semantic-ds-toolkit
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Performance-first semantic layer for modern data stacks - Stable Column Anchors & intelligent inference
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TypeScript
import { StableColumnAnchor, ColumnData, ColumnFingerprint } from '../types/anchor.types';
/**
* Example usage of the drift detection system
* This demonstrates how to use the various components for semantic drift detection
*/
declare const historicalAnchor: StableColumnAnchor;
declare const currentColumn: ColumnData;
declare const currentFingerprint: ColumnFingerprint;
/**
* Example 1: Basic drift detection
*/
export declare function basicDriftDetectionExample(): Promise<import("./drift-detector").DriftDetectionResult>;
/**
* Example 2: Performance-optimized drift detection for large datasets
*/
export declare function performanceOptimizedExample(): Promise<import("./drift-detector").DriftDetectionResult>;
/**
* Example 3: Batch processing multiple columns
*/
export declare function batchProcessingExample(): Promise<import("./drift-detector").DriftDetectionResult[]>;
/**
* Example 4: Performance benchmarking
*/
export declare function performanceBenchmarkExample(): Promise<Record<number, {
avgTime: number;
throughput: number;
}>>;
/**
* Example 5: Statistical tests demonstration
*/
export declare function statisticalTestsExample(): Promise<{
ksResult: import("./statistical-tests").KolmogorovSmirnovResult;
psiScore: number;
comparison: {
ks_test: import("./statistical-tests").KolmogorovSmirnovResult;
psi_analysis?: import("./statistical-tests").PopulationStabilityResult;
wasserstein_distance?: number;
summary: {
drift_detected: boolean;
severity: "none" | "low" | "medium" | "high";
primary_indicator: string;
};
};
}>;
/**
* Run all examples
*/
export declare function runAllExamples(): Promise<void>;
export { historicalAnchor, currentColumn, currentFingerprint };
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