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Add new schemas and scripts for calculate

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Matt
2025-03-29 17:08:30 -04:00
parent f4854423ab
commit 54cc4be1e3
6 changed files with 901 additions and 228 deletions
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113
inventory-server/db/config-schema-new.sql Normal file
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-- Drop tables in reverse order of dependency
DROP TABLE IF EXISTS public.settings_product CASCADE;
DROP TABLE IF EXISTS public.settings_vendor CASCADE;
DROP TABLE IF EXISTS public.settings_global CASCADE;
-- Table Definition: settings_global
CREATE TABLE public.settings_global (
setting_key VARCHAR PRIMARY KEY,
setting_value VARCHAR NOT NULL,
description TEXT,
updated_at TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- Table Definition: settings_vendor
CREATE TABLE public.settings_vendor (
vendor VARCHAR PRIMARY KEY, -- Matches products.vendor
default_lead_time_days INT,
default_days_of_stock INT,
updated_at TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- Index for faster lookups if needed (PK usually sufficient)
-- CREATE INDEX idx_settings_vendor_vendor ON public.settings_vendor(vendor);
-- Table Definition: settings_product
CREATE TABLE public.settings_product (
pid INT8 PRIMARY KEY,
lead_time_days INT, -- Overrides vendor/global
days_of_stock INT, -- Overrides vendor/global
safety_stock INT DEFAULT 0, -- Minimum desired stock level
forecast_method VARCHAR DEFAULT 'standard', -- e.g., 'standard', 'seasonal'
exclude_from_forecast BOOLEAN DEFAULT FALSE,
updated_at TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
CONSTRAINT fk_settings_product_pid FOREIGN KEY (pid) REFERENCES public.products(pid) ON DELETE CASCADE ON UPDATE CASCADE
);
-- Description: Inserts or updates standard default global settings.
-- Safe to rerun; will update existing keys with these default values.
-- Dependencies: `settings_global` table must exist.
-- Frequency: Run once initially, or rerun if you want to reset global defaults.
INSERT INTO public.settings_global (setting_key, setting_value, description) VALUES
('abc_revenue_threshold_a', '0.80', 'Revenue percentage for Class A (cumulative)'),
('abc_revenue_threshold_b', '0.95', 'Revenue percentage for Class B (cumulative)'),
('abc_calculation_basis', 'revenue_30d', 'Metric for ABC calc (revenue_30d, sales_30d, lifetime_revenue)'),
('abc_calculation_period', '30', 'Days period for ABC calculation if not lifetime'),
('default_forecast_method', 'standard', 'Default forecast method (standard, seasonal)'),
('default_lead_time_days', '14', 'Global default lead time in days'),
('default_days_of_stock', '30', 'Global default days of stock coverage target'),
-- Set default safety stock to 0 units. Can be overridden per product.
-- If you wanted safety stock in days, you'd store 'days' here and calculate units later.
('default_safety_stock_units', '0', 'Global default safety stock in units')
ON CONFLICT (setting_key) DO UPDATE SET
setting_value = EXCLUDED.setting_value,
description = EXCLUDED.description,
updated_at = CURRENT_TIMESTAMP; -- Update timestamp if default value changes
-- Description: Creates placeholder rows in `settings_vendor` for each unique vendor
-- found in the `products` table. Does NOT set specific overrides.
-- Safe to rerun; will NOT overwrite existing vendor settings.
-- Dependencies: `settings_vendor` table must exist, `products` table populated.
-- Frequency: Run once after initial product load, or periodically if new vendors are added.
INSERT INTO public.settings_vendor (
vendor,
default_lead_time_days,
default_days_of_stock
-- updated_at will use its default CURRENT_TIMESTAMP on insert
)
SELECT
DISTINCT p.vendor,
-- Explicitly cast NULL to INTEGER to resolve type mismatch
CAST(NULL AS INTEGER),
CAST(NULL AS INTEGER)
FROM
public.products p
WHERE
p.vendor IS NOT NULL
AND p.vendor <> '' -- Exclude blank vendors if necessary
ON CONFLICT (vendor) DO NOTHING; -- IMPORTANT: Do not overwrite existing vendor settings
SELECT COUNT(*) FROM public.settings_vendor; -- Verify rows were inserted
-- Description: Creates placeholder rows in `settings_product` for each unique product
-- found in the `products` table. Sets basic defaults but no specific overrides.
-- Safe to rerun; will NOT overwrite existing product settings.
-- Dependencies: `settings_product` table must exist, `products` table populated.
-- Frequency: Run once after initial product load, or periodically if new products are added.
INSERT INTO public.settings_product (
pid,
lead_time_days, -- NULL = Inherit from Vendor/Global
days_of_stock, -- NULL = Inherit from Vendor/Global
safety_stock, -- Default to 0 units initially
forecast_method, -- NULL = Inherit from Global ('standard')
exclude_from_forecast -- Default to FALSE
-- updated_at will use its default CURRENT_TIMESTAMP on insert
)
SELECT
p.pid,
CAST(NULL AS INTEGER), -- Explicitly cast NULL to INTEGER
CAST(NULL AS INTEGER), -- Explicitly cast NULL to INTEGER
COALESCE((SELECT setting_value::int FROM settings_global WHERE setting_key = 'default_safety_stock_units'), 0), -- Use global default safety stock units
CAST(NULL AS VARCHAR), -- Cast NULL to VARCHAR for forecast_method (already varchar, but explicit)
FALSE -- Default: Include in forecast
FROM
public.products p
ON CONFLICT (pid) DO NOTHING; -- IMPORTANT: Do not overwrite existing product-specific settings

456
inventory-server/db/config-schema.sql
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@@ -1,261 +1,261 @@
-- Configuration tables schema
-- -- Configuration tables schema
-- Create function for updating timestamps if it doesn't exist
CREATE OR REPLACE FUNCTION update_updated_column()
RETURNS TRIGGER AS $$
BEGIN
NEW.updated = CURRENT_TIMESTAMP;
RETURN NEW;
END;
$$ language 'plpgsql';
-- -- Create function for updating timestamps if it doesn't exist
-- CREATE OR REPLACE FUNCTION update_updated_column()
-- RETURNS TRIGGER AS $$
-- BEGIN
-- NEW.updated = CURRENT_TIMESTAMP;
-- RETURN NEW;
-- END;
-- $$ language 'plpgsql';
-- Create function for updating updated_at timestamps
CREATE OR REPLACE FUNCTION update_updated_at_column()
RETURNS TRIGGER AS $$
BEGIN
NEW.updated_at = CURRENT_TIMESTAMP;
RETURN NEW;
END;
$$ language 'plpgsql';
-- -- Create function for updating updated_at timestamps
-- CREATE OR REPLACE FUNCTION update_updated_at_column()
-- RETURNS TRIGGER AS $$
-- BEGIN
-- NEW.updated_at = CURRENT_TIMESTAMP;
-- RETURN NEW;
-- END;
-- $$ language 'plpgsql';
-- Stock threshold configurations
CREATE TABLE stock_thresholds (
id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors
critical_days INTEGER NOT NULL DEFAULT 7,
reorder_days INTEGER NOT NULL DEFAULT 14,
overstock_days INTEGER NOT NULL DEFAULT 90,
low_stock_threshold INTEGER NOT NULL DEFAULT 5,
min_reorder_quantity INTEGER NOT NULL DEFAULT 1,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE (category_id, vendor)
);
-- -- Stock threshold configurations
-- CREATE TABLE stock_thresholds (
-- id INTEGER NOT NULL,
-- category_id BIGINT, -- NULL means default/global threshold
-- vendor VARCHAR(100), -- NULL means applies to all vendors
-- critical_days INTEGER NOT NULL DEFAULT 7,
-- reorder_days INTEGER NOT NULL DEFAULT 14,
-- overstock_days INTEGER NOT NULL DEFAULT 90,
