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+# pivot_forecast
+
+Sales forecasting API using Node.js/Express + PostgreSQL. Takes historical sales data and generates forecast baselines, with the ability to scale/adjust forecasts for different scenarios.
+
+## Project Structure
+
+```
+pivot_forecast/
+├── index.js                 # Express server (2 routes: /baseline, /scale)
+├── package.json
+├── .env                     # DB connection (host, port, user, password, database)
+├── routes/
+│   ├── baseline/
+│   │   ├── baseline.sql     # SQL for baseline generation
+│   │   ├── generate_route_sql.sh
+│   │   └── req.json         # Example request
+│   └── scale/
+│       ├── scale.sql        # SQL for scaling
+│       ├── generate_route_sql.sh
+│       └── req.json
+├── setup_sql/
+│   ├── 01_schema.sql        # Create fc schema, tables, period data
+│   ├── 02_target_info.sql   # Populate target_meta from dcard columns
+│   └── 03_build_master_tables.sql
+└── readme.md
+```
+
+## Database Schema (`fc` schema)
+
+### Tables
+
+| Table | Purpose |
+|-------|---------|
+| `fc.dcard` | Main sales data (copied from source at setup) |
+| `fc.target_meta` | Column metadata for dcard |
+| `fc.appcols` | App column definitions (value, cost, units, dates, status) |
+| `fc.log` | Forecast change log (JSONB) |
+| `fc.sql` | Stored SQL commands |
+| `fc.perd` | Fiscal period/calendar (2008-2023) |
+
+### target_meta Column Definitions
+
+| Field | Description |
+|-------|-------------|
+| `schema` | Schema of target table |
+| `tname` | Table name |
+| `cname` | Column name |
+| `opos` | Ordinal position |
+| `func` | Functional entity (e.g., "cost", "scust") - creates master table |
+| `fkey` | Primary key for functional entity |
+| `fcol` | Associated field in master table if different |
+| `dtype` | Data type (numeric, text, date) |
+| `appcol` | App-facing column name (e.g., "customer", "item") |
+| `pretty` | User-friendly display name |
+
+**Example target_meta row:**
+```sql
+| fc      | live    | fb_cst_loc     | 91   | cost         |              | fb_cst_loc     | numeric |              |        |
+```
+
+### appcols Requirements
+
+| Column | Type | Required | Default |
+|--------|------|----------|---------|
+| value | numeric | yes | - |
+| cost | numeric | yes | 0 |
+| units | numeric | yes | 0 |
+| order_date | date | yes | - |
+| ship_date | date | no | - |
+| order_status | text | yes | CLOSED |
+| version | text | yes | ACTUALS |
+| iter | text | yes | ACTUALS |
+| logid | bigint | yes | - |
+| tag | text | yes | - |
+| comment | text | yes | - |
+| customer | text | no | - |
+| item | text | no | - |
+
+## Setup
+
+### 1. Configure Environment
+```bash
+cp .env-sample .env
+# Edit .env with your PostgreSQL credentials
+```
+
+### 2. Run Database Setup
+```bash
+psql -h $host -U $user -d $database -f setup_sql/01_schema.sql
+psql -h $host -U $user -d $database -f setup_sql/02_target_info.sql
+psql -h $host -U $user -d $database -f setup_sql/03_build_master_tables.sql
+```
+
+### 3. Populate target_meta
+Edit `target_meta` with the column mappings for your data:
+
+```sql
+UPDATE fc.target_meta SET func = 'cost', fkey = '', appcol = 'cost' WHERE cname = 'fb_cst_loc';
+UPDATE fc.target_meta SET func = 'scust', fkey = 'ship_cust', appcol = 'customer' WHERE cname = 'ship_cust';
+-- etc.
+```
+
+### 4. Generate Route SQL
+```bash
+./routes/baseline/generate_route_sql.sh
+./routes/scale/generate_route_sql.sh
+```
+
+### 5. Start Server
+```bash
+node index.js
+# Server runs on port in .env (default 3000)
+```
+
+## API Routes
+
+### GET /baseline
+Generate forecast baseline - mirrors historical data for forecast periods.
+
+**Request body:**
+```json
+{
+  "app_forecast_name": "Q1_2024",
+  "app_forecast_version": "v1",
+  "app_scenario": {
+    "drange": "[2024-01-01,2024-03-31)"
+  }
+}
+```
+
+**Example curl:**
+```bash
+curl -X GET http://localhost:3000/baseline \
+  -H "Content-Type: application/json" \
+  -d '{"app_forecast_name":"Q1_2024","app_forecast_version":"v1","app_scenario":{"drange":"[2024-01-01,2024-03-31)"}}'
+```
+
+### GET /scale
+Scale a selected data slice by specified amounts.
+
+**Request body:**
+```json
+{
+  "app_forecast_name": "Q1_2024_scaled",
+  "app_where": "part = 'XFRM500'",
+  "app_scenario": {
+    "scust": "Sanford and Son"
+  }
+}
+```
+
+**Example curl:**
+```bash
+curl -X GET http://localhost:3000/scale \
+  -H "Content-Type: application/json" \
+  -d '{"app_forecast_name":"Q1_2024_scaled","app_scenario":{"scust":"Sanford and Son"}}'
+```
+
+## Common Tasks
+
+### Add a new forecast dimension
+1. Add column mapping to `fc.target_meta`:
+   ```sql
+   INSERT INTO fc.target_meta (schema, tname, cname, opos, func, fkey, fcol, dtype, appcol)
+   VALUES ('fc', 'dcard', 'new_column', 99, 'new_func', 'new_column', 'new_column', 'text', 'new_dim');
+   ```
+2. Run `./routes/baseline/generate_route_sql.sh`
+3. Run `./routes/scale/generate_route_sql.sh`
+
+### Adjust forecast for a specific customer
+```bash
+curl -X GET http://localhost:3000/scale \
+  -H "Content-Type: application/json" \
+  -d '{
+    "app_forecast_name": "Adjusted_Forecast",
+    "app_scenario": {
+      "scust": ["Customer A", "Customer B"]
+    }
+  }'
+```
+
+### View forecast logs
+```sql
+SELECT * FROM fc.log ORDER BY id DESC LIMIT 10;
+```
+
+### Add new fiscal periods
+Insert into `fc.perd` with columns: comp, fsyr, perds, perd, fspr, sdat, edat, drange, capr, ndays, ssyr, sspr
+
+## Known Issues
+
+- [ ] SQL stored in files instead of database table
+- [ ] Null handling in func tables (orders without quotes)
+- [ ] Multi-table target_meta support
+- [ ] Currency adjustment handling (which currency?)
+
+## Testing
+
+No automated test suite. Manual testing via curl commands in `routes/*/req.json` examples.