supplychainpy
supplychainpy: A focused, free toolkit for inventory analysis, forecasting, and simulation. Ranked #21 of 25 in Inventory Optimization Software by our editors (6.5/10); pricing: Free plan; best for free open-source inventory analysis.
At a glance
- Editor score6.5 / 10
- PricingFree plan
- Best forFree open-source inventory analysis
- Free planYes
- Paid fromFree
- Replenishment recsYes
- Founded2016
- Facts checked21 Sep 2026
Where it wins
- Free open-source inventory analysis across Windows, macOS, and Linux
- Combines safety stock, reorder levels, EOQ, forecasting, and simulation
- Supports Pandas, Jupyter, browser reports, and Docker deployment
Where it doesn't
- Self-hosted setup requires Python-oriented technical capability
- The project describes itself as early-stage and not production-ready
- It does not provide verified multi-echelon functionality
Our verdict on supplychainpy
supplychainpy is an open-source Python library for inventory analysis, modeling, forecasting, and simulation. It is designed for demand planners, buyers, supply-chain analysts, and BI analysts who want an alternative to spreadsheet-based workflows. The toolkit covers uncertain-demand analysis, safety-stock and reorder-level calculations, economic order quantity, ABC/XYZ classification, exponential-smoothing forecasts, Monte Carlo simulation, and service-level optimization. It runs across Windows, macOS, and Linux, with self-hosted deployment and a browser-based reporting suite.
Its strongest fit is for teams that want analytical depth without a paid license. The feature set reaches from core replenishment calculations to demand forecasting, simulation, and service-level analysis, giving analysts several ways to examine inventory policy. Pandas DataFrame support connects the library to Python data workflows, while Jupyter and Matplotlib support analysis and visualization. OpenPyXL and XLWings provide spreadsheet-oriented options, and Docker supports a containerized deployment path. These integrations make supplychainpy more useful for analytical workflows than for broad operational inventory management.
The trade-off is implementation and project maturity. A self-hosted Python library is better suited to technically capable solo users and small or mid-market teams than to organizations seeking a turnkey application. Community support and documentation are the stated support channels, and the project describes itself as early-stage and not production-ready. PyPI lists version 0.0.5, released November 8, 2017, which is an important consideration for teams evaluating ongoing maintenance. Choose supplychainpy for free, code-centered inventory analysis; choose an alternative when multi-echelon planning, broader operations coverage, or a production-ready commercial platform is required.
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supplychainpy pricing
supplychainpy fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Multi-location optimization | Not verified |
| Safety stock optimization | Yes |
| Service-level targets | Yes |
| Replenishment recs | Yes |
| Multi-echelon optimization | Not verified |
| Scenario planning | Not verified |
| Deployment | Self-hosted |
| Platforms | Windows, macOS, Linux |
| Support | Community, Docs |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Integrations | 6 integrations: Pandas, Jupyter, Matplotlib, OpenPyXL, XLWings, Docker |
| Pricing | Free plan |
| Website | supplychainpy.org |
| Facts checked | 21 Sep 2026 |
supplychainpy integrations
supplychainpy lists 6 integrations on its own site.
- Pandas
- Jupyter
- Matplotlib
- OpenPyXL
- XLWings
- Docker
Alternatives to supplychainpy
- PTC Servigistics Advanced Inventory OptimizationA specialized platform for optimizing service-parts stock across complex supply chains.9.2
- Slimstock Slim4ERP-connected forecasting and replenishment for complex, multi-location inventory networks.8.7
- ToolsGroup SO99+A broad, enterprise-focused optimizer for uncertain demand and multi-location inventory.8.6
See all supplychainpy alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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