Project: Centralize 1,600 Excel Recipe Sheets into a Smart, Open PostgreSQL System with Auto-Updating Costs, Packaging, Nutrition, Allergens, Process Data, Brand & Multi-Pricelist Generation (with REST API and 1C ERP integration)
Budget: €250 – €750 EUR
We currently have around 1,600 individual Excel workbooks, each representing a complete recipe.
We need a developer to build a system that consolidates them into a single, query-friendly PostgreSQL database, dynamically linked to ingredient price files and capable of automatic recalculations for cost, packaging, nutrition, allergens, process data, and production departments.
The system must be open-source, modifiable, and integrable with our ERP system (1C) through REST APIs.
1. Recipe Core Data
Each recipe must include the following fields and attributes:
Recipe code (assigned manually by us)
Product name
Brand under which the product will be manufactured (e.g., Disano, Meucci, Romeo, Private Label, etc.)
Ingredient list and quantities (entered manually or imported from Excel)
Allergens management:
Ingredients containing allergens must be displayed in bold (e.g., “pasta di PISTACCHIO 50%”).
The recipe datasheet must include a dedicated “Allergens” section, indicating both “Contains” and “May contain” allergens.
The system must use a master table of the 14 EU allergens, with mapping between each ingredient and its allergens.
Usage instructions / directions for use
Production process description, including:
Machines or equipment used
Step-by-step process and production time
Batch size or yield (%)
Production department where the recipe must be produced (e.g., “Spreads”, “Nut Pastes”, “Fillings”, “Variegates”)
2. Costing and Pricing
Automatic cost calculation based on ingredient and packaging prices.
Additional cost inputs: labor, processing, logistics, overheads, energy, etc.
Packaging cost integration based on packaging type (jar, pouch, squeeze bottle, etc.).
Auto-update mechanism: when ingredient or packaging prices change, all related recipes are automatically recalculated.
Target margin management: define a desired profit margin and automatically compute the final selling price.
Unified export: generate a single consolidated Excel/CSV file showing product name, department, total cost, brand, and selling price.
Multi-pricelist generator: create different price lists (for markets, customers, or countries) with variable margins, rounding rules, and tax/VAT handling.
ERP Integration: the system must provide REST API endpoints compatible with our 1C ERP, allowing synchronization of prices, products, brands, and departments.
3. Nutrition and Scaling
Automatic nutritional calculation based on ingredient nutritional data (per 100 g).
Nutritional fields to include:
Carbohydrates (g), Sugars (g), Dietary Fiber (g), Fats (g), Saturated Fats (g), Trans Fats (g), Proteins (g), Fiber (g), Cholesterol (mg), Other Solids (g), Moisture (g), Salt (g), Total Solids (g), Alcohol (g), Sodium (mg), Potassium (mg), Calcium (mg), Magnesium (mg), Copper (mg), Iron (mg), Manganese (mg), Vitamin A (µg), Vitamin B2 (mg), Vitamin C (mg), Vitamin D (µg), Vitamin B6 (mg), Folic Acid (µg), Energy (kcal, kJ), PAC, POD, SLNG (g).
Proportional scaling engine:
User inputs a target output quantity (e.g., 800 kg).
The system proportionally recalculates all ingredient quantities to reach that production volume.
Supports unit conversions, rounding rules, and process yield/loss%.
Optional packaging-aware rounding (adjust batch to full packaging units).
Automatically updates cost, nutrition, and pricing values for the scaled batch.
REST API endpoint:
POST /recipes/{id}/scale { target_output_kg, yield_percent, rounding_rules }.
4. Process & Production Data
Each recipe must store detailed production information:
Production department (e.g., Spreads, Pastes, Variegates, etc.)
Machines or equipment used
Expected production time (minutes/hours)
Yield and losses (%)
Optional capacity check (warning if scaled batch exceeds machine capacity)
Brand (internal or private label) for traceability in production
5. Allergens Management
Dedicated Allergens Master Table with EU-standard allergens.
Ingredient–allergen mapping (many-to-many).
Automatic bolding of allergenic ingredients in label rendering and exports.
Recipe datasheet section “Allergens” showing both “Contains” and “May contain”.
REST API endpoints for reading/updating allergens, and retrieving full label text with bold formatting.
Exports must include:
allergens_contained
allergens_may_contain
ingredient_list_bolded (HTML/Markdown ready for labeling).
6. System Openness and Connectivity
Full open-source code, documented and editable by our internal developer.
REST API architecture for:
Recipe CRUD operations
Cost and price recalculation
Scaled batch generation
Pricelist and label export
Integration with 1C ERP
JSON format for data exchange, documented via Swagger/Postman.
Secure token-based authentication (e.g., JWT).