-- low_stock_threshold INTEGER NOT NULL DEFAULT 5,
-- min_reorder_quantity INTEGER NOT NULL DEFAULT 1,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (id),
-- FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
-- UNIQUE (category_id, vendor)
-- );
CREATE TRIGGER update_stock_thresholds_updated
BEFORE UPDATE ON stock_thresholds
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_stock_thresholds_updated
-- BEFORE UPDATE ON stock_thresholds
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
CREATE INDEX idx_st_metrics ON stock_thresholds(category_id, vendor);
-- CREATE INDEX idx_st_metrics ON stock_thresholds(category_id, vendor);
-- Lead time threshold configurations
CREATE TABLE lead_time_thresholds (
id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors
target_days INTEGER NOT NULL DEFAULT 14,
warning_days INTEGER NOT NULL DEFAULT 21,
critical_days INTEGER NOT NULL DEFAULT 30,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE (category_id, vendor)
);
-- -- Lead time threshold configurations
-- CREATE TABLE lead_time_thresholds (
-- id INTEGER NOT NULL,
-- category_id BIGINT, -- NULL means default/global threshold
-- vendor VARCHAR(100), -- NULL means applies to all vendors
-- target_days INTEGER NOT NULL DEFAULT 14,
-- warning_days INTEGER NOT NULL DEFAULT 21,
-- critical_days INTEGER NOT NULL DEFAULT 30,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (id),
-- FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
-- UNIQUE (category_id, vendor)
-- );
CREATE TRIGGER update_lead_time_thresholds_updated
BEFORE UPDATE ON lead_time_thresholds
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_lead_time_thresholds_updated
-- BEFORE UPDATE ON lead_time_thresholds
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
-- Sales velocity window configurations
CREATE TABLE sales_velocity_config (
id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors
daily_window_days INTEGER NOT NULL DEFAULT 30,
weekly_window_days INTEGER NOT NULL DEFAULT 7,
monthly_window_days INTEGER NOT NULL DEFAULT 90,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE (category_id, vendor)
);
-- -- Sales velocity window configurations
-- CREATE TABLE sales_velocity_config (
-- id INTEGER NOT NULL,
-- category_id BIGINT, -- NULL means default/global threshold
-- vendor VARCHAR(100), -- NULL means applies to all vendors
-- daily_window_days INTEGER NOT NULL DEFAULT 30,
-- weekly_window_days INTEGER NOT NULL DEFAULT 7,
-- monthly_window_days INTEGER NOT NULL DEFAULT 90,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (id),
-- FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
-- UNIQUE (category_id, vendor)
-- );
CREATE TRIGGER update_sales_velocity_config_updated
BEFORE UPDATE ON sales_velocity_config
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_sales_velocity_config_updated
-- BEFORE UPDATE ON sales_velocity_config
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
CREATE INDEX idx_sv_metrics ON sales_velocity_config(category_id, vendor);
-- CREATE INDEX idx_sv_metrics ON sales_velocity_config(category_id, vendor);
-- ABC Classification configurations
CREATE TABLE abc_classification_config (
id INTEGER NOT NULL PRIMARY KEY,
a_threshold DECIMAL(5,2) NOT NULL DEFAULT 20.0,
b_threshold DECIMAL(5,2) NOT NULL DEFAULT 50.0,
classification_period_days INTEGER NOT NULL DEFAULT 90,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
-- -- ABC Classification configurations
-- CREATE TABLE abc_classification_config (
-- id INTEGER NOT NULL PRIMARY KEY,
-- a_threshold DECIMAL(5,2) NOT NULL DEFAULT 20.0,
-- b_threshold DECIMAL(5,2) NOT NULL DEFAULT 50.0,
-- classification_period_days INTEGER NOT NULL DEFAULT 90,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
-- );
CREATE TRIGGER update_abc_classification_config_updated
BEFORE UPDATE ON abc_classification_config
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_abc_classification_config_updated
-- BEFORE UPDATE ON abc_classification_config
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
-- Safety stock configurations
CREATE TABLE safety_stock_config (
id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors
coverage_days INTEGER NOT NULL DEFAULT 14,
service_level DECIMAL(5,2) NOT NULL DEFAULT 95.0,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE (category_id, vendor)
);
-- -- Safety stock configurations
-- CREATE TABLE safety_stock_config (
-- id INTEGER NOT NULL,
-- category_id BIGINT, -- NULL means default/global threshold
-- vendor VARCHAR(100), -- NULL means applies to all vendors
-- coverage_days INTEGER NOT NULL DEFAULT 14,
-- service_level DECIMAL(5,2) NOT NULL DEFAULT 95.0,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (id),
-- FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
-- UNIQUE (category_id, vendor)
-- );
CREATE TRIGGER update_safety_stock_config_updated
BEFORE UPDATE ON safety_stock_config
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_safety_stock_config_updated
-- BEFORE UPDATE ON safety_stock_config
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
CREATE INDEX idx_ss_metrics ON safety_stock_config(category_id, vendor);
-- CREATE INDEX idx_ss_metrics ON safety_stock_config(category_id, vendor);
-- Turnover rate configurations
CREATE TABLE turnover_config (
id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors
calculation_period_days INTEGER NOT NULL DEFAULT 30,
target_rate DECIMAL(10,2) NOT NULL DEFAULT 1.0,
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE (category_id, vendor)
);
-- -- Turnover rate configurations
-- CREATE TABLE turnover_config (
-- id INTEGER NOT NULL,
-- category_id BIGINT, -- NULL means default/global threshold
-- vendor VARCHAR(100), -- NULL means applies to all vendors
-- calculation_period_days INTEGER NOT NULL DEFAULT 30,
-- target_rate DECIMAL(10,2) NOT NULL DEFAULT 1.0,
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (id),
-- FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
-- UNIQUE (category_id, vendor)
-- );
CREATE TRIGGER update_turnover_config_updated
BEFORE UPDATE ON turnover_config
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_turnover_config_updated
-- BEFORE UPDATE ON turnover_config
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
-- Create table for sales seasonality factors
CREATE TABLE sales_seasonality (
month INTEGER NOT NULL,
seasonality_factor DECIMAL(5,3) DEFAULT 0,
last_updated TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (month),
CONSTRAINT month_range CHECK (month BETWEEN 1 AND 12),
CONSTRAINT seasonality_range CHECK (seasonality_factor BETWEEN -1.0 AND 1.0)
);
-- -- Create table for sales seasonality factors
-- CREATE TABLE sales_seasonality (
-- month INTEGER NOT NULL,
-- seasonality_factor DECIMAL(5,3) DEFAULT 0,
-- last_updated TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP,
-- PRIMARY KEY (month),
-- CONSTRAINT month_range CHECK (month BETWEEN 1 AND 12),
-- CONSTRAINT seasonality_range CHECK (seasonality_factor BETWEEN -1.0 AND 1.0)
-- );
CREATE TRIGGER update_sales_seasonality_updated
BEFORE UPDATE ON sales_seasonality
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_sales_seasonality_updated
-- BEFORE UPDATE ON sales_seasonality
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
-- Create table for financial calculation parameters
