openseespy
OpenSeesPy — Python interpreter for OpenSees
Decision gist · record as of 2026-08-14
Yes, if you need Python-based structural analysis and simulation. The package has low install friction, active maintenance, no known vulnerabilities, and broad platform support. The main caveat is that license terms are unclear—verify LICENSE.md in the repository before use in commercial or restricted-license projects. For academic and open-source structural engineering work, it is a solid choice.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Installation is straightforward with low friction—the package is a meta-package that automatically selects and installs the correct platform-specific binary (openseespylinux, openseespywin, or openseespymac) for your OS.
- The project is actively maintained with recent commits.
License · maintenance · safety
LICENSE.md (unclear) — License treatment is unclear—the package references LICENSE.md but provides no SPDX identifier. Before relying on this package in a commercial or restricted-license context, verify the actual license terms in the repository.
last release 2026-03-18 (149 days) · last repo commit 2026-05-20 · 268 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 625,670 downloads/mo, #5,693 on PyPI
Alternatives
Verify before relying
pip install openseespy
import openseespy.opensees as ops- Actual license terms and restrictions (LICENSE.md is referenced but SPDX is null)
- Whether platform-specific binaries are pre-built or compiled on install
- Performance characteristics and typical use-case scale limits
What it is and what it does
OpenSeesPy provides a Python interface to OpenSees, an open-source framework for structural analysis and earthquake engineering simulation. It wraps the core OpenSees engine and exposes it through a Python API, allowing you to define structural models, apply loads, run analyses, and extract results programmatically.
The package itself is a meta-package—when you install it, pip automatically detects your operating system and installs the matching platform-specific binary (Linux, Windows, or macOS). This removes the friction of manual binary selection. The package requires Python 3.10 or later and has three runtime dependencies, one for each supported platform.
Use it for
- Define and analyze structural models for buildings, bridges, or other civil infrastructure using Python scripts.
- Run earthquake ground-motion simulations and seismic response analyses on structural systems.
- Automate parametric studies by scripting multiple model variations and batch-running analyses.
- Integrate structural analysis into larger engineering workflows or optimization loops.
- Prototype and validate finite-element models before deploying to production analysis tools.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need Python-based structural analysis and simulation.
The package has low install friction, active maintenance, no known vulnerabilities, and broad platform support. The main caveat is that license terms are unclear—verify LICENSE.md in the repository before use in commercial or restricted-license projects. For academic and open-source structural engineering work, it is a solid choice.
Install
openseespy on PyPI
Before you install
Installation is straightforward with low friction—the package is a meta-package that automatically selects and installs the correct platform-specific binary (openseespylinux, openseespywin, or openseespymac) for your OS. The project is actively maintained with recent commits.
Requires Python 3.10 or later.
License in practice
License treatment is unclear—the package references LICENSE.md but provides no SPDX identifier. Before relying on this package in a commercial or restricted-license context, verify the actual license terms in the repository.
Quickstart
pip install openseespy
import openseespy.opensees as opsVerify before relying
- Actual license terms and restrictions (LICENSE.md is referenced but SPDX is null)
- Whether platform-specific binaries are pre-built or compiled on install
- Performance characteristics and typical use-case scale limits
Package facts
| License | LICENSE.md unclear |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesopenseespylinuxopenseespywinopenseespymac |
| Maintenance | Actively maintained 149 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 625,670 / month, #5,693 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3 |
Evidence: openseespy-3.8.0.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “structural analysis python”
- openseespyOpenSeesPy is a Python interpreter for OpenSees, a structural…
- PyNiteFEAPyNiteFEA performs 3D elastic structural finite element analysis,…
- openseespylinuxOpenSeesPy Linux provides a Python interface to OpenSees, an…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also obspy · openseespylinux · PyNiteFEA · MDAnalysis · pyocse · OpenMM · matscipy · anastruct · ase · mujoco