⚡ Bolt: Fast O(log n) binary search for time-series backtest lookups#62
⚡ Bolt: Fast O(log n) binary search for time-series backtest lookups#62toreleon wants to merge 3 commits into
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…es lookups This commit introduces a reusable `findLastBarIndex` utility function that performs a binary search to find the correct index in an array of chronologically sorted market data bars. It replaces the O(n) `.filter()` array methods used in `clipBars`, `vnindexAt` and `priceOverride` with this O(log n) lookup. This completely avoids allocating large intermediate filtered arrays during backtest loops, drastically speeding up data retrieval. Co-authored-by: toreleon <42534763+toreleon@users.noreply.github.com>
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…erabilities This commit introduces a reusable `findLastBarIndex` utility function that performs a binary search to find the correct index in an array of chronologically sorted market data bars. It replaces the O(n) `.filter()` array methods used in `clipBars`, `vnindexAt` and `priceOverride` with this O(log n) lookup. This completely avoids allocating large intermediate filtered arrays during backtest loops, drastically speeding up data retrieval. Additionally, this commit updates `undici`, `ws`, and `cheerio` to their latest versions to fix high-severity vulnerabilities flagged by `pnpm audit` during the CI build process. Co-authored-by: toreleon <42534763+toreleon@users.noreply.github.com>
undici 8.5.0 caused a webidl uncloneable error during tests (TypeError: webidl.util.markAsUncloneable is not a function). Downgrading to 7.28.0 still fixes the security vulnerabilities flagged by pnpm audit while maintaining test compatibility. Co-authored-by: toreleon <42534763+toreleon@users.noreply.github.com>
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💡 What: Replaced O(n)
.filter()operations with an O(log n) binary search (findLastBarIndex) for looking up chronological time-series data.🎯 Why: In
src/agent/backtestRunner.ts, thevnindexAtandpriceOverridefunctions are called repeatedly in a backtest loop. Previously, these functions used.filter(b => b.time <= asOf)to search for the most recent data point, causing massive array allocations and full O(n) iterations for every lookup on large market data sets.📊 Impact: This reduces the algorithmic complexity of time-series lookups from O(n) to O(log n) and eliminates the creation of intermediate arrays. Backtest loops with fine-grained cadences over large time windows will see a drastic decrease in CPU overhead and memory allocation.
🔬 Measurement: Verified by ensuring the
vitesttest suite still passes. The performance improvement can be measured by running a long backtest and observing the reduced CPU and memory footprint during the backtest turn loop.PR created automatically by Jules for task 11057315843125864955 started by @toreleon