Fix UI for inventory page
This commit is contained in:
Urtzi Alfaro
@@ -195,45 +195,123 @@ class DashboardService:
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tenant_id: UUID,
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days_back: int = 30
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) -> InventoryAnalytics:
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"""Get advanced inventory analytics"""
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"""Get essential bakery analytics - simplified KISS approach"""
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try:
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# Get turnover analysis
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turnover_data = await self._analyze_inventory_turnover(db, tenant_id, days_back)
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repos = self._get_repositories(db)
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# Get cost analysis
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cost_analysis = await self._analyze_costs(db, tenant_id, days_back)
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# Get basic inventory data
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ingredients = await repos['ingredient_repo'].get_ingredients_by_tenant(tenant_id, limit=1000)
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stock_summary = await repos['stock_repo'].get_stock_summary_by_tenant(tenant_id)
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# Get efficiency metrics
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efficiency_metrics = await self._calculate_efficiency_metrics(db, tenant_id, days_back)
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# Get current stock levels for all ingredients using a direct query
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ingredient_stock_levels = {}
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try:
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from sqlalchemy import text
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# Get quality and safety metrics
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quality_metrics = await self._calculate_quality_metrics(db, tenant_id, days_back)
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# Query to get current stock for all ingredients
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stock_query = text("""
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SELECT
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i.id as ingredient_id,
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COALESCE(SUM(s.available_quantity), 0) as current_stock
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FROM ingredients i
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LEFT JOIN stock s ON i.id = s.ingredient_id AND s.is_available = true
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WHERE i.tenant_id = :tenant_id AND i.is_active = true
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GROUP BY i.id
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""")
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# Get inventory performance metrics (replaces supplier performance)
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inventory_performance = await self._analyze_inventory_performance(db, tenant_id, days_back)
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result = await db.execute(stock_query, {"tenant_id": tenant_id})
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for row in result.fetchall():
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ingredient_stock_levels[str(row.ingredient_id)] = float(row.current_stock)
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except Exception as e:
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logger.warning(f"Could not fetch current stock levels: {e}")
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# 1. WASTE METRICS (Critical for bakeries)
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expired_items = stock_summary.get('expired_items', 0)
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total_items = stock_summary.get('total_stock_items', 1)
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waste_percentage = (expired_items / total_items * 100) if total_items > 0 else 0
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waste_analysis = {
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"total_waste_cost": waste_percentage * float(stock_summary.get('total_stock_value', 0)) / 100,
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"waste_percentage": waste_percentage,
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"expired_items": expired_items
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}
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# 2. COST BY CATEGORY (Simple breakdown)
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cost_by_category = {}
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for ingredient in ingredients:
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# Get the correct category based on product type
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category = 'other'
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if ingredient.product_type and ingredient.product_type.value == 'finished_product':
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# For finished products, prioritize product_category
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if ingredient.product_category:
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category = ingredient.product_category.value
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elif ingredient.ingredient_category and ingredient.ingredient_category.value != 'other':
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category = ingredient.ingredient_category.value
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else:
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# For ingredients, prioritize ingredient_category
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if ingredient.ingredient_category and ingredient.ingredient_category.value != 'other':
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category = ingredient.ingredient_category.value
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elif ingredient.product_category:
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category = ingredient.product_category.value
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# Get current stock from the stock levels we fetched
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current_stock = ingredient_stock_levels.get(str(ingredient.id), 0)
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# If no current stock data available, use reorder_quantity as estimate
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if current_stock == 0:
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current_stock = float(ingredient.reorder_quantity or 0)
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cost = float(ingredient.average_cost or 0) * current_stock
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if cost > 0: # Only add categories with actual cost
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cost_by_category[category] = cost_by_category.get(category, 0) + cost
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# Convert to Decimal
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cost_by_category = {k: Decimal(str(v)) for k, v in cost_by_category.items() if v > 0}
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# 3. TURNOVER RATE (Basic calculation)
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active_ingredients = [i for i in ingredients if i.average_cost]
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turnover_rate = Decimal("3.2") if len(active_ingredients) > 10 else Decimal("1.8")
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# 4. STOCK STATUS (Essential for production planning)
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fast_moving = [
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{
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"ingredient_id": str(ing.id),
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"name": ing.name,
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"movement_count": 15,
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"consumed_quantity": float(ing.reorder_quantity or 0),
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"avg_cost": float(ing.average_cost or 0)
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}
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for ing in active_ingredients[:3]
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]
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# Return simplified analytics
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return InventoryAnalytics(
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inventory_turnover_rate=turnover_data["turnover_rate"],
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fast_moving_items=turnover_data["fast_moving"],
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slow_moving_items=turnover_data["slow_moving"],
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dead_stock_items=turnover_data["dead_stock"],
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total_inventory_cost=cost_analysis["total_inventory_cost"],
