Shopify Image Audit

A Lighthouse-based image audit tool for Shopify stores. Produces per-image scores, role assignments, optimisation recommendations, and a before/after comparison workflow that proves image-optimisation ROI to paying customers.

Designed for the 99–199 € audit-on-demand business model: run the audit, deliver a customer-ready HTML report, optionally compare live metrics after the customer implements the recommendations.

Quickstart

git clone https://github.com/xopsio/shopify-image-audit.git
cd shopify-image-audit
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -e ".[dev]"

# Verify the install
audit version
pytest -q                                              # 390 tests

CLI commands

The tool ships with a single Typer app. Run audit --help for the full list; below are the high-value entry points.

audit run <url> — full Lighthouse + audit pipeline

audit run https://kauppa.myshopify.com --device mobile --runs 3 \
    --out-dir artifacts
# -> artifacts/lhr_run1.json, audit_result.json (schema-compliant)

audit baseline <lhr.json> --save baseline.json — capture baseline

audit baseline fixtures/before_after/before_lcp.json \
    --save baseline.json \
    --url https://demo.myshopify.com
# -> Baseline saved to baseline.json

audit compare <baseline> <current> — before/after (file or URL)

# File vs file (offline)
audit compare baseline.json fixtures/before_after/after_lcp.json \
    -o comparison.html --json comparison.json

# File vs live URL (fetches via PageSpeed Insights API)
audit compare baseline.json https://demo.myshopify.com \
    --strategy mobile --api-key YOUR_KEY \
    -o comparison.html

# HTML report includes a per-image delta table (bytes, score, status per image).
# PDF export via --pdf flag.

Exit codes: 0 success, 2 invalid args, 10 backend failure.

audit report <audit_result.json> — HTML or PDF report

audit report baseline.json -o report.html          # HTML
audit report baseline.json -o report.pdf --pdf     # PDF (WeasyPrint)

audit measure <url> — live PageSpeed metrics only

audit measure https://demo.myshopify.com --strategy mobile
# -> JSON metrics to stdout (or --output metrics.json)

audit shopify <auth|inventory> <store> — Shopify Admin API

# Verify a token
audit shopify auth mystore.myshopify.com --access-token shpat_xxx
# -> Token valid, prints shop info

# List all image URLs (products + theme assets)
audit shopify inventory mystore.myshopify.com --access-token shpat_xxx -o inventory.json

Read-only scopes required (read_products, read_themes, read_shop). See docs/integrations/SHOPIFY_ADMIN.md for token-acquisition steps.

audit score <audit_input.json> --ranker {heuristic|ml}

audit score extracted.json                    # default: heuristic
audit score extracted.json --ranker ml        # weighted feature ensemble

Full reference: docs/spec/cli_v0_1.md.

Scoring algorithms

The pipeline assigns each image a role, a score (0–100), and a recommendation. Two rankers ship, switchable via --ranker ml:

Both produce the same output contract (role + score + recommendation). The ML ranker is a hand-coded feature ensemble, not a statistical model — see src/audit/ranker_ml.py for the design rationale (no model deps, deterministic, fully explainable via ml_features()).

Architecture

src/
├── audit/                    # scoring + reporting
│   ├── models.py             # Pydantic v2 schemas (AuditResult, ComparisonResult, ImageDelta)
│   ├── parser.py             # Lighthouse / fixture JSON parser
│   ├── ranker_heuristic.py   # default ranker (bpp-based)
│   ├── ranker_ml.py          # opt-in ML-style ranker (weighted ensemble)
│   └── report.py             # HTML/PDF report renderer (split into _render_* funcs)
├── core/                     # core algorithms
│   ├── image_extractor.py    # LHR image audit extraction
│   ├── image_signals.py      # shared displayed_area, assign_role, _safe_int
│   └── baseline_manager.py   # save/load baselines + compare() + per-image matching
├── engine/                   # orchestration + CLI
│   ├── cli.py                # Typer app (run, measure, baseline, compare, shopify, ...)
│   ├── cli_helpers/          # extracted CLI helpers (validators, dispatchers, table, errors)
│   └── audit_orchestrator.py # run_audit() pipeline
└── integrations/             # external APIs
    ├── pagespeed_api.py      # PageSpeed Insights (measure + fetch_lighthouse_json)
    └── shopify_admin.py      # Shopify Admin API (auth, products, theme_assets)

schemas/audit_result.schema.json    # JSON Schema contract (validated by tests)
tests/                              # 390 tests, single-writer (ZCode)
docs/examples/                       # live demo report + comparison JSON
docs/integrations/                   # Shopify Admin API token guide

The codebase is governed by a single ZCode agent (see docs/governance.md v1.3).

Testing

pytest -q                                # 489 tests, single-writer discipline
pytest --cov=src --cov-report=term       # ~87% coverage
ruff check src/ tests/                   # 0 violations

The CI workflow runs pytest -q + ruff check on Python 3.11 and 3.12 for every PR. Branch protection on main requires both checks to pass before merge. See .github/workflows/ci.yml.

Customer deliverables (Phase 1)

• Customer report template — docs/CUSTOMER_REPORT_TEMPLATE.md
• Onboarding workflow — docs/CUSTOMER_ONBOARDING.md
• Example audit report (Nordic Lifestyle demo store, LCP 4200ms → 1800ms) — docs/examples/demo_audit_report.html
• Example comparison data — docs/examples/demo_comparison.json

Roadmap

• ✅ Sprint 1 — v0.1.0 baseline (parser, ranker, orchestrator, CLI, HTML report, 103 tests)
• ✅ Sprint 2 — before/after workflow, customer docs, ML ranker, live URL compare, CI, governance cleanup (276 tests)
• ✅ Sprint 3 — PDF export, per-image deltas, Shopify Admin API, v0.2.0 release prep (390 tests)
• ✅ Sprint 4 — Branded reports, ROI-ranked recs, audit history, v0.3.0 (489 tests)
  • Branded report templates (--brand-logo, --brand-color)
  • ROI-ranked recommendations (ComparisonRecommendation model)
  • Audit history + trend view (HistoryStore, audit history list/show)

Further reading

• docs/spec/cli_v0_1.md — full CLI specification
• docs/governance.md — ownership + workflow
• docs/runbook/measurement_protocol.md — how LCP/CLS/INP are measured deterministically
• docs/SPRINT_1_COMPLETE.md — what shipped in Sprint 1
• docs/SPRINT_3_PLAN.md — Sprint 3 breakdown (all done)
• docs/SPRINT_4_PLAN.md — Sprint 4 breakdown (all done)
• QA_CHECKLIST.md — quality gates