simpm 2.1.2

SimPM (Simulation for Project Management) is a discrete-event simulation toolkit for modeling project schedules and resources (Python 3+).

SimPM - Simulation Tool in Project Management

SimPM offers a discrete event simulation library for project management in Python.

Documentation

Full documentation is available at simpm.readthedocs.io.

SimPM - Simulation Tool in Project Management

SimPM is a discrete-event simulation library for modelling projects, construction operations, and other resource-constrained workflows in Python.

It is designed to help you answer questions like:

• How long will this project or work package take?
• How much variability is there in the completion time?
• Where are the bottlenecks in crews, equipment, or workspaces?

What is SimPM?

SimPM uses a process-based discrete-event simulation engine: you describe activities, resources, and logic using plain Python, and the environment advances simulation time while handling queues, waiting, and resource constraints.

The focus is project and construction management: activities are tasks or work items, resources are crews, equipment, or workspaces, and you can run scenarios or experiments to explore “what-if” questions.

Typical use cases include:

• Schedule risk analysis and Monte Carlo simulations.
• Evaluating different crew allocations or equipment plans.
• Studying queues and waiting times at critical resources.
• Comparing alternative construction methods or phasing plans.

Key capabilities

SimPM builds a project-oriented layer on top of a general DES core:

• Project-oriented modelling

  • Entities as activities or work items.
  • Resources as crews, equipment, or workspaces with capacities, priorities, and (optionally) preemption.

• Schedule-friendly probability distributions (simpm.dist)

  • Triangular, beta, trapezoidal, normal, exponential, uniform, and empirical distributions.
  • Well suited to three-point estimates and Monte Carlo schedule risk analysis.

• Automatic tabular logging

  • Events, queue lengths, waiting times, resource utilization, and project duration.
  • Logs are stored in pandas-friendly tables, ready for further analysis and plotting.

• Optional dashboards

  • simpm.run(..., dashboard=True|False) for Plotly Dash dashboards (enabled by default).
  • Inspect timelines, queues, and bottlenecks interactively after a run completes.

• Central logging configuration

  • simpm.log_cfg.LogConfig to control console and file logging for single runs or large experiments.

Relationship to SimPy

SimPM is built on the same process-based discrete-event simulation approach popularized by SimPy <https://simpy.readthedocs.io/>_, but it is a self-contained toolkit purpose-built for project and construction management.

SimPM includes many features that SimPy requires extensive custom code to achieve:

• Entities with attributes – track entity-specific data (start time, end time, custom properties).
• Automatic logging and analytics – events, queues, waiting times, and utilization tracked automatically.
• Interactive dashboards – optional Plotly Dash dashboards for inspecting results interactively.
• Integrated distributions – triangular, beta, empirical, and other project-friendly distributions.
• Stochastic simulation – seamless Monte Carlo support without manual instrumentation.

For a detailed comparison, see the getting-started guide and the DES background in the documentation.

You do not need to install or know SimPy to use SimPM: you work directly with simpm.des, simpm.dist, and the higher-level features built in for project management.

Using SimPM

Getting started quickly:

pip install simpm

Dashboard mode

simpm.run is a convenience wrapper around env.run that optionally starts a dashboard after execution. You can continue to call env.run directly for headless runs; switch to simpm.run when you want dashboards without changing your simulation logic. Install the optional dependencies and run your environment with dashboards enabled (the default) to launch an interactive summary once the simulation finishes:

pip install simpm[dash]

import simpm.des as des
import simpm

env = des.Environment()
worker = env.create_entities("worker", 1, log=True)[0]
machine = des.Resource(env, "machine", init=1, capacity=1, log=True)

def job(entity, resource):
    yield entity.get(resource, 1)
    yield entity.do("work", 2)
    yield entity.put(resource, 1)

env.process(job(worker, machine))

simpm.run(env, dashboard=True, host="127.0.0.1", port=8050)

Use dashboard=False to disable the dashboard entirely.

Community

• Github Discussions

Contributing back to SimPM

If you run into an issue, please file a new issue for us to discuss. If possible, follow up with a pull request.

If you would like to add a feature, please reach out via issue. A feature is most likely to be added if you build it!

Authors and Contributors

• Naimeh Sadeghi – Lead developer and maintainer
  Website: https://wp.kntu.ac.ir/sadeghi/ GitHub: https://github.com/NaimaSadeghi
  Email: [e-mail], [e-mail]

• Pedram Elmi – Core contributor
  GitHub: https://github.com/PedramElmi
  Email: [e-mail]