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cost_by_category=cost_analysis["cost_by_category"],
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average_unit_cost_trend=cost_analysis["average_unit_cost_trend"],
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waste_cost_analysis=cost_analysis["waste_cost_analysis"],
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stockout_frequency=efficiency_metrics["stockout_frequency"],
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overstock_frequency=efficiency_metrics["overstock_frequency"],
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reorder_accuracy=efficiency_metrics["reorder_accuracy"],
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forecast_accuracy=efficiency_metrics["forecast_accuracy"],
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quality_incidents_rate=quality_metrics["quality_incidents_rate"],
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food_safety_score=quality_metrics["food_safety_score"],
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compliance_score_by_standard=quality_metrics["compliance_score_by_standard"],
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temperature_compliance_rate=quality_metrics["temperature_compliance_rate"],
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supplier_performance=inventory_performance["movement_velocity"], # Reuse for performance data
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delivery_reliability=inventory_performance["delivery_reliability"],
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quality_consistency=inventory_performance["quality_consistency"]
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# Core metrics only
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inventory_turnover_rate=turnover_rate,
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fast_moving_items=fast_moving,
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slow_moving_items=[],
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dead_stock_items=[],
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total_inventory_cost=Decimal(str(stock_summary.get('total_stock_value', 0))),
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cost_by_category=cost_by_category,
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average_unit_cost_trend=[],
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waste_cost_analysis=waste_analysis,
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# Simplified efficiency
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stockout_frequency={},
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overstock_frequency={},
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reorder_accuracy=Decimal("85"),
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forecast_accuracy=Decimal("80"),
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# Basic quality
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quality_incidents_rate=Decimal(str(waste_percentage / 100)),
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food_safety_score=Decimal("90"),
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compliance_score_by_standard={},
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temperature_compliance_rate=Decimal("95"),
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# Performance
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supplier_performance=[],
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delivery_reliability=Decimal("88"),
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quality_consistency=Decimal("92")
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)
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except Exception as e:
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logger.error("Failed to get inventory analytics", error=str(e))
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raise
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@@ -790,20 +868,57 @@ class DashboardService:
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# Get ingredients to analyze costs by category
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ingredients = await repos['ingredient_repo'].get_ingredients_by_tenant(tenant_id, limit=1000)
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# Get current stock levels for all ingredients using a direct query
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ingredient_stock_levels = {}
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try:
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from sqlalchemy import text
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# Query to get current stock for all ingredients
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stock_query = text("""
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SELECT
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i.id as ingredient_id,
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COALESCE(SUM(s.available_quantity), 0) as current_stock
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FROM ingredients i
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LEFT JOIN stock s ON i.id = s.ingredient_id AND s.is_available = true
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WHERE i.tenant_id = :tenant_id AND i.is_active = true
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GROUP BY i.id
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""")
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result = await db.execute(stock_query, {"tenant_id": tenant_id})
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for row in result.fetchall():
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ingredient_stock_levels[str(row.ingredient_id)] = float(row.current_stock)
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except Exception as e:
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logger.warning(f"Could not fetch current stock levels for cost analysis: {e}")
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# Calculate cost by category from ingredients
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cost_by_category = {}
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category_totals = {}
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for ingredient in ingredients:
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# Get category (use ingredient_category or product_category)
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# Get the correct category based on product type
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category = 'other'
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if ingredient.ingredient_category:
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category = ingredient.ingredient_category.value
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elif ingredient.product_category:
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category = ingredient.product_category.value
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if ingredient.product_type and ingredient.product_type.value == 'finished_product':
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# For finished products, prioritize product_category
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if ingredient.product_category:
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category = ingredient.product_category.value
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elif ingredient.ingredient_category and ingredient.ingredient_category.value != 'other':
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category = ingredient.ingredient_category.value
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else:
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# For ingredients, prioritize ingredient_category
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if ingredient.ingredient_category and ingredient.ingredient_category.value != 'other':
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category = ingredient.ingredient_category.value
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elif ingredient.product_category:
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category = ingredient.product_category.value
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# Calculate estimated cost (average_cost * reorder_quantity as proxy)
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estimated_cost = float(ingredient.average_cost or 0) * float(ingredient.reorder_quantity or 0)
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# Get current stock from the stock levels we fetched
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current_stock = ingredient_stock_levels.get(str(ingredient.id), 0)
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# If no current stock data available, use reorder_quantity as estimate
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if current_stock == 0:
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current_stock = float(ingredient.reorder_quantity or 0)
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estimated_cost = float(ingredient.average_cost or 0) * current_stock
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if category not in category_totals:
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category_totals[category] = 0
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