CREATE TABLE financial_calc_config (
id INTEGER NOT NULL PRIMARY KEY,
order_cost DECIMAL(10,2) NOT NULL DEFAULT 25.00, -- The fixed cost per purchase order (used in EOQ)
holding_rate DECIMAL(10,4) NOT NULL DEFAULT 0.25, -- The annual inventory holding cost as a percentage of unit cost (used in EOQ)
service_level_z_score DECIMAL(10,4) NOT NULL DEFAULT 1.96, -- Z-score for ~95% service level (used in Safety Stock)
min_reorder_qty INTEGER NOT NULL DEFAULT 1, -- Minimum reorder quantity
default_reorder_qty INTEGER NOT NULL DEFAULT 5, -- Default reorder quantity when sales data is insufficient
default_safety_stock INTEGER NOT NULL DEFAULT 5, -- Default safety stock when sales data is insufficient
created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
);
-- -- Create table for financial calculation parameters
-- CREATE TABLE financial_calc_config (
-- id INTEGER NOT NULL PRIMARY KEY,
-- order_cost DECIMAL(10,2) NOT NULL DEFAULT 25.00, -- The fixed cost per purchase order (used in EOQ)
-- holding_rate DECIMAL(10,4) NOT NULL DEFAULT 0.25, -- The annual inventory holding cost as a percentage of unit cost (used in EOQ)
-- service_level_z_score DECIMAL(10,4) NOT NULL DEFAULT 1.96, -- Z-score for ~95% service level (used in Safety Stock)
-- min_reorder_qty INTEGER NOT NULL DEFAULT 1, -- Minimum reorder quantity
-- default_reorder_qty INTEGER NOT NULL DEFAULT 5, -- Default reorder quantity when sales data is insufficient
-- default_safety_stock INTEGER NOT NULL DEFAULT 5, -- Default safety stock when sales data is insufficient
-- created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
-- updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP
-- );
CREATE TRIGGER update_financial_calc_config_updated
BEFORE UPDATE ON financial_calc_config
FOR EACH ROW
EXECUTE FUNCTION update_updated_at_column();
-- CREATE TRIGGER update_financial_calc_config_updated
-- BEFORE UPDATE ON financial_calc_config
-- FOR EACH ROW
-- EXECUTE FUNCTION update_updated_at_column();
-- Insert default global thresholds
INSERT INTO stock_thresholds (id, category_id, vendor, critical_days, reorder_days, overstock_days)
VALUES (1, NULL, NULL, 7, 14, 90)
ON CONFLICT (id) DO UPDATE SET
critical_days = EXCLUDED.critical_days,
reorder_days = EXCLUDED.reorder_days,
overstock_days = EXCLUDED.overstock_days;
-- -- Insert default global thresholds
-- INSERT INTO stock_thresholds (id, category_id, vendor, critical_days, reorder_days, overstock_days)
-- VALUES (1, NULL, NULL, 7, 14, 90)
-- ON CONFLICT (id) DO UPDATE SET
-- critical_days = EXCLUDED.critical_days,
-- reorder_days = EXCLUDED.reorder_days,
-- overstock_days = EXCLUDED.overstock_days;
INSERT INTO lead_time_thresholds (id, category_id, vendor, target_days, warning_days, critical_days)
VALUES (1, NULL, NULL, 14, 21, 30)
ON CONFLICT (id) DO UPDATE SET
target_days = EXCLUDED.target_days,
warning_days = EXCLUDED.warning_days,
critical_days = EXCLUDED.critical_days;
-- INSERT INTO lead_time_thresholds (id, category_id, vendor, target_days, warning_days, critical_days)
-- VALUES (1, NULL, NULL, 14, 21, 30)
-- ON CONFLICT (id) DO UPDATE SET
-- target_days = EXCLUDED.target_days,
-- warning_days = EXCLUDED.warning_days,
-- critical_days = EXCLUDED.critical_days;
INSERT INTO sales_velocity_config (id, category_id, vendor, daily_window_days, weekly_window_days, monthly_window_days)
VALUES (1, NULL, NULL, 30, 7, 90)
ON CONFLICT (id) DO UPDATE SET
daily_window_days = EXCLUDED.daily_window_days,
weekly_window_days = EXCLUDED.weekly_window_days,
monthly_window_days = EXCLUDED.monthly_window_days;
-- INSERT INTO sales_velocity_config (id, category_id, vendor, daily_window_days, weekly_window_days, monthly_window_days)
-- VALUES (1, NULL, NULL, 30, 7, 90)
-- ON CONFLICT (id) DO UPDATE SET
-- daily_window_days = EXCLUDED.daily_window_days,
-- weekly_window_days = EXCLUDED.weekly_window_days,
-- monthly_window_days = EXCLUDED.monthly_window_days;
INSERT INTO abc_classification_config (id, a_threshold, b_threshold, classification_period_days)
VALUES (1, 20.0, 50.0, 90)
ON CONFLICT (id) DO UPDATE SET
a_threshold = EXCLUDED.a_threshold,
b_threshold = EXCLUDED.b_threshold,
classification_period_days = EXCLUDED.classification_period_days;
-- INSERT INTO abc_classification_config (id, a_threshold, b_threshold, classification_period_days)
-- VALUES (1, 20.0, 50.0, 90)
-- ON CONFLICT (id) DO UPDATE SET
-- a_threshold = EXCLUDED.a_threshold,
-- b_threshold = EXCLUDED.b_threshold,
-- classification_period_days = EXCLUDED.classification_period_days;
INSERT INTO safety_stock_config (id, category_id, vendor, coverage_days, service_level)
VALUES (1, NULL, NULL, 14, 95.0)
ON CONFLICT (id) DO UPDATE SET
coverage_days = EXCLUDED.coverage_days,
service_level = EXCLUDED.service_level;
-- INSERT INTO safety_stock_config (id, category_id, vendor, coverage_days, service_level)
-- VALUES (1, NULL, NULL, 14, 95.0)
-- ON CONFLICT (id) DO UPDATE SET
-- coverage_days = EXCLUDED.coverage_days,
-- service_level = EXCLUDED.service_level;
INSERT INTO turnover_config (id, category_id, vendor, calculation_period_days, target_rate)
VALUES (1, NULL, NULL, 30, 1.0)
ON CONFLICT (id) DO UPDATE SET
calculation_period_days = EXCLUDED.calculation_period_days,
target_rate = EXCLUDED.target_rate;
-- INSERT INTO turnover_config (id, category_id, vendor, calculation_period_days, target_rate)
-- VALUES (1, NULL, NULL, 30, 1.0)
-- ON CONFLICT (id) DO UPDATE SET
-- calculation_period_days = EXCLUDED.calculation_period_days,
-- target_rate = EXCLUDED.target_rate;
-- Insert default seasonality factors (neutral)
INSERT INTO sales_seasonality (month, seasonality_factor)
VALUES
(1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0),
(7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0)
ON CONFLICT (month) DO UPDATE SET
last_updated = CURRENT_TIMESTAMP;
-- -- Insert default seasonality factors (neutral)
-- INSERT INTO sales_seasonality (month, seasonality_factor)
-- VALUES
-- (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0),
-- (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0)
-- ON CONFLICT (month) DO UPDATE SET
-- last_updated = CURRENT_TIMESTAMP;
-- Insert default values
INSERT INTO financial_calc_config (id, order_cost, holding_rate, service_level_z_score, min_reorder_qty, default_reorder_qty, default_safety_stock)
VALUES (1, 25.00, 0.25, 1.96, 1, 5, 5)
ON CONFLICT (id) DO UPDATE SET
order_cost = EXCLUDED.order_cost,
holding_rate = EXCLUDED.holding_rate,
service_level_z_score = EXCLUDED.service_level_z_score,
min_reorder_qty = EXCLUDED.min_reorder_qty,
default_reorder_qty = EXCLUDED.default_reorder_qty,
default_safety_stock = EXCLUDED.default_safety_stock;
-- -- Insert default values
-- INSERT INTO financial_calc_config (id, order_cost, holding_rate, service_level_z_score, min_reorder_qty, default_reorder_qty, default_safety_stock)
-- VALUES (1, 25.00, 0.25, 1.96, 1, 5, 5)
-- ON CONFLICT (id) DO UPDATE SET
-- order_cost = EXCLUDED.order_cost,
-- holding_rate = EXCLUDED.holding_rate,
-- service_level_z_score = EXCLUDED.service_level_z_score,
-- min_reorder_qty = EXCLUDED.min_reorder_qty,
-- default_reorder_qty = EXCLUDED.default_reorder_qty,
-- default_safety_stock = EXCLUDED.default_safety_stock;
-- View to show thresholds with category names
CREATE OR REPLACE VIEW stock_thresholds_view AS
SELECT
st.*,
