- WeightOptimizer base class with registry (equal, factor_weighted, risk_parity, mean_variance)
- RiskModel with shrinkage covariance estimation and portfolio risk metrics
- RebalanceEngine for multi-period backtesting with commission/slippage
- 20 unit tests covering all components
Co-Authored-By: Claude <noreply@anthropic.com>
FastAPI does not accept redoc_js_url as a constructor param — the old
approach silently ignored it, leaving the default redoc@next CDN URL
(which returns 404). Manually register /redoc with get_redoc_html()
using the fixed v3.0.0-rc.0 bundle URL.
Co-Authored-By: Claude <noreply@anthropic.com>
- get_mac_client() now raises TdxConnectionError (503) when MAC client
is None, matching get_ex_client() behavior. Previously returned None
causing AttributeError (500) on all 12 MAC endpoints.
- _records_to_df_resp() filters out internal _raw: bytes fields from
Ex dataclass models. Previously asdict() included binary protocol
data that is not JSON-serializable and would cause 500 errors.
Co-Authored-By: Claude <noreply@anthropic.com>
Root cause: _market_from_str/_market/_category in routers used bare
MarketEnum[key]/Market[key] without .upper() or try/except, so
lowercase or invalid values (sz, ZZZ) threw uncaught KeyError → 500.
Fix: extract shared convert.py with market_from_str/category_from_str
that do .upper() + ValueError on invalid input. All 4 routers updated.
4 regression tests added for case-insensitive and invalid input.
The typing.cast(AsyncTdxClient, ...) evaluated AsyncTdxClient at
runtime, but the import was gated behind TYPE_CHECKING, causing
NameError in production. Direct import is safe here — web module
already depends on easy_tdx core.
- Add get_board_change_ranking() to MacClient and AsyncMacClient
- Add 'board-change-ranking' CLI command (--type/--date/--days/--top/--asc)
- Calculate N-day price change from board index K-lines directly
- Default to listing all boards; --top N to truncate
- 12 unit tests covering calculation, edges, sorting
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add EventBus for async publish/subscribe market events
- Add MarketEvent dataclass with tick/bar/signal/error types
- Add RealtimeStrategy base class with on_tick/on_bar callbacks
- Add emit_signal() for strategy-to-engine signal publishing
- Support per-symbol and global subscriptions
- API skeleton: transport-level subscription TBD
- Add 10 tests covering events, bus, and strategy
- Create type stub file for 50+ MyTT indicator functions
- Covers all 31 functions used in the project + common utilities
- Remove mypy disallow_untyped_defs/calls override for MyTT
- MyTT now covered by strict mypy via .pyi stubs
- Store previous DataFrame in ChanlunAnalyser after process_klines
- Add append_klines(df_new) to concatenate and recompute
- Handles datetime deduplication automatically
- Raises RuntimeError if called before initial process_klines
- Add 2 tests: append + recompute, error without init
- Add workers param to SignalScanner.scan() (default=0 for serial)
- workers=2+ uses ProcessPoolExecutor for parallel .day file processing
- Extract _scan_one_file as top-level function for pickle compatibility
- Results identical between serial and parallel modes
- Add 4 tests with synthetic .day file fixtures
- Add chanlun_level param to BacktestEngine constructor
- When set, auto-create ChanlunAnalyser and compute ChanlunResult
- Manual chanlun_result in run() takes priority over auto-compute
- Update Strategy.chanlun type to Any (accepts ChanlunResult or dict)
- Add 2 tests: auto-bridge and manual override priority
- Track SL/TP conditions from BUY signals in _generate_signals loop
- Check active conditions against each bar's high/low price range
- Auto-generate SELL signal at trigger price when condition is met
- Modify OrderSimulator to respect signal.price for direct execution
(previously signal.price was stored but never used in execution)
- SL/TP activates on bar AFTER BUY signal (consistent with next_open)
- Stop-loss checked before take-profit (conservative for holder)
- Add 4 tests: SL trigger, TP trigger, no-trigger, priority over manual sell
- Add --cov and --cov-fail-under=50 to CI pytest command
- Replace hardcoded avg_holding_days=5.0 with FIFO-based calculation
from actual trade datetime pairs (handles int and Timestamp types)
- Vectorize _datetime_to_int using pd.to_datetime().strftime()
instead of Python for-loop (~100-200x faster on large arrays)
- Add 3 new test cases: weighted holding days, no datetime fallback,
only-buys edge case
Use 'row_any: Any = row' pattern to avoid arg-type mismatch between
local (pandas-stubs) and CI (bare pandas) environments.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- pyproject.toml: add mypy overrides for pandas/tabulate/matplotlib stubs,
disable strict checking for vendored MyTT library
- config.py: use cast() for dict[str, Any] .get() returns
- beichi.py: widen _calc_bi_force param to BI | XD, import XD
- backtest/cli.py: split combo/single strategy into separate typed variables
- backtest/combo.py: add bool_array() helper for numpy return types
- chanlun/analyser.py: type ignore for pandas row access, fix dict type arg
- unified.py: change fields param from object to Any
- ex/mac_client.py: add type args to list literals
- cli/cmd_offline.py: wrap int market as Market enum before API call
- cli/cmd_chanlun.py: fix dict type arg
- offline/write_*.py: explicit int() cast for struct.unpack returns
- MyTT.py: fix line-too-long comments, UP038 isinstance syntax
- tests: fix E712 (==False → ~mask), E741 (noqa), F841, import sorting
- ruff format applied across codebase
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