7. Technical Requirements
Database: PostgreSQL (mandatory)
Backend: Python (FastAPI or Django, using pandas and SQLAlchemy)
Import/update logic: Fully automated, seamless, and repeatable
Interface: Web-based UI or simple CLI to:
Import Excel data
Edit recipes, ingredients, processes, departments, brands
Trigger recalculations
Manage allergens
Scale recipes (e.g., 800 kg batch)
Export cost sheets and price lists
Architecture: Modular, scalable, and API-ready for future ERP/analytics integrations
Documentation:
Clean and commented code
REST API documentation (Swagger)
Setup and usage manual (local or server installation)
8. Deliverables
PostgreSQL database schema with all related tables (recipes, ingredients, prices, packaging, nutrition, allergens, processes, departments, brands).
Excel-to-PostgreSQL importer for recipes and ingredient price files.
Automatic recalculation engine for costs, packaging, and nutrition.
Proportional scaling module for target batch size.
Nutrition calculation engine with all fields listed above.
Allergen management module (master table, mapping, bold rendering, export, API).
Brand assignment system for each recipe.
Multi-pricelist generator (configurable margins, rounding, taxes).
Unified export generator (Excel/CSV/PDF).
REST API endpoints for 1C ERP integration.
Recipe management UI with editable fields:
Recipe code
Product name
Brand
Ingredient list (with bold allergens)
Directions for use
Process description (equipment + timing)
Production department
Nutrition and cost summary
Open and documented source code, editable by internal developers.
9. Preferred Skills
Python (pandas, SQLAlchemy, FastAPI/Django)
PostgreSQL (schema design & optimization)
REST API design and documentation (Swagger/Postman)
Experience with ERP integration (1C preferred)
Web UI design for data-driven applications
Background in food or manufacturing software (plus)
10. Summary
We are an Italian food manufacturing group using 1C ERP, seeking a scalable and automated recipe management system to centralize costing, nutrition, production, and labeling data.
The system must ensure accuracy, automation, modularity, and seamless ERP connectivity, while being open and maintainable internally.
Key goals: real-time cost control, automatic recipe updates, multi-brand support, allergen compliance, and efficient integration with our existing ERP 1C environment.
Progetto:
Sistema gestionale ricette centralizzato (PostgreSQL + Python), collegato all’ERP 1C, con funzioni di:
importazione 1.600 ricette Excel
calcolo automatico costi, margini, packaging e nutrizione
proporzionamento automatico per quantità (es. 800 kg)
gestione reparti, processi, macchinari e tempi
evidenziazione allergeni in grassetto e sezione “Contiene / Può contenere”
marchio associato alla ricetta (Disano, Meucci, Romeo, Private Label…)
generazione listini multipli e export Excel/CSV
API REST per sincronizzazione con 1C ERP
codice sorgente aperto e modificabile internamente
Tecnologie:
PostgreSQL, Python (FastAPI/Django, pandas, SQLAlchemy), REST API (Swagger), UI web modulare.
Obiettivo: piattaforma unica per la gestione industriale e commerciale delle ricette, pronta per integrazione ERP e automazione dei costi.
We need a developer to build a system that consolidates them into a single, query-friendly PostgreSQL database, dynamically linked to ingredient price files and capable of automatic recalculations for cost, packaging, nutrition, allergens, process data, and production departments.
The system must be open-source, modifiable, and integrable with our ERP system (1C) through REST APIs.
1. Recipe Core Data
Each recipe must include the following fields and attributes:
Recipe code (assigned manually by us)
Product name
Brand under which the product will be manufactured (e.g., Disano, Meucci, Romeo, Private Label, etc.)
Ingredient list and quantities (entered manually or imported from Excel)
Allergens management:
Ingredients containing allergens must be displayed in bold (e.g., “pasta di PISTACCHIO 50%”).
The recipe datasheet must include a dedicated “Allergens” section, indicating both “Contains” and “May contain” allergens.
The system must use a master table of the 14 EU allergens, with mapping between each ingredient and its allergens.
Usage instructions / directions for use
Production process description, including:
Machines or equipment used
Step-by-step process and production time
Batch size or yield (%)
Production department where the recipe must be produced (e.g., “Spreads”, “Nut Pastes”, “Fillings”, “Variegates”)
2. Costing and Pricing
Automatic cost calculation based on ingredient and packaging prices.
Additional cost inputs: labor, processing, logistics, overheads, energy, etc.
Packaging cost integration based on packaging type (jar, pouch, squeeze bottle, etc.).
Auto-update mechanism: when ingredient or packaging prices change, all related recipes are automatically recalculated.
Target margin management: define a desired profit margin and automatically compute the final selling price.
Unified export: generate a single consolidated Excel/CSV file showing product name, department, total cost, brand, and selling price.
Multi-pricelist generator: create different price lists (for markets, customers, or countries) with variable margins, rounding rules, and tax/VAT handling.
ERP Integration: the system must provide REST API endpoints compatible with our 1C ERP, allowing synchronization of prices, products, brands, and departments.
3. Nutrition and Scaling
Automatic nutritional calculation based on ingredient nutritional data (per 100 g).