c.name as category_name,
CASE
WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 'Global Default'
WHEN st.category_id IS NULL THEN 'Vendor: ' || st.vendor
WHEN st.vendor IS NULL THEN 'Category: ' || c.name
ELSE 'Category: ' || c.name || ' / Vendor: ' || st.vendor
END as threshold_scope
FROM
stock_thresholds st
LEFT JOIN
categories c ON st.category_id = c.cat_id
ORDER BY
CASE
WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 1
WHEN st.category_id IS NULL THEN 2
WHEN st.vendor IS NULL THEN 3
ELSE 4
END,
c.name,
st.vendor;
-- -- View to show thresholds with category names
-- CREATE OR REPLACE VIEW stock_thresholds_view AS
-- SELECT
-- st.*,
-- c.name as category_name,
-- CASE
-- WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 'Global Default'
-- WHEN st.category_id IS NULL THEN 'Vendor: ' || st.vendor
-- WHEN st.vendor IS NULL THEN 'Category: ' || c.name
-- ELSE 'Category: ' || c.name || ' / Vendor: ' || st.vendor
-- END as threshold_scope
-- FROM
-- stock_thresholds st
-- LEFT JOIN
-- categories c ON st.category_id = c.cat_id
-- ORDER BY
-- CASE
-- WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 1
-- WHEN st.category_id IS NULL THEN 2
-- WHEN st.vendor IS NULL THEN 3
-- ELSE 4
-- END,
-- c.name,
-- st.vendor;
-- History and status tables
CREATE TABLE IF NOT EXISTS calculate_history (

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inventory-server/db/new-metrics-schema.sql → inventory-server/db/metrics-schema-new.sql
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-- Description: Calculates and updates daily aggregated product data for the current day.
-- Uses UPSERT (INSERT ON CONFLICT UPDATE) for idempotency.
-- Dependencies: Core import tables (products, orders, purchase_orders), calculate_status table.
-- Frequency: Hourly (Run ~5-10 minutes after hourly data import completes).
DO $$
DECLARE
_module_name VARCHAR := 'daily_snapshots';
_start_time TIMESTAMPTZ := clock_timestamp(); -- Time execution started
_last_calc_time TIMESTAMPTZ;
_target_date DATE := CURRENT_DATE; -- Always recalculate today for simplicity with hourly runs
BEGIN
-- Get the timestamp before the last successful run of this module
SELECT last_calculation_timestamp INTO _last_calc_time
FROM public.calculate_status
WHERE module_name = _module_name;
RAISE NOTICE 'Running % for date %. Start Time: %', _module_name, _target_date, _start_time;
-- Use CTEs to aggregate data for the target date
WITH SalesData AS (
SELECT
p.pid,
p.sku,
-- Aggregate Sales (Quantity > 0, Status not Canceled/Returned)
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.quantity ELSE 0 END), 0) AS units_sold,
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.price * o.quantity ELSE 0 END), 0.00) AS gross_revenue_unadjusted, -- Before discount
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.discount ELSE 0 END), 0.00) AS discounts,
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN COALESCE(o.costeach, p.landing_cost_price, p.cost_price) * o.quantity ELSE 0 END), 0.00) AS cogs,
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN p.regular_price * o.quantity ELSE 0 END), 0.00) AS gross_regular_revenue, -- Use current regular price for simplicity here
-- Aggregate Returns (Quantity < 0 or Status = Returned)
COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN ABS(o.quantity) ELSE 0 END), 0) AS units_returned,
COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN o.price * ABS(o.quantity) ELSE 0 END), 0.00) AS returns_revenue
FROM public.products p -- Start from products to include those with no orders today
LEFT JOIN public.orders o
ON p.pid = o.pid
AND o.date >= _target_date -- Filter orders for the target date
AND o.date < _target_date + INTERVAL '1 day'
GROUP BY p.pid, p.sku
),
ReceivingData AS (
SELECT
po.pid,
COALESCE(SUM((rh.item->>'qty')::numeric), 0) AS units_received,
COALESCE(SUM((rh.item->>'qty')::numeric * COALESCE((rh.item->>'cost')::numeric, po.cost_price)), 0.00) AS cost_received
FROM public.purchase_orders po
CROSS JOIN LATERAL jsonb_array_elements(po.receiving_history) AS rh(item)
WHERE (rh.item->>'received_at')::date = _target_date -- Filter receipts for the target date
GROUP BY po.pid
),
CurrentStock AS (
-- Select current stock values directly from products table
SELECT
pid,
stock_quantity,
COALESCE(landing_cost_price, cost_price, 0.00) as effective_cost_price,
COALESCE(price, 0.00) as current_price,
COALESCE(regular_price, 0.00) as current_regular_price
FROM public.products
)
-- Upsert into the daily snapshots table
INSERT INTO public.daily_product_snapshots (
snapshot_date,
pid,
sku,
eod_stock_quantity,
eod_stock_cost,
eod_stock_retail,
eod_stock_gross,
stockout_flag,
units_sold,
units_returned,
gross_revenue,
discounts,
returns_revenue,
net_revenue,
cogs,
gross_regular_revenue,
profit,
units_received,
cost_received,
calculation_timestamp
)
SELECT
_target_date AS snapshot_date,
p.pid,
p.sku,
-- Inventory Metrics (Using CurrentStock)
cs.stock_quantity AS eod_stock_quantity,
cs.stock_quantity * cs.effective_cost_price AS eod_stock_cost,
cs.stock_quantity * cs.current_price AS eod_stock_retail,
cs.stock_quantity * cs.current_regular_price AS eod_stock_gross,
(cs.stock_quantity <= 0) AS stockout_flag,
-- Sales Metrics (From SalesData)
COALESCE(sd.units_sold, 0),
COALESCE(sd.units_returned, 0),
COALESCE(sd.gross_revenue_unadjusted, 0.00),
COALESCE(sd.discounts, 0.00),
COALESCE(sd.returns_revenue, 0.00),
COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) AS net_revenue,
COALESCE(sd.cogs, 0.00),
COALESCE(sd.gross_regular_revenue, 0.00),
(COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00)) - COALESCE(sd.cogs, 0.00) AS profit, -- Basic profit: Net Revenue - COGS
-- Receiving Metrics (From ReceivingData)
COALESCE(rd.units_received, 0),
COALESCE(rd.cost_received, 0.00),
_start_time -- Timestamp of this calculation run
FROM public.products p
LEFT JOIN CurrentStock cs ON p.pid = cs.pid
LEFT JOIN SalesData sd ON p.pid = sd.pid
LEFT JOIN ReceivingData rd ON p.pid = rd.pid
WHERE p.pid IS NOT NULL -- Ensure we only insert for existing products
ON CONFLICT (snapshot_date, pid) DO UPDATE SET
sku = EXCLUDED.sku,
eod_stock_quantity = EXCLUDED.eod_stock_quantity,
eod_stock_cost = EXCLUDED.eod_stock_cost,
eod_stock_retail = EXCLUDED.eod_stock_retail,
eod_stock_gross = EXCLUDED.eod_stock_gross,
stockout_flag = EXCLUDED.stockout_flag,
units_sold = EXCLUDED.units_sold,
units_returned = EXCLUDED.units_returned,
gross_revenue = EXCLUDED.gross_revenue,
discounts = EXCLUDED.discounts,
returns_revenue = EXCLUDED.returns_revenue,
net_revenue = EXCLUDED.net_revenue,
cogs = EXCLUDED.cogs,
gross_regular_revenue = EXCLUDED.gross_regular_revenue,
profit = EXCLUDED.profit,
units_received = EXCLUDED.units_received,
cost_received = EXCLUDED.cost_received,
calculation_timestamp = EXCLUDED.calculation_timestamp; -- Use the timestamp from this run
-- Update the status table with the timestamp from the START of this run
UPDATE public.calculate_status
SET last_calculation_timestamp = _start_time
WHERE module_name = _module_name;
RAISE NOTICE 'Finished % for date %. Duration: %', _module_name, _target_date, clock_timestamp() - _start_time;
END $$;

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-- Description: Calculates metrics that don't need hourly updates, like ABC class
-- and average lead time.
