Finance-Accounts/ar-aging-app/README.md

# Amazon Accounts Receivable Aging Dashboard

Automates the Finance team's month-end **Amazon Accounts Receivable Aging** workbook:
upload the month's Amazon *Custom Unified Transaction* files → get a structurally- and
financially-identical Accounts Receivable Aging workbook, with validation, settlement
reconciliation, exceptions, drill-down, and an audit trail.

**Amazon only** (no Walmart/TikTok/Temu/Shein/eBay/Shopify). Reverse-engineered from the
Jan-2026 files; the USA receivable reproduces to the penny (**11,110,433 = `Detail!D11`**).
See [docs/accounts-receivable-logic.md](docs/accounts-receivable-logic.md).

## Layout
```
backend/
  app/core/        # streaming parser + receivable engine (stdlib + openpyxl only)
  app/api/         # FastAPI app: routes, auth (login), deps
  app/services/    # jobs, persistence, FX-rate fetch, controls, retention
  app/db/          # SQLAlchemy models (20 tables) + engine (SQLite / MySQL)
  tests/           # 150+ tests: engine, API, auth, FX, dedup, Jan-2026 integration
  cli.py           # process files from the command line
  manage.py        # admin: add-user / set-password / dedupe-files / …
  migrate_sqlite_to_mysql.py   # one-time data migration for the AWS cutover
frontend/          # React + TS + Vite dashboard (nginx-served in production)
scripts/           # launchers: start.ps1 / start.bat (Windows) · start.command (macOS)
deploy/            # DEPLOY.md runbook + backup.sh (nightly mysqldump + S3 sync)
docs/              # system guide · AR logic · audit reports
docker-compose.yml            # dev stack        docker-compose.prod.yml  # production
.env.example                  # every setting, LOCAL + PRODUCTION sections
```

## Production deployment (AWS)

One 8 GB server runs the whole stack with automatic HTTPS, MySQL, per-user login, and
nightly S3 backups — see **[deploy/DEPLOY.md](deploy/DEPLOY.md)** for the full runbook
(provisioning, user creation, SQLite→MySQL migration, backups, updates). ≈ $50–55/month.

```bash
cp .env.example .env.production    # fill the PRODUCTION section (domain, passwords, AR_SECRET_KEY)
docker compose --env-file .env.production -f docker-compose.prod.yml up -d --build
docker compose --env-file .env.production -f docker-compose.prod.yml exec backend \
  python manage.py add-user <user> --name "Full Name"
```

Key production behaviors:
- **One closing per month** — every month stays saved and selectable (month switcher in the
  closing header); creating a second closing for an existing month requires an explicit override.
- **Duplicate-proof uploads** — re-uploading a filename *replaces* it; identical content
  under another name is skipped. A month can never count a file twice.
- **Login** (`AR_AUTH`) — per-user accounts via `manage.py add-user`; journal review/approval
  and FX confirmations record the signed-in user's verified name.
- **Password self-service** — users change or recover passwords with a 6-digit code emailed
  to their account address (Settings, or "Forgot password?" on the login screen). Sent via
  the company Mail API (`AR_MAIL_API_*`), SMTP fallback; `manage.py set-password` remains
  the admin override.
- **Exchange rates** — "Fetch month-end rates" pulls central-bank rates (Frankfurter, free,
  keyless; `AR_FX_PROVIDER`); fetched rates still require human confirmation (Control C5).
- **Completed closings are locked** read-only; corrections need an explicit Reopen.
- **Crash-safe jobs** — a restart mid-processing marks the closing as interrupted instead of
  leaving it stuck; generated exports are purged after `AR_RETENTION_DAYS` (uploads never are).

## Run the app (development)
```bash
# 1. Configure the environment (SQLite by default — no database setup needed)
cp .env.example .env   # then fill the LOCAL section (AR_SECRET_KEY at minimum)

# Option A — Docker (backend + Vite hot reload)
docker compose up --build
# → http://localhost:5173  (API on :8000; uploads/exports on the ar_data volume)

# Option B — local processes
make install          # backend deps + npm install
make backend          # terminal 1 → FastAPI on :8000
make frontend         # terminal 2 → dashboard on http://localhost:5173

# Option C — Windows one-click (ports 8010/5174)
scripts\start.bat     # or: powershell -ExecutionPolicy Bypass -File scripts\start.ps1
# macOS one-click:
scripts/start.command
```
Then open the dashboard → **New Closing** → pick the month → drag in the month's Amazon
files → **Run processing** → review → **Download Full A/R Aging Excel**.

Uploads and exports are stored under `AR_DATA_DIR` (default `backend/data` locally, `/data` in
Docker). The database is a local SQLite file by default; set `MYSQL_*` in `.env` to use MySQL.

## Run the engine headless (CLI)
```bash
cd backend && pip install -r requirements.txt
python cli.py "/path/USA…01 to 10 January,2026.xlsx" \
              "/path/USA…11 to 20 January,2026.xlsx" \
              "/path/USA…21 to 31 January,2026.xlsx" \
              --month-end 2026-01-31 --lag 2 --reserve-standard 125.44 --out AR_Aging_Jan26.xlsx
```

## Tests
```bash
make test        # 155 fast tests: engine, API, auth, FX, upload dedup, month locking
make test-all    # + Jan-2026 reconciliation & sample-comparison (integration, ~4 min)
# point the integration tests at the sample files if not in the repo root:
AR_SAMPLE_DIR="/path/to/samples" make test-all
```
The suite runs against an isolated temporary database — it can never touch real data
(a session-scoped guard asserts the isolation before anything runs).

## Feature summary

**Calculation engine**
- Settlement classification + receivable; USA Jan-26 = **11,110,433** verified to the penny
- All 13 marketplaces reconcile to the penny vs the Finance workbook — per-market currency
  & FX, settlement-owner logic for cross-market EU chains, helper-row/pivot-sheet detection
- AR roll-forward (opening + net revenue − payouts = closing) with auto carry-forward,
  AR Ledger, Finance Summary, per-marketplace Journal Entry, Reconciliation Control
- Header mapping with localized alias tables + admin rules UI; unmapped amounts are never
  silently excluded; storage-fee detection; full Excel audit workbook + Finance pack

**Operations & security**
- Per-user login with emailed password codes; verified names on every sign-off
- Six month-end controls (C1–C6) block publication of any untrusted figure
- Month-end FX fetched from central-bank data, gated by human confirmation
- Duplicate-proof uploads, one-closing-per-month guard, completed-month locking
- Production Docker stack (auto-HTTPS · MySQL · nightly S3 backups) + Gitea Actions CI