UNPKG

datapilot-cli

Version:

Enterprise-grade streaming multi-format data analysis with comprehensive statistical insights and intelligent relationship detection - supports CSV, JSON, Excel, TSV, Parquet - memory-efficient, cross-platform

57 lines 1.75 kB
/** * Section 2: Validity Dimension Analyzer * Validates data types, ranges, patterns, and business rules */ import type { ValidityAnalysis, BusinessRule } from './types'; import { DataType } from '../../core/types'; export interface ValidityAnalyzerInput { data: (string | null | undefined)[][]; headers: string[]; columnTypes: DataType[]; rowCount: number; columnCount: number; businessRules?: BusinessRule[]; customPatterns?: Record<string, string>; customRanges?: Record<string, { min?: number; max?: number; }>; } export declare class ValidityAnalyzer { private data; private headers; private columnTypes; private rowCount; private columnCount; private businessRules; private customPatterns; private customRanges; private static readonly DATE_PATTERNS; constructor(input: ValidityAnalyzerInput); analyze(): ValidityAnalysis; private analyzeTypeConformance; private analyzeRangeConformance; private analyzePatternConformance; private validateBusinessRules; private analyzeFileStructure; private inferActualType; private checkTypeConformance; private inferValueType; private looksLikeDate; private looksLikeDateTime; private isCompatibleType; private suggestConversionStrategy; private inferReasonableRange; private findRangeViolations; private inferPattern; private getSampleValues; private detectCommonPatterns; private findPatternViolations; private evaluateBusinessRule; private calculateValidityScore; private formatDataType; private formatRange; private isValidValue; private getMostFrequent; } //# sourceMappingURL=validity-analyzer.d.ts.map