ad5b9dcc28
The spot fix introduced `last_day_by_symbol` date-resume, but the sibling bybit ingests still used the
OLD symbol-skip resume ("resuming: N already done, M to go"): once a symbol carried ANY row of a feature
it was never fetched again, so the feature froze at the last ingest. funding stuck at 2026-06-23 froze
`xvenue_carry_nav` (it reads bybit_features funding) at 0d; open_interest/long_ratio/worst_basis lagged.
Extract a shared `resume_floor_ms(last_day, symbol, default_start_ms)` primitive (bybit_concurrency) and
apply it to `ingest_bybit_funding`, `ingest_bybit_oi`, `ingest_bybit_long_short`, and
`ingest_bybit_worst_basis`: each symbol now resumes from its last persisted day for ITS feature (the
adapter's backward-pagination floor), so done symbols are re-fetched only from their last day forward
(advancing them; the idempotent upsert overwrites the boundary day in place) and fresh symbols back-fill
from the caller's start_ms. Nothing is symbol-skipped → every feature advances each run. Refactored
`ingest_bybit_spot` onto the same shared primitive. deribit_funding already re-fetches all (no skip) — left
as-is. The perp `close`/`turnover` leg of `ingest_bybit_klines` keeps its symbol-skip resume (out of scope).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
fxhnt
Agentic strategy-research & multi-strategy execution platform. It systematically discovers, backtests and out-of-sample-validates trading strategies across many markets, keeps only what survives a rigorous statistical gauntlet, and runs the survivors live (multiple strategies at once).
The bet is not a secret edge — it's breadth + discipline + automation. The hard part (and the moat) is refusing to fool yourself at scale; the validation gauntlet is the core, built and proven first.
Architecture (hexagonal / ports-and-adapters)
src/fxhnt/
domain/ pure logic: gauntlet (Deflated Sharpe), strategies, backtest, models ← no I/O
ports/ contracts: DataProvider, repositories (the only seams)
adapters/ infra: yahoo data, SQLAlchemy (Postgres/SQLite) + DuckDB stores
application/ use-case services (ResearchService) — orchestrate via ports
cli.py composition root (wires concrete adapters)
See docs/architecture/0001-architecture.md.
Quickstart
pip install -e ".[dev]"
pytest # unit (gauntlet falsification) + integration (vertical slice)
fxhnt strategies # list strategy kinds
fxhnt research SPY --kind trend --window 200 # data → backtest → gauntlet → persist
fxhnt list --passed-only # the survivor library
Config via FXHNT_* env vars (e.g. FXHNT_OPERATIONAL_DSN=postgresql+psycopg://...). Defaults to
SQLite + a local DuckDB file under ~/.fxhnt/.
Status
Vertical slice working: data (Yahoo) → strategy (trend) → backtest (net of costs) → IS/OOS gauntlet → persistence (operational + analytical). Next: the multi-strategy execution layer, more strategy templates + data adapters, and the agentic discovery search on top of the proven gauntlet.