DataSI v0.1.0

First public release.

Added

• inspect() / investigate() pipeline over pandas, CSV/TSV (incl. gzip), Parquet,
  JSON/JSONL, Polars and PyArrow inputs, with pluggable source adapters.
• Schema inference with semantic types, storage hints and explained identifier detection.
• 16 detectors: schema, missingness (group, time, co-occurrence and numeric
  association), duplicates, constant, identifier, types, rules, numeric, outliers (IQR,
  z-score, modified z-score, isolation forest), categorical, strings, datetime,
  temporal (CUSUM change points), correlation (Pearson, Spearman, Cramér's V,
  correlation ratio, mutual information), redundancy (identical, linear, sum identities
  and their breaking rows, one-to-one mappings) and target analysis.
• inspect_train_test() / datasi compare: schema, missingness, KS, Wasserstein, PSI,
  JSD, unseen categories, range checks and a domain classifier.
• Structured findings separating observation, evidence, rule, interpretation,
  suggestion and confidence; configurable, validated thresholds.
• JSON, Markdown and self-contained offline HTML reports; optional matplotlib figures.
• CLI: inspect, report, compare, schema (incl. streaming --chunksize),
  config validate|init, detectors, serve.
• Local web UI (React, TypeScript, Vite, Tailwind) served by datasi serve.
• Synthetic dataset generator with ground truth, detector evaluation
  (precision/recall/FPR/FNR), research experiments E1–E6 and a 10K/100K/1M benchmark.