# Pivot Forecast — CLAUDE.md

## What this app is

A web app for building named forecast scenarios against any PostgreSQL table. The workflow: load historical actuals as a baseline (optionally date-shifted into the forecast period), then apply incremental adjustments (scale, recode, clone) to build a plan. All changes are append-only, fully audited, and reversible by log entry.

Full spec: `pf_spec.md`
Data transport architecture options: `pf_perspective_options.md`
UX mockup: `pf_ux_mockup.md`
Open work: `todo.md`

---

## Tech stack

- **Backend:** Node.js / Express (`server.js`), runs on port 3010
- **Database:** PostgreSQL — isolated `pf` schema
- **Frontend:** React + Vite + Tailwind CSS in `ui/`; built output lands in `public/app/`
- **Pivot:** [Perspective](https://perspective.finos.org/) 4.4.0 loaded from CDN at runtime
- **Dev:** `npm run dev` (nodemon) in root; `npm run build` in `ui/`

---

## Project layout

```
server.js               Express entry point; pg pool; type parsers for bigint/numeric
routes/
  tables.js             GET /api/tables, /api/tables/:schema/:tname/preview
  sources.js            Source registration, col_meta, SQL generation
  versions.js           Version CRUD, baseline/reference load, data stream
  operations.js         scale, recode, clone, undo — the core forecast ops
  log.js                GET /api/versions/:id/log, DELETE /api/log/:logid
lib/
  sql_generator.js      buildFilterClause, token substitution helpers
  utils.js
setup_sql/
  01_schema.sql         pf schema DDL — run once to install
ui/src/
  views/
    Setup.jsx           DB browser, source registration, col_meta editor
    Baseline.jsx        Version management, baseline workbench, reference load
    Forecast.jsx        Perspective pivot + operation panel (Scale/Recode/Clone)
    Sidebar.jsx         3-step collapsible nav
    StatusBar.jsx       Source · version · row count · status
    Timeline.jsx        Date-range preview bar for baseline segments
```

---

## Database schema (`pf`)

- **`pf.source`** — registered source tables
- **`pf.col_meta`** — column roles: `dimension` | `value` | `units` | `date` | `filter` | `ignore`; `is_key` marks dimensions used in slice WHERE clauses
- **`pf.version`** — named forecast scenarios; `exclude_iters` (default `["reference"]`) blocks those iter values from all operations
- **`pf.fc_{tname}_{version_id}`** — one forecast table per version; contains both operational rows (`iter = baseline|scale|recode|clone`) and reference rows (`iter = reference`)
- **`pf.log`** — audit log; every write gets one entry; `slice` + `params` stored as jsonb
- **`pf.sql`** — generated SQL templates per source/operation; tokens substituted at request time

### Key token substitution tokens
`{{fc_table}}`, `{{where_clause}}`, `{{exclude_clause}}`, `{{logid}}`, `{{pf_user}}`, `{{value_incr}}`, `{{units_incr}}`, `{{pct}}`, `{{set_clause}}`, `{{scale_factor}}`, `{{date_offset}}`, `{{filter_clause}}`

---

## Core data flow

### Initial load (Forecast view)
`GET /api/versions/:id/data` → Arrow IPC binary stream → `worker.table(buffer)` in Perspective WASM

**Why one batch (not streaming):** pg returns `bigint`/`numeric` as strings by default — type parsers in `server.js` coerce them to numbers. Per-batch Arrow encoding creates independent dictionaries that cause Perspective WASM to crash on dictionary replacement messages. Server accumulates all rows, emits one record batch.

### Forecast operations
POST to `/api/versions/:id/{scale|recode|clone}` → SQL executed with `RETURNING *` → new rows returned as JSON → `pspTable.update(rows)` — no full reload.

### Undo
`DELETE /api/log/:logid` → removes rows by logid → **full Perspective reload** (known wart).

---

## Slice mechanics

When the user clicks a pivot cell, `perspective-click` fires. The handler in `Forecast.jsx` extracts `[col, '==', value]` filters from `detail.config.filter` — only `role = dimension` columns are kept as the slice. This slice populates the operation panel and is sent as the `slice` object in all operation POST bodies.

**Limitation:** computed columns created by Perspective's split_by (e.g. Month, YearDate) don't map back to raw rows — only native dimension columns work for slice extraction.

---

## Operation SQL patterns

All three operations follow the same structure: insert a `pf.log` row in a CTE, then insert forecast rows referencing its id. `{{where_clause}}` is built from the slice; `{{exclude_clause}}` blocks `exclude_iters` rows.

- **Scale** — distributes `value_incr`/`units_incr` proportionally across rows in the slice using window functions
- **Recode** — inserts negative rows (zero out original) + positive rows with `{{set_clause}}` dimension overrides; both share the same logid
- **Clone** — copies the slice with `{{set_clause}}` overrides and `{{scale_factor}}` multiplier; original untouched

`build_where()` validates every slice key against col_meta (only `role = dimension` allowed). Values are escaped but not parameterized — consistent with existing patterns, debuggable in pg logs.

---

## Known issues / active work (see todo.md for detail)

- Operation panel (Scale/Recode/Clone) wiring to API is a stub — needs completion
- Status bar is hardcoded — needs to reflect actual selected source/version
- Load progress bar is jittery — needs throttle (~10 updates/sec)
- Default pivot layout should be configurable per source (currently hardcodes first 2 dimensions)
- Source/version selection doesn't persist across page reload
- Col_meta / version schema drift: if col_meta roles change after a version's forecast table is created, SQL and DDL go out of sync — workaround is to delete and recreate the version

## Deferred (not in v1)
Baseline replay (`replay: true` returns 501), approval workflow, territory filtering, export, version comparison, multi-DB connections.