-- Dependencies: product_metrics, purchase_orders, settings_global, calculate_status.
-- Frequency: Daily or Weekly (e.g., run via cron job overnight).
DO $$
DECLARE
_module_name VARCHAR := 'periodic_metrics';
_start_time TIMESTAMPTZ := clock_timestamp();
_last_calc_time TIMESTAMPTZ;
_abc_basis VARCHAR;
_abc_period INT;
_threshold_a NUMERIC;
_threshold_b NUMERIC;
BEGIN
-- Get the timestamp before the last successful run of this module
SELECT last_calculation_timestamp INTO _last_calc_time
FROM public.calculate_status
WHERE module_name = _module_name;
RAISE NOTICE 'Running % module. Start Time: %', _module_name, _start_time;
-- 1. Calculate Average Lead Time
RAISE NOTICE 'Calculating Average Lead Time...';
WITH LeadTimes AS (
SELECT
pid,
AVG(GREATEST(1, DATE_PART('day', last_received_date - date))) AS avg_days -- Use GREATEST(1,...) to avoid 0 or negative days
FROM public.purchase_orders
WHERE status = 'received' -- Or potentially 'full_received' if using that status
AND last_received_date IS NOT NULL
AND date IS NOT NULL
AND last_received_date >= date -- Ensure received date is not before order date
GROUP BY pid
)
UPDATE public.product_metrics pm
SET avg_lead_time_days = lt.avg_days::int
FROM LeadTimes lt
WHERE pm.pid = lt.pid
AND pm.avg_lead_time_days IS DISTINCT FROM lt.avg_days::int; -- Only update if changed
RAISE NOTICE 'Finished Average Lead Time calculation.';
-- 2. Calculate ABC Classification
RAISE NOTICE 'Calculating ABC Classification...';
-- Get ABC settings
SELECT setting_value INTO _abc_basis FROM public.settings_global WHERE setting_key = 'abc_calculation_basis' LIMIT 1;
SELECT setting_value::numeric INTO _threshold_a FROM public.settings_global WHERE setting_key = 'abc_revenue_threshold_a' LIMIT 1;
SELECT setting_value::numeric INTO _threshold_b FROM public.settings_global WHERE setting_key = 'abc_revenue_threshold_b' LIMIT 1;
_abc_basis := COALESCE(_abc_basis, 'revenue_30d'); -- Default basis
_threshold_a := COALESCE(_threshold_a, 0.80);
_threshold_b := COALESCE(_threshold_b, 0.95);
RAISE NOTICE 'Using ABC Basis: %, Threshold A: %, Threshold B: %', _abc_basis, _threshold_a, _threshold_b;
WITH RankedProducts AS (
SELECT
pid,
-- Dynamically select the metric based on setting
CASE _abc_basis
WHEN 'sales_30d' THEN COALESCE(sales_30d, 0)
WHEN 'lifetime_revenue' THEN COALESCE(lifetime_revenue, 0)::numeric -- Cast needed if different type
ELSE COALESCE(revenue_30d, 0) -- Default to revenue_30d
END AS metric_value
FROM public.product_metrics
WHERE is_replenishable = TRUE -- Typically only classify replenishable items
),
Cumulative AS (
SELECT
pid,
metric_value,
SUM(metric_value) OVER (ORDER BY metric_value DESC NULLS LAST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as cumulative_metric,
SUM(metric_value) OVER () as total_metric
FROM RankedProducts
WHERE metric_value > 0 -- Exclude items with no contribution
)
UPDATE public.product_metrics pm
SET abc_class =
CASE
WHEN c.cumulative_metric / NULLIF(c.total_metric, 0) <= _threshold_a THEN 'A'
WHEN c.cumulative_metric / NULLIF(c.total_metric, 0) <= _threshold_b THEN 'B'
ELSE 'C'
END
FROM Cumulative c
WHERE pm.pid = c.pid
AND pm.abc_class IS DISTINCT FROM ( -- Only update if changed
CASE
WHEN c.cumulative_metric / NULLIF(c.total_metric, 0) <= _threshold_a THEN 'A'
WHEN c.cumulative_metric / NULLIF(c.total_metric, 0) <= _threshold_b THEN 'B'
ELSE 'C'
END);
-- Set non-contributing or non-replenishable to 'C' or NULL if preferred
UPDATE public.product_metrics
SET abc_class = 'C' -- Or NULL
WHERE abc_class IS NULL AND is_replenishable = TRUE; -- Catch those with 0 metric value
UPDATE public.product_metrics
SET abc_class = NULL -- Or 'N/A'?
WHERE is_replenishable = FALSE AND abc_class IS NOT NULL; -- Unclassify non-replenishable items
RAISE NOTICE 'Finished ABC Classification calculation.';
-- Add other periodic calculations here if needed (e.g., recalculating first/last dates)
-- Update the status table with the timestamp from the START of this run
UPDATE public.calculate_status
SET last_calculation_timestamp = _start_time
WHERE module_name = _module_name;
RAISE NOTICE 'Finished % module. Duration: %', _module_name, clock_timestamp() - _start_time;
END $$;

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-- Description: Calculates and updates the main product_metrics table based on current data
-- and aggregated daily snapshots. Uses UPSERT for idempotency.
-- Dependencies: Core import tables, daily_product_snapshots, configuration tables, calculate_status.
-- Frequency: Hourly (Run AFTER update_daily_snapshots.sql completes).
