Stockpyl

Stockpyl is best suited to analysts, researchers, and developers who are comfortable working in Python. Its appeal is the combination of established inventory models and multi-echelon optimization; it is less suited to teams looking for a ready-to-use business application.

Overview

Stockpyl brings single-node inventory models, network algorithms, and simulation into a package that can be installed from PyPI with pip install stockpyl. It requires Python v3.7 or later and is released under the MIT License, making it a practical option for open-source Python projects and technical coursework.

Tutorials and API modules cover optimization, simulation, and supply-chain data structures. The project directs feedback and problem reports to GitHub Issues, with email as an alternative. That support route fits users comfortable working with a software project, rather than organizations expecting a dedicated service channel.

Key features

Inventory models and optimization

Stockpyl implements economic order quantity, newsvendor, and Wagner-Whitin models, and supports safety stock optimization. It also includes stochastic-service and guaranteed-service methods for multi-echelon inventory. This range is useful for comparing different formulations within one Python workflow, especially when the analysis spans basic replenishment decisions and more complex inventory networks.

Dynamic programming and network methods

Documented optimization methods include dynamic programming for Wagner-Whitin and finite-horizon stochastic inventory problems. Algorithms for serial systems and acyclical guaranteed-service systems give users methods suited to those network structures. The focus is on model-based analysis; teams seeking a broader operational application should consider a different category of tool.

Simulation

Stockpyl can simulate multi-echelon inventory systems as well as optimize them. Having both capabilities in one package helps users examine system behavior alongside optimization results, though the Python package format favors technical workflows over a turnkey interface.

Pricing

Stockpyl is free: the Stockpyl plan costs free and includes an open-source Python package under the MIT License. There are no paid tiers or stated seat and usage caps. It is a strong fit for individuals and teams that can work directly in Python; organizations that need a packaged business application or a commercial support arrangement may prefer a paid product.

Platforms

Stockpyl is an API-oriented package for Linux. Its Python v3.7-or-later requirement makes it unsuitable for environments that cannot meet that version requirement.

Who it's for

Stockpyl is a good fit for supply-chain analysts, researchers, educators, and developers building or studying inventory models in Python. Its coverage of single-node decisions, multi-echelon optimization, and simulation supports a range of technical work. It is not the right choice for buyers seeking a general inventory application with a nontechnical workflow.

Pros and cons

• Pros: Free and MIT-licensed, with no paid tier to weigh against the core package.
• Pros: Combines single-node models, multi-echelon methods, and simulation, useful for varied model-based inventory work.
• Pros: Tutorials and API modules cover optimization, simulation, and supply-chain data structures.
• Cons: Requires Python v3.7 or later, so older Python environments are not suitable.
• Cons: Its API-oriented, technical format is a poor fit for teams wanting a ready-made business application.
• Cons: Support is routed through GitHub Issues or email, rather than a dedicated commercial support channel.

Alternatives

Inventory Optimization Software is a useful place to compare tools in the broader category. Choose ZebraDesigner instead if the need is basic barcode label and tag design and printing: its free Essentials 3 plan supports Zebra Link-OS and Link-OS Basic printers, and it also offers a free trial and paid pricing. Manhattan Active Inventory Replenishment is a paid alternative with API and web platforms. 4R Systems Intelligent Inventory Optimization is a paid web option with custom pricing and a demo request. Bluemingo Production Planning & Scheduling is another paid web option, with pricing through its sales team. Decion Demand Planning is a paid web product with pricing tailored to capabilities, scope, users, integrations, and implementation requirements. E2open Planning offers a paid connected-planning product with custom pricing. GAINS is a paid API and web platform with pricing by request. Logility DemandAI+ is a paid web product with pricing by request.

Verdict

Choose Stockpyl if you need a free, open-source Python toolkit for inventory optimization and multi-echelon simulation, and your work can live in a technical workflow. Its breadth of models is the main reason to choose it; look elsewhere if your priority is a ready-to-use business application rather than a package for building and analyzing models.