Releases: lavs9/quantwave
v0.5.2 - Python DX & Discoverability
v0.5.1 - Complete publishing + release reliability
v0.5.1 (clean re-tag)
- All internal crates now publish successfully (including quantwave-backtest)
- Release no longer hard-blocked by docs build warnings
- See changelog for full details
v0.5.0 - Backtest Engine v0.2 + rich PA metadata sizers, high-fidelity execution & professional tearsheets
v0.5.0 - Backtest Engine v0.2 + rich PA metadata sizers, realistic execution models (incl. high-fidelity mode), professional tearsheets with attribution + PA metadata. Notebook + docs hardening, release workflow robustness.
Strict Next + Polars batch/streaming parity preserved across all enhancements (inspired by QF-Lib patterns for the vectorized path only).
Re-tagged cleanly on current main after internal crate version hygiene (path-only only in [workspace.dependencies]; no ^ pins for quantwave-* crates). This ensures Rust crates and Python wheels/sdist publish correctly.
Closes quantwave-n1yc epic and all 5 children (quantwave-n1yc.1 through .5) — rich position sizing from PA metadata, pluggable CommissionModel/SlippageModel (incl. SquareRootMarketImpact + volume limits), High-Fidelity ExecutionSimulator mode, BacktestTearsheet + EnrichedTrade + AttributionReport with full PA metadata, to_markdown() + trades_df() for Excel.
See docs/changelog.md for the complete list of changes.
CI publishing workflow (crates.io + PyPI): https://github.com/lavs9/quantwave/actions/runs/26691989511
(2026-05 IST — re-tag of exact v0.5.0 on the fixed main commit per user request)
v0.4.0 – Options India Suite & Polars Enhancements
v0.4.0 – Options India Suite & Polars Enhancements
This release delivers the long-requested Options India analytics suite and significant Polars quality-of-life improvements.
Highlights
- Options India Suite (new): Full Black-Scholes Greeks (Delta, Gamma, Theta, Vega, Rho, etc.), Implied Volatility solvers, Chain Analytics (Max Pain, PCR, GEX, OI Zones, ATM Straddle, Synthetic Futures), plus NSE utilities (
nse_lot_size,moneyness). - All Options India functionality is available as native Polars expressions with clean column-or-value parameter handling.
- Major code hygiene pass and release build fixes.
Installation
- Python:
pip install quantwave - Rust:
cargo add quantwave
Links
- Full Documentation: https://lavs9.github.io/quantwave/
- Ask DeepWiki: https://deepwiki.com/lavs9/quantwave
- 150+ indicators • Full Ehlers DSP • Regime Detection • Python + Rust
See the Changelog for complete details.