Nutritional fields to include:
Carbohydrates (g), Sugars (g), Dietary Fiber (g), Fats (g), Saturated Fats (g), Trans Fats (g), Proteins (g), Fiber (g), Cholesterol (mg), Other Solids (g), Moisture (g), Salt (g), Total Solids (g), Alcohol (g), Sodium (mg), Potassium (mg), Calcium (mg), Magnesium (mg), Copper (mg), Iron (mg), Manganese (mg), Vitamin A (µg), Vitamin B2 (mg), Vitamin C (mg), Vitamin D (µg), Vitamin B6 (mg), Folic Acid (µg), Energy (kcal, kJ), PAC, POD, SLNG (g).
Proportional scaling engine:
User inputs a target output quantity (e.g., 800 kg).
The system proportionally recalculates all ingredient quantities to reach that production volume.
Supports unit conversions, rounding rules, and process yield/loss%.
Optional packaging-aware rounding (adjust batch to full packaging units).
Automatically updates cost, nutrition, and pricing values for the scaled batch.
REST API endpoint:
POST /recipes/{id}/scale { target_output_kg, yield_percent, rounding_rules }.
4. Process & Production Data
Each recipe must store detailed production information:
Production department (e.g., Spreads, Pastes, Variegates, etc.)
Machines or equipment used
Expected production time (minutes/hours)
Yield and losses (%)
Optional capacity check (warning if scaled batch exceeds machine capacity)
Brand (internal or private label) for traceability in production
5. Allergens Management
Dedicated Allergens Master Table with EU-standard allergens.
Ingredient–allergen mapping (many-to-many).
Automatic bolding of allergenic ingredients in label rendering and exports.
Recipe datasheet section “Allergens” showing both “Contains” and “May contain”.
REST API endpoints for reading/updating allergens, and retrieving full label text with bold formatting.
Exports must include:
allergens_contained
allergens_may_contain
ingredient_list_bolded (HTML/Markdown ready for labeling).
6. System Openness and Connectivity
Full open-source code, documented and editable by our internal developer.
REST API architecture for:
Recipe CRUD operations
Cost and price recalculation
Scaled batch generation
Pricelist and label export
Integration with 1C ERP
JSON format for data exchange, documented via Swagger/Postman.
Secure token-based authentication (e.g., JWT).
7. Technical Requirements
Database: PostgreSQL (mandatory)
Backend: Python (FastAPI or Django, using pandas and SQLAlchemy)
Import/update logic: Fully automated, seamless, and repeatable
Interface: Web-based UI or simple CLI to:
Import Excel data
Edit recipes, ingredients, processes, departments, brands
Trigger recalculations
Manage allergens
Scale recipes (e.g., 800 kg batch)
Export cost sheets and price lists
Architecture: Modular, scalable, and API-ready for future ERP/analytics integrations
Documentation:
Clean and commented code
REST API documentation (Swagger)
Setup and usage manual (local or server installation)
8. Deliverables
PostgreSQL database schema with all related tables (recipes, ingredients, prices, packaging, nutrition, allergens, processes, departments, brands).
Excel-to-PostgreSQL importer for recipes and ingredient price files.
Automatic recalculation engine for costs, packaging, and nutrition.
Proportional scaling module for target batch size.
Nutrition calculation engine with all fields listed above.
Allergen management module (master table, mapping, bold rendering, export, API).
Brand assignment system for each recipe.
Multi-pricelist generator (configurable margins, rounding, taxes).
Unified export generator (Excel/CSV/PDF).
REST API endpoints for 1C ERP integration.
Recipe management UI with editable fields:
Recipe code
Product name
Brand
Ingredient list (with bold allergens)
Directions for use
Process description (equipment + timing)
Production department
Nutrition and cost summary
Open and documented source code, editable by internal developers.
9. Preferred Skills
Python (pandas, SQLAlchemy, FastAPI/Django)
PostgreSQL (schema design & optimization)
REST API design and documentation (Swagger/Postman)
Experience with ERP integration (1C preferred)
Web UI design for data-driven applications
Background in food or manufacturing software (plus)
10. Summary
We are an Italian food manufacturing group using 1C ERP, seeking a scalable and automated recipe management system to centralize costing, nutrition, production, and labeling data.
The system must ensure accuracy, automation, modularity, and seamless ERP connectivity, while being open and maintainable internally.
Key goals: real-time cost control, automatic recipe updates, multi-brand support, allergen compliance, and efficient integration with our existing ERP 1C environment.
Progetto:
Sistema gestionale ricette centralizzato (PostgreSQL + Python), collegato all’ERP 1C, con funzioni di:
importazione 1.600 ricette Excel
calcolo automatico costi, margini, packaging e nutrizione
proporzionamento automatico per quantità (es. 800 kg)
gestione reparti, processi, macchinari e tempi
evidenziazione allergeni in grassetto e sezione “Contiene / Può contenere”
marchio associato alla ricetta (Disano, Meucci, Romeo, Private Label…)
generazione listini multipli e export Excel/CSV
API REST per sincronizzazione con 1C ERP
codice sorgente aperto e modificabile internamente
Tecnologie:
PostgreSQL, Python (FastAPI/Django, pandas, SQLAlchemy), REST API (Swagger), UI web modulare.
Obiettivo: piattaforma unica per la gestione industriale e commerciale delle ricette, pronta per integrazione ERP e automazione dei costi.