DO $$
DECLARE
_module_name VARCHAR := 'product_metrics';
_start_time TIMESTAMPTZ := clock_timestamp();
_last_calc_time TIMESTAMPTZ;
_current_date DATE := CURRENT_DATE;
BEGIN
-- Get the timestamp before the last successful run of this module
SELECT last_calculation_timestamp INTO _last_calc_time
FROM public.calculate_status
WHERE module_name = _module_name;
RAISE NOTICE 'Running % module. Start Time: %', _module_name, _start_time;
-- Use CTEs to gather all necessary information
WITH CurrentInfo AS (
SELECT
p.pid,
p.sku,
p.title,
p.brand,
p.vendor,
COALESCE(p.image_175, p.image) as image_url,
p.visible as is_visible,
p.replenishable as is_replenishable,
COALESCE(p.price, 0.00) as current_price,
COALESCE(p.regular_price, 0.00) as current_regular_price,
COALESCE(p.cost_price, 0.00) as current_cost_price,
COALESCE(p.landing_cost_price, p.cost_price, 0.00) as current_effective_cost, -- Use landing if available, else cost
p.stock_quantity as current_stock,
p.created_at,
p.first_received,
p.date_last_sold,
p.moq,
p.uom -- Assuming UOM logic is handled elsewhere or simple (e.g., 1=each)
FROM public.products p
),
OnOrderInfo AS (
SELECT
pid,
COALESCE(SUM(ordered - received), 0) AS on_order_qty,
COALESCE(SUM((ordered - received) * cost_price), 0.00) AS on_order_cost,
MIN(expected_date) AS earliest_expected_date
FROM public.purchase_orders
WHERE status IN ('open', 'partially_received', 'ordered', 'preordered', 'receiving_started', 'electronically_sent', 'electronically_ready_send') -- Adjust based on your status workflow representing active POs not fully received
AND (ordered - received) > 0
GROUP BY pid
),
HistoricalDates AS (
-- Note: Calculating these MIN/MAX values hourly can be slow on large tables.
-- Consider calculating periodically or storing on products if import can populate them.
SELECT
p.pid,
MIN(o.date)::date AS date_first_sold,
MAX(o.date)::date AS max_order_date, -- Use MAX for potential recalc of date_last_sold
MIN(rh.first_receipt_date) AS date_first_received_calc,
MAX(rh.last_receipt_date) AS date_last_received_calc
FROM public.products p
LEFT JOIN public.orders o ON p.pid = o.pid AND o.quantity > 0 AND o.status NOT IN ('canceled', 'returned')
LEFT JOIN (
SELECT
po.pid,
MIN((rh.item->>'received_at')::date) as first_receipt_date,
MAX((rh.item->>'received_at')::date) as last_receipt_date
FROM public.purchase_orders po
CROSS JOIN LATERAL jsonb_array_elements(po.receiving_history) AS rh(item)
WHERE jsonb_typeof(po.receiving_history) = 'array' AND jsonb_array_length(po.receiving_history) > 0
GROUP BY po.pid
) rh ON p.pid = rh.pid
GROUP BY p.pid
),
SnapshotAggregates AS (
SELECT
pid,
-- Rolling periods (ensure dates are inclusive/exclusive as needed)
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '6 days' THEN units_sold ELSE 0 END) AS sales_7d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '6 days' THEN net_revenue ELSE 0 END) AS revenue_7d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '13 days' THEN units_sold ELSE 0 END) AS sales_14d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '13 days' THEN net_revenue ELSE 0 END) AS revenue_14d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN units_sold ELSE 0 END) AS sales_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN net_revenue ELSE 0 END) AS revenue_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN cogs ELSE 0 END) AS cogs_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN profit ELSE 0 END) AS profit_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN units_returned ELSE 0 END) AS returns_units_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN returns_revenue ELSE 0 END) AS returns_revenue_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN discounts ELSE 0 END) AS discounts_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN gross_revenue ELSE 0 END) AS gross_revenue_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN gross_regular_revenue ELSE 0 END) AS gross_regular_revenue_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' AND stockout_flag THEN 1 ELSE 0 END) AS stockout_days_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '364 days' THEN units_sold ELSE 0 END) AS sales_365d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '364 days' THEN net_revenue ELSE 0 END) AS revenue_365d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN units_received ELSE 0 END) AS received_qty_30d,
SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN cost_received ELSE 0 END) AS received_cost_30d,
-- Averages (check for NULLIF 0 days in period if filtering dates)
AVG(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN eod_stock_quantity END) AS avg_stock_units_30d,
AVG(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN eod_stock_cost END) AS avg_stock_cost_30d,
AVG(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN eod_stock_retail END) AS avg_stock_retail_30d,
AVG(CASE WHEN snapshot_date >= _current_date - INTERVAL '29 days' THEN eod_stock_gross END) AS avg_stock_gross_30d,
-- Lifetime
SUM(units_sold) AS lifetime_sales,
SUM(net_revenue) AS lifetime_revenue,
-- Yesterday
SUM(CASE WHEN snapshot_date = _current_date - INTERVAL '1 day' THEN units_sold ELSE 0 END) as yesterday_sales
FROM public.daily_product_snapshots
WHERE snapshot_date <= _current_date -- Include today's snapshot
AND snapshot_date >= _current_date - INTERVAL '365 days' -- Limit history scan slightly
GROUP BY pid
),
FirstPeriodMetrics AS (
SELECT
pid,
date_first_sold,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '6 days' THEN units_sold ELSE 0 END) AS first_7_days_sales,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '6 days' THEN net_revenue ELSE 0 END) AS first_7_days_revenue,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '29 days' THEN units_sold ELSE 0 END) AS first_30_days_sales,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '29 days' THEN net_revenue ELSE 0 END) AS first_30_days_revenue,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '59 days' THEN units_sold ELSE 0 END) AS first_60_days_sales,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '59 days' THEN net_revenue ELSE 0 END) AS first_60_days_revenue,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '89 days' THEN units_sold ELSE 0 END) AS first_90_days_sales,
SUM(CASE WHEN snapshot_date BETWEEN date_first_sold AND date_first_sold + INTERVAL '89 days' THEN net_revenue ELSE 0 END) AS first_90_days_revenue
FROM public.daily_product_snapshots ds
