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Point-in-Time Quant Validation SDK

\n

A zero-dependency Python engineering toolkit designed for quantitative research teams, algorithmic trading engineers, and financial machine learning systems to eliminate look-ahead bias and audit temporal data causality.

\n

Core Capabilities

\n\n

Quick Start

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import datetime as dt\nfrom pit_quant.splits import PurgedWalkForwardSplitter\nfrom pit_quant.leakage_detector import LeakageDetector\n\ntimestamps = [dt.datetime(2026, 1, 1, tzinfo=dt.timezone.utc) + dt.timedelta(minutes=5*i) for i in range(100)]\nsplitter = PurgedWalkForwardSplitter(n_splits=3, purge_window_seconds=1800.0)\nfolds = splitter.split(timestamps)\nfor f in folds:\n    print(f"Fold {f.fold_index}: Train={len(f.train_indices)} -> Gap={f.purge_gap_seconds}s -> Test={len(f.test_indices)}")\n
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Production Standards

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