claude]

Claude finished @jkirkmannz's task in 1m 14s —— View job

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Market Data Backend — already complete ✅

Todo list

• Read planning docs (PLAN.md, MARKET_DATA_SUMMARY.md, MARKET_DATA_DESIGN.md, archive docs)
• Check current state of backend/ directory
• Verify the 4 requested pieces exist and are wired together correctly
• Confirm this branch is up to date with main (no missing work)

Finding

The Market Data Backend requested in this issue has already been built and merged to main in PR #2 (8c7f8e2 Merge pull request #2 from jkirkmannz/claude/happy-cerf-bl420s). This branch (claude/issue-3-20260912-0346) is at the same commit as main — working tree is clean, nothing to add.

I verified the implementation directly (not just the summary doc) by reading every module in backend/app/market/:

Requirement	File	Notes
Unified market data interface	app/market/interface.py	MarketDataSource ABC with start/stop/add_ticker/remove_ticker/get_tickers
Massive API interface	app/market/massive_client.py	MassiveDataSource — polls Polygon.io REST snapshots, runs sync client in a thread, handles rate-limit/network failures without crashing the poll loop
Market data simulator	app/market/simulator.py	GBMSimulator — geometric Brownian motion with Cholesky-correlated moves across sector groups (tech, finance, TSLA idiosyncratic), plus random 2–5% shock events; SimulatorDataSource wraps it as a MarketDataSource
Supporting pieces	models.py, cache.py, factory.py, stream.py, seed_prices.py	PriceUpdate immutable model, thread-safe PriceCache with version counter, create_market_data_source() factory selecting simulator vs. Massive based on MASSIVE_API_KEY, SSE router factory
Full unit tests	backend/tests/market/*.py	6 test modules (test_models, test_cache, test_simulator, test_simulator_source, test_factory, test_massive) covering models, cache, GBM math, factory selection logic, and mocked Massive API responses

pyproject.toml is correctly configured (hatchling build targets app, pytest/ruff dev deps, coverage config), and backend/CLAUDE.md documents the public API for downstream consumers (portfolio, SSE, chat).

Note on verification

I was not able to execute uv run pytest or uv run ruff in this environment — Bash(uv ...) commands require interactive approval that isn't available in this automated run. If you'd like me to actually execute the test suite and linter (rather than just reading the code), add something like Bash(uv run pytest*) and Bash(uv run ruff*) to the workflow's --allowedTools. Per planning/MARKET_DATA_SUMMARY.md, the suite was previously reported as 73 tests passing with 84% coverage when it was built.

Outcome

No code changes were made — there is nothing new to implement for this issue since the described work already exists on main. No PR is needed. If this issue was filed before PR #2 merged, it can be closed as a duplicate/already-resolved.