Overview

Stockpyl brings single-node inventory models, multi-echelon optimization, and system simulation into one package. Install it from PyPI with pip install stockpyl; it requires Python v3.7 or later. That requirement makes it a poor fit for environments that cannot meet the version floor.

The project is released under the MIT License. Tutorials and API modules cover optimization, simulation, and supply-chain data structures. Support runs through GitHub Issues, with email as an alternative, a practical route for users comfortable working through a software project rather than relying on a dedicated commercial-support channel.

Key features

Inventory models and optimization

Stockpyl implements economic order quantity, newsvendor, and Wagner-Whitin models, as well as multi-echelon optimization for stochastic-service and guaranteed-service systems. Safety stock optimization is supported. This range is useful when a team needs to work across several inventory formulations in Python, rather than adopt a broader business application.

Dynamic programming and network models

Documented methods include dynamic programming for Wagner-Whitin and finite-horizon stochastic inventory problems, along with algorithms for serial systems and acyclical guaranteed-service systems. These capabilities make the package relevant to structured, model-based analysis; teams seeking an interface for operational workflows should consider a different kind of tool.

Multi-echelon simulation

Stockpyl can simulate multi-echelon inventory systems in addition to optimizing them. Having both in one package suits developers who need to examine system behavior alongside model solutions, though it still calls for a Python-based workflow.

Pricing

Stockpyl is free and open source. The Stockpyl plan costs 0.00 USD per free and includes the MIT-licensed Python package. It is the natural choice for individuals and teams able to install and use a Python library; there is no paid tier or packaged business application described.

Platforms

Stockpyl is categorized for API and Linux use. Distribution through PyPI and installation with pip suit Python environments, while Python v3.7 or later is required.

Who it's for

Stockpyl fits analysts, developers, and research or engineering teams who need inventory optimization or multi-echelon simulation in Python. Its documented coverage also makes it relevant to education and business analysis. It is less suitable for teams that need a ready-to-use application or a commercial support arrangement.

Pros and cons

Pros: The package covers several single-node methods, multi-echelon optimization, and simulation, giving Python users a focused toolkit for varied inventory-modeling work.
Pros: MIT licensing and free distribution make it an accessible option for teams that can work directly with a Python package.
Cons: The Python v3.7-or-later requirement rules out older environments.
Cons: Support is routed through GitHub Issues or email, rather than a stated dedicated commercial-support channel.
Cons: Its package-based workflow is not a substitute for a broader operational inventory application.

Alternatives

For a business-facing inventory platform, Manhattan Active Inventory Replenishment is a paid API and web option without a free plan. GAINS is another paid API and web alternative, with pricing by request.

Flowlity offers a paid API and web product with a free trial; its Lite plan costs 249.00 EUR per month on a monthly subscription with no long-term commitment, supports up to 5,000 SKUs, and excludes ERP integration. Choose it when those stated product and subscription terms suit the workflow. ketteQ is a paid API and web option with proposals based on deployed use cases and environment scope.

o9 Digital Brain is a paid enterprise SaaS option spanning Android, API, iOS, and web, with pricing scoped to each customer. ZebraDesigner is a different kind of alternative: its free Essentials 3 plan provides basic barcode label and tag design and printing, with support for Zebra Link-OS and Link-OS Basic printers.

E2open Planning and Bluemingo Production Planning & Scheduling are further paid alternatives.

Browse the Inventory Optimization Software category to compare more options.

Verdict

Choose Stockpyl if your team wants a free, MIT-licensed Python toolkit for inventory optimization and multi-echelon simulation. Its main advantage is the breadth of documented model methods in a package; look elsewhere if you need a ready-made business application or a workflow outside Python.

	buffers.ai	Stockpyl
Free plan	No	Yes
Free trial	No	No
Paid from	$25/mo	Free
Open source	No	No
Platforms	Web	api, Linux
Paid from	25 /mo	—
Multi-location optimization	Yes	—
Free plan	—	No
Safety stock optimization	—	Yes
Multi-echelon optimization	—	Yes

buffers.ai vs Stockpyl

buffers.ai

Stockpyl