JOIN HistoricalDates hd USING(pid)
WHERE date_first_sold IS NOT NULL
AND snapshot_date >= date_first_sold
AND snapshot_date <= date_first_sold + INTERVAL '90 days' -- Limit scan range
GROUP BY pid, date_first_sold
),
Settings AS (
SELECT
p.pid,
COALESCE(sp.lead_time_days, sv.default_lead_time_days, (SELECT setting_value FROM settings_global WHERE setting_key = 'default_lead_time_days')::int, 14) AS effective_lead_time,
COALESCE(sp.days_of_stock, sv.default_days_of_stock, (SELECT setting_value FROM settings_global WHERE setting_key = 'default_days_of_stock')::int, 30) AS effective_days_of_stock,
COALESCE(sp.safety_stock, 0) AS effective_safety_stock, -- Assuming safety stock is units, not days from global for now
COALESCE(sp.exclude_from_forecast, FALSE) AS exclude_forecast
FROM public.products p
LEFT JOIN public.settings_product sp ON p.pid = sp.pid
LEFT JOIN public.settings_vendor sv ON p.vendor = sv.vendor
)
-- Final UPSERT into product_metrics
INSERT INTO public.product_metrics (
pid, last_calculated, sku, title, brand, vendor, image_url, is_visible, is_replenishable,
current_price, current_regular_price, current_cost_price, current_landing_cost_price,
current_stock, current_stock_cost, current_stock_retail, current_stock_gross,
on_order_qty, on_order_cost, on_order_retail, earliest_expected_date,
date_created, date_first_received, date_last_received, date_first_sold, date_last_sold, age_days,
sales_7d, revenue_7d, sales_14d, revenue_14d, sales_30d, revenue_30d, cogs_30d, profit_30d,
returns_units_30d, returns_revenue_30d, discounts_30d, gross_revenue_30d, gross_regular_revenue_30d,
stockout_days_30d, sales_365d, revenue_365d,
avg_stock_units_30d, avg_stock_cost_30d, avg_stock_retail_30d, avg_stock_gross_30d,
received_qty_30d, received_cost_30d,
lifetime_sales, lifetime_revenue,
first_7_days_sales, first_7_days_revenue, first_30_days_sales, first_30_days_revenue,
first_60_days_sales, first_60_days_revenue, first_90_days_sales, first_90_days_revenue,
asp_30d, acp_30d, avg_ros_30d, avg_sales_per_day_30d, avg_sales_per_month_30d,
margin_30d, markup_30d, gmroi_30d, stockturn_30d, return_rate_30d, discount_rate_30d,
stockout_rate_30d, markdown_30d, markdown_rate_30d, sell_through_30d,
-- avg_lead_time_days, -- Calculated periodically
-- abc_class, -- Calculated periodically
sales_velocity_daily, config_lead_time, config_days_of_stock, config_safety_stock,
planning_period_days, lead_time_forecast_units, days_of_stock_forecast_units,
planning_period_forecast_units, lead_time_closing_stock, days_of_stock_closing_stock,
replenishment_needed_raw, replenishment_units, replenishment_cost, replenishment_retail, replenishment_profit,
to_order_units, forecast_lost_sales_units, forecast_lost_revenue,
stock_cover_in_days, po_cover_in_days, sells_out_in_days, replenish_date,
overstocked_units, overstocked_cost, overstocked_retail, is_old_stock,
yesterday_sales
)
SELECT
ci.pid, _start_time, ci.sku, ci.title, ci.brand, ci.vendor, ci.image_url, ci.is_visible, ci.is_replenishable,
ci.current_price, ci.current_regular_price, ci.current_cost_price, ci.current_effective_cost,
ci.current_stock, ci.current_stock * ci.current_effective_cost, ci.current_stock * ci.current_price, ci.current_stock * ci.current_regular_price,
COALESCE(ooi.on_order_qty, 0), COALESCE(ooi.on_order_cost, 0.00), COALESCE(ooi.on_order_qty, 0) * ci.current_price, ooi.earliest_expected_date,
ci.created_at::date, COALESCE(ci.first_received::date, hd.date_first_received_calc), hd.date_last_received_calc, hd.date_first_sold, COALESCE(ci.date_last_sold, hd.max_order_date), DATE_PART('day', _current_date - LEAST(ci.created_at::date, hd.date_first_sold)),
sa.sales_7d, sa.revenue_7d, sa.sales_14d, sa.revenue_14d, sa.sales_30d, sa.revenue_30d, sa.cogs_30d, sa.profit_30d,
sa.returns_units_30d, sa.returns_revenue_30d, sa.discounts_30d, sa.gross_revenue_30d, sa.gross_regular_revenue_30d,
sa.stockout_days_30d, sa.sales_365d, sa.revenue_365d,
sa.avg_stock_units_30d, sa.avg_stock_cost_30d, sa.avg_stock_retail_30d, sa.avg_stock_gross_30d,
sa.received_qty_30d, sa.received_cost_30d,
sa.lifetime_sales, sa.lifetime_revenue,
fpm.first_7_days_sales, fpm.first_7_days_revenue, fpm.first_30_days_sales, fpm.first_30_days_revenue,
fpm.first_60_days_sales, fpm.first_60_days_revenue, fpm.first_90_days_sales, fpm.first_90_days_revenue,
-- Calculated KPIs
sa.revenue_30d / NULLIF(sa.sales_30d, 0) AS asp_30d,
sa.cogs_30d / NULLIF(sa.sales_30d, 0) AS acp_30d,
sa.profit_30d / NULLIF(sa.sales_30d, 0) AS avg_ros_30d,
sa.sales_30d / 30.0 AS avg_sales_per_day_30d,
sa.sales_30d AS avg_sales_per_month_30d, -- Using 30d sales as proxy for month
(sa.profit_30d / NULLIF(sa.revenue_30d, 0)) * 100 AS margin_30d,
(sa.profit_30d / NULLIF(sa.cogs_30d, 0)) * 100 AS markup_30d,
sa.profit_30d / NULLIF(sa.avg_stock_cost_30d, 0) AS gmroi_30d,
sa.sales_30d / NULLIF(sa.avg_stock_units_30d, 0) AS stockturn_30d,
(sa.returns_units_30d / NULLIF(sa.sales_30d + sa.returns_units_30d, 0)) * 100 AS return_rate_30d,
(sa.discounts_30d / NULLIF(sa.gross_revenue_30d, 0)) * 100 AS discount_rate_30d,
(sa.stockout_days_30d / 30.0) * 100 AS stockout_rate_30d,
sa.gross_regular_revenue_30d - sa.gross_revenue_30d AS markdown_30d,
((sa.gross_regular_revenue_30d - sa.gross_revenue_30d) / NULLIF(sa.gross_regular_revenue_30d, 0)) * 100 AS markdown_rate_30d,
(sa.sales_30d / NULLIF(ci.current_stock + sa.sales_30d, 0)) * 100 AS sell_through_30d,
-- Forecasting intermediate values
(sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) AS sales_velocity_daily,
s.effective_lead_time AS config_lead_time,
s.effective_days_of_stock AS config_days_of_stock,
s.effective_safety_stock AS config_safety_stock,
(s.effective_lead_time + s.effective_days_of_stock) AS planning_period_days,
(sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time AS lead_time_forecast_units,
(sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock AS days_of_stock_forecast_units,
((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock) AS planning_period_forecast_units,
(ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time)) AS lead_time_closing_stock,
((ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time))) - ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock) AS days_of_stock_closing_stock,
(((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0) AS replenishment_needed_raw,
-- Final Forecasting / Replenishment Metrics (apply CEILING/GREATEST/etc.)
