AeroSandbox
AeroSandbox is a Python package that helps you design and optimize aircraft and other engineered systems.
Decision gist · record as of 2026-08-14
Yes. AeroSandbox is actively maintained, has no known vulnerabilities, and offers a rare combination of ease-of-use and power for aerospace design and general optimization. The low install friction, permissive MIT license, and broad applicability make it a strong choice for researchers, engineers, and students. Install the base package for core functionality, or add [full] for 3D visualization and CAD export if needed.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- The full feature set (3D visualization, CAD export) requires optional dependencies; core optimization and physics models work with the base install.
- Low friction: pure Python wheel with ten runtime dependencies.
License · maintenance · safety
MIT (permissive) — MIT license (permissive): you can use, modify, and distribute freely in commercial and private projects with minimal restrictions, provided you include the original license notice.
last release 2026-07-05 (40 days) · last repo commit 2026-07-05 · 1,301 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 161,105 downloads/mo, #10,642 on PyPI
Alternatives
Verify before relying
pip install aerosandbox
import aerosandbox as asb
# Define and optimize an aircraft
airplane = asb.Airplane()
# Then use optimization methods on the airplane object- Whether casadi must be installed separately as a system dependency or installs automatically.
- Performance characteristics on problems with tens of thousands of decision variables on typical hardware.
- Whether automatic differentiation is compatible with all custom physics models users might provide.
What it is and what it does
AeroSandbox is a Python optimization framework designed for aerospace engineering and general-purpose multidisciplinary design. At its core, it wraps automatic differentiation around NumPy-compatible syntax to solve large constrained optimization problems efficiently. The package ships with dozens of end-to-end-differentiable physics models covering aerodynamics, structