Flexible open source alternative for complex simulation projects
SimPy is a process-based framework for discrete event simulations based on Python. It enables the mapping of complex processes and resource flows without relying on a graphical user interface.
Use at SimPlan
We use SimPy in projects where classic simulation tools cannot be used for technical reasons. Examples:
- DigiPrime research project: Integration in the backend of a web application on Linux servers
- IFCO Simulation of the crate cycle: Mapping of very large numbers of containers where performance would be limited in classic tools
- A.T. Kearney / Lufthansa: Simulation of ULD requirements with extensive entities
Special features of SimPy
- Library approach: SimPy is not a finished software product with a user interface, but a programming library in Python.
- No GUI or animation: Models are created and analysed purely programmatically.
- Flexibility through the Python ecosystem: Embedding in existing Python infrastructures, including the use of additional data analysis and machine learning libraries.
- High scalability: Suitable for simulations with very large amounts of data and a high number of business entities (BEs).
Advantages at a glance
- Easy integration into existing Python environments
- High performance with large and complex models
- Extensibility through the broad Python library landscape
- Free use through open source licence (MIT Licence)
When is SimPy suitable?
SimPy is the right choice if:
- Classic simulation software cannot be used (e.g. due to server or system environments)
- Models need to be integrated into an existing Python environment
- Very large amounts of data or many entities need to be simulated with high performance.