-- Note: These calculations are nested for clarity, can be simplified in prod
CEILING(GREATEST(0, ((((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS replenishment_units,
(CEILING(GREATEST(0, ((((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_effective_cost AS replenishment_cost,
(CEILING(GREATEST(0, ((((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_price AS replenishment_retail,
(CEILING(GREATEST(0, ((((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * (ci.current_price - ci.current_effective_cost) AS replenishment_profit,
-- Placeholder for To Order (Apply MOQ/UOM logic here if needed, otherwise equals replenishment)
CEILING(GREATEST(0, ((((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS to_order_units,
GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time))) AS forecast_lost_sales_units,
GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time))) * ci.current_price AS forecast_lost_revenue,
ci.current_stock / NULLIF((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)), 0) AS stock_cover_in_days,
COALESCE(ooi.on_order_qty, 0) / NULLIF((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)), 0) AS po_cover_in_days,
(ci.current_stock + COALESCE(ooi.on_order_qty, 0)) / NULLIF((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)), 0) AS sells_out_in_days,
-- Replenish Date: Date when stock is projected to hit safety stock, minus lead time
CASE
WHEN (sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) > 0
THEN _current_date + FLOOR(GREATEST(0, ci.current_stock - s.effective_safety_stock) / (sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)))::int - s.effective_lead_time
ELSE NULL
END AS replenish_date,
GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)))::int AS overstocked_units,
(GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)))) * ci.current_effective_cost AS overstocked_cost,
(GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_lead_time) + ((sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) * s.effective_days_of_stock)))) * ci.current_price AS overstocked_retail,
-- Old Stock Flag
(ci.created_at::date < _current_date - INTERVAL '60 day') AND
(COALESCE(ci.date_last_sold, hd.max_order_date) IS NULL OR COALESCE(ci.date_last_sold, hd.max_order_date) < _current_date - INTERVAL '60 day') AND
(hd.date_last_received_calc IS NULL OR hd.date_last_received_calc < _current_date - INTERVAL '60 day') AND
COALESCE(ooi.on_order_qty, 0) = 0
AS is_old_stock,
sa.yesterday_sales
FROM CurrentInfo ci
LEFT JOIN OnOrderInfo ooi ON ci.pid = ooi.pid
LEFT JOIN HistoricalDates hd ON ci.pid = hd.pid
LEFT JOIN SnapshotAggregates sa ON ci.pid = sa.pid
LEFT JOIN FirstPeriodMetrics fpm ON ci.pid = fpm.pid
LEFT JOIN Settings s ON ci.pid = s.pid
WHERE s.exclude_forecast IS FALSE OR s.exclude_forecast IS NULL -- Exclude products explicitly marked
ON CONFLICT (pid) DO UPDATE SET
last_calculated = EXCLUDED.last_calculated,
sku = EXCLUDED.sku, title = EXCLUDED.title, brand = EXCLUDED.brand, vendor = EXCLUDED.vendor, image_url = EXCLUDED.image_url, is_visible = EXCLUDED.is_visible, is_replenishable = EXCLUDED.is_replenishable,
current_price = EXCLUDED.current_price, current_regular_price = EXCLUDED.current_regular_price, current_cost_price = EXCLUDED.current_cost_price, current_landing_cost_price = EXCLUDED.current_landing_cost_price,
current_stock = EXCLUDED.current_stock, current_stock_cost = EXCLUDED.current_stock_cost, current_stock_retail = EXCLUDED.current_stock_retail, current_stock_gross = EXCLUDED.current_stock_gross,
on_order_qty = EXCLUDED.on_order_qty, on_order_cost = EXCLUDED.on_order_cost, on_order_retail = EXCLUDED.on_order_retail, earliest_expected_date = EXCLUDED.earliest_expected_date,
date_created = EXCLUDED.date_created, date_first_received = EXCLUDED.date_first_received, date_last_received = EXCLUDED.date_last_received, date_first_sold = EXCLUDED.date_first_sold, date_last_sold = EXCLUDED.date_last_sold, age_days = EXCLUDED.age_days,
sales_7d = EXCLUDED.sales_7d, revenue_7d = EXCLUDED.revenue_7d, sales_14d = EXCLUDED.sales_14d, revenue_14d = EXCLUDED.revenue_14d, sales_30d = EXCLUDED.sales_30d, revenue_30d = EXCLUDED.revenue_30d, cogs_30d = EXCLUDED.cogs_30d, profit_30d = EXCLUDED.profit_30d,
returns_units_30d = EXCLUDED.returns_units_30d, returns_revenue_30d = EXCLUDED.returns_revenue_30d, discounts_30d = EXCLUDED.discounts_30d, gross_revenue_30d = EXCLUDED.gross_revenue_30d, gross_regular_revenue_30d = EXCLUDED.gross_regular_revenue_30d,
stockout_days_30d = EXCLUDED.stockout_days_30d, sales_365d = EXCLUDED.sales_365d, revenue_365d = EXCLUDED.revenue_365d,
avg_stock_units_30d = EXCLUDED.avg_stock_units_30d, avg_stock_cost_30d = EXCLUDED.avg_stock_cost_30d, avg_stock_retail_30d = EXCLUDED.avg_stock_retail_30d, avg_stock_gross_30d = EXCLUDED.avg_stock_gross_30d,
received_qty_30d = EXCLUDED.received_qty_30d, received_cost_30d = EXCLUDED.received_cost_30d,
lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue,
first_7_days_sales = EXCLUDED.first_7_days_sales, first_7_days_revenue = EXCLUDED.first_7_days_revenue, first_30_days_sales = EXCLUDED.first_30_days_sales, first_30_days_revenue = EXCLUDED.first_30_days_revenue,
first_60_days_sales = EXCLUDED.first_60_days_sales, first_60_days_revenue = EXCLUDED.first_60_days_revenue, first_90_days_sales = EXCLUDED.first_90_days_sales, first_90_days_revenue = EXCLUDED.first_90_days_revenue,
asp_30d = EXCLUDED.asp_30d, acp_30d = EXCLUDED.acp_30d, avg_ros_30d = EXCLUDED.avg_ros_30d, avg_sales_per_day_30d = EXCLUDED.avg_sales_per_day_30d, avg_sales_per_month_30d = EXCLUDED.avg_sales_per_month_30d,
margin_30d = EXCLUDED.margin_30d, markup_30d = EXCLUDED.markup_30d, gmroi_30d = EXCLUDED.gmroi_30d, stockturn_30d = EXCLUDED.stockturn_30d, return_rate_30d = EXCLUDED.return_rate_30d, discount_rate_30d = EXCLUDED.discount_rate_30d,
stockout_rate_30d = EXCLUDED.stockout_rate_30d, markdown_30d = EXCLUDED.markdown_30d, markdown_rate_30d = EXCLUDED.markdown_rate_30d, sell_through_30d = EXCLUDED.sell_through_30d,
-- avg_lead_time_days = EXCLUDED.avg_lead_time_days, -- Updated Periodically
-- abc_class = EXCLUDED.abc_class, -- Updated Periodically
sales_velocity_daily = EXCLUDED.sales_velocity_daily, config_lead_time = EXCLUDED.config_lead_time, config_days_of_stock = EXCLUDED.config_days_of_stock, config_safety_stock = EXCLUDED.config_safety_stock,
planning_period_days = EXCLUDED.planning_period_days, lead_time_forecast_units = EXCLUDED.lead_time_forecast_units, days_of_stock_forecast_units = EXCLUDED.days_of_stock_forecast_units,
planning_period_forecast_units = EXCLUDED.planning_period_forecast_units, lead_time_closing_stock = EXCLUDED.lead_time_closing_stock, days_of_stock_closing_stock = EXCLUDED.days_of_stock_closing_stock,
replenishment_needed_raw = EXCLUDED.replenishment_needed_raw, replenishment_units = EXCLUDED.replenishment_units, replenishment_cost = EXCLUDED.replenishment_cost, replenishment_retail = EXcluded.replenishment_retail, replenishment_profit = EXCLUDED.replenishment_profit,
to_order_units = EXCLUDED.to_order_units, forecast_lost_sales_units = EXCLUDED.forecast_lost_sales_units, forecast_lost_revenue = EXCLUDED.forecast_lost_revenue,
stock_cover_in_days = EXCLUDED.stock_cover_in_days, po_cover_in_days = EXCLUDED.po_cover_in_days, sells_out_in_days = EXCLUDED.sells_out_in_days, replenish_date = EXCLUDED.replenish_date,
overstocked_units = EXCLUDED.overstocked_units, overstocked_cost = EXCLUDED.overstocked_cost, overstocked_retail = EXCLUDED.overstocked_retail, is_old_stock = EXCLUDED.is_old_stock,
yesterday_sales = EXCLUDED.yesterday_sales
;
-- Update the status table with the timestamp from the START of this run
UPDATE public.calculate_status
SET last_calculation_timestamp = _start_time
WHERE module_name = _module_name;
RAISE NOTICE 'Finished % module. Duration: %', _module_name, clock_timestamp() - _start_time;
END $$;