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ultravisor-suite-harness

v1.0.0

Published

End-to-end test harness for the Ultravisor/Facto pipeline with blessed terminal UI

Readme

Ultravisor Suite Harness

License: MIT


An end-to-end test harness for the Ultravisor / Facto / Meadow Integration data pipeline. The harness boots a full in-process stack (Facto data warehouse, Meadow Integration parser, Ultravisor workflow engine) and drives real-world datasets from the facto-library through the scan -> parse -> map -> transform -> load -> verify pipeline, then reports pass/fail per dataset.

The harness ships with a blessed terminal UI built on top of Pict for interactive development and a --headless mode suitable for CI.

Features

  • Full-Stack In-Process -- Boots Facto (:8420), Meadow Integration (:8421), and Ultravisor (:8422) as Pict child applications in the same Node process
  • Real Workload Testing -- Drives ISO codes, IANA TLDs, RAL colors, BLS titles, IEEE OUI, OurAirports, Tiger Census, Project Gutenberg, and more through the full pipeline
  • Multi-Entity Extraction -- Bookstore fixture exercises the TabularTransform multi-mapping path (one CSV -> Book / Author / BookAuthorJoin datasets)
  • Interactive TUI -- Blessed + Pict layout with main menu, suite runner, results table, dataset picker, and captured server log
  • Headless Mode -- node harness.js --headless --datasets=... prints progress, results summary, and exits 0/1 for CI
  • Dataset Presets -- Small / Medium / Large presets let you scale from 30-second smoke test to multi-minute full sweep
  • Port Cleanup & Graceful Shutdown -- Automatically reclaims ports 8420-8422 from stale runs and shuts down cleanly on Ctrl+C
  • Persistent Results -- Each run is written to ./data/harness.db (HarnessTestRun + HarnessTestResult tables) for later inspection

Installation

cd modules/apps/ultravisor-suite-harness
npm install

The harness expects the facto-library dataset cache at ./modules/dist/facto-library/ relative to the repo root. Large presets assume those datasets have already been fetched.

Quick Start

# Interactive blessed UI
npm start

# Headless run with the default preset
npm run headless

# CI-friendly validation runs
npm run test:small     # 3 datasets
npm run test:medium    # 8 datasets
npm run test:large     # 14+ datasets

Once the TUI is open, use the number-key shortcuts:

| Key | Action | |---|---| | 1 | Clean & Execute -- stop servers, wipe ./data/, restart, run the selected preset | | 2 | Run Suite -- run the selected preset without cleaning (reuse existing DB state) | | 3 | View Results -- pass/fail summary table from the last run | | 4 | Dataset Picker -- choose small / medium / large preset | | 5 | Server Log -- captured stdout / stderr from the three child servers | | m | Return to main menu from any view | | q | Quit |

In the Dataset Picker view, press s for small, M for medium, L for large.

Headless Usage

# Default preset
node harness.js --headless

# Explicit dataset list
node harness.js --headless --datasets=datahub-country-codes,datahub-currency-codes

# Run a single multi-entity fixture
node harness.js --headless --datasets=bookstore

Headless mode exits with code 0 when every dataset passes, 1 when any dataset fails. It prints a summary table identical to the one shown in the View Results screen of the TUI.

What the Suite Tests

For each selected dataset the harness executes the full pipeline:

  1. Scan -- locate the input file in modules/dist/facto-library/<name>/data/ (or the local fixtures/ folder for multi-entity scenarios)
  2. Parse -- meadow-integration FileParser streams the file and auto-detects CSV / JSON
  3. Map -- identity mapping for single-entity datasets, or custom Mappings JSON for multi-entity fixtures like bookstore
  4. Transform -- meadow-integration TabularTransform flattens nested objects and sanitizes values
  5. Load -- Ultravisor dispatches the facto-ingest operation which calls Facto beacons (createsource, createdataset, createingestjob, bulkcreaterecords, updateingestjob)
  6. Verify -- SELECT COUNT(*) against the resulting Facto dataset is compared to the parsed row count

A dataset passes only when all six steps complete and the verified count matches the parsed count.

Architecture Summary

  • harness.js -- entry point; intercepts stdout/stderr, parses CLI args, cleans stale ports, launches either the blessed TUI or the headless orchestrator
  • source/Harness-Application.js -- the Pict application that owns the blessed layout, navigation, dataset presets, and runtime state
  • source/services/Service-ServerManager.js -- starts, stops, and health-checks the three in-process servers
  • source/services/Service-TestOrchestrator.js -- owns DATASET_REGISTRY, runs the per-dataset pipeline, dispatches facto-ingest operations through Ultravisor
  • source/services/Service-DataManager.js -- manages the ./data/ directory and the harness.db SQLite file (HarnessTestRun, HarnessTestResult)
  • source/views/ -- blessed + Pict views (View-MainMenu, View-SuiteRunner, View-Results, View-DatasetPicker, View-Log)
  • operations/ -- Ultravisor operation JSON (facto-ingest.json, facto-full-ingest.json, facto-projection-import.json, facto-projection-deploy.json)
  • fixtures/ -- local test data, including bookstore/ multi-entity mappings

See docs/architecture.md for diagrams.

Data Storage

All runtime state lives under ./data/ (git-ignored):

  • ./data/harness.db -- harness-owned SQLite DB with suite-run history
  • ./data/facto.db -- Facto warehouse DB
  • ./data/target.db -- Meadow Integration transform workspace
  • Any additional databases spun up by child services

Pressing 1 (Clean & Execute) wipes this directory before a run. Pressing 2 (Run Suite) leaves existing state alone -- useful for isolating pipeline failures from data-setup failures.

Documentation

Related Packages

License

MIT

Contributing

Pull requests welcome. See the Retold Contributing Guide for the code of conduct, contribution process, and testing requirements.