A block-based time-domain system simulation framework in Python

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PathSim lets you model and simulate complex dynamical systems using an intuitive block diagram approach. Connect sources, integrators, functions, and scopes to build continuous-time, discrete-time, or hybrid systems.

Minimal dependencies: just numpy, scipy, and matplotlib.

• Hot-swappable — modify blocks and solvers during simulation
• Stiff solvers — implicit methods (BDF, ESDIRK) for challenging systems
• Event handling — zero-crossing detection for hybrid systems
• Hierarchical — nest subsystems for modular designs
• Extensible — subclass Block to create custom components

pip install pathsim

or with conda:

conda install conda-forge::pathsim

from pathsim import Simulation, Connection
from pathsim.blocks import Integrator, Amplifier, Adder, Scope

# Damped harmonic oscillator: x'' + 0.5x' + 2x = 0
int_v = Integrator(5)       # velocity, v0=5
int_x = Integrator(2)       # position, x0=2
amp_c = Amplifier(-0.5)     # damping
amp_k = Amplifier(-2)       # spring
add = Adder()
scp = Scope()

sim = Simulation(
    blocks=[int_v, int_x, amp_c, amp_k, add, scp],
    connections=[
        Connection(int_v, int_x, amp_c),
        Connection(int_x, amp_k, scp),
        Connection(amp_c, add),
        Connection(amp_k, add[1]),
        Connection(add, int_v),
    ],
    dt=0.05
)

sim.run(30)
scp.plot()

PathView is the graphical editor for PathSim — design systems visually and export to Python.

• Documentation — tutorials, examples, and API reference
• Homepage — overview and getting started
• Contributing — how to contribute
• Consulting & commercial support — integration, custom blocks, migration from closed tools

If you use PathSim in research, please cite:

@article{Rother2025,
  author = {Rother, Milan},
  title = {PathSim - A System Simulation Framework},
  journal = {Journal of Open Source Software},
  year = {2025},
  volume = {10},
  number = {109},
  pages = {8158},
  doi = {10.21105/joss.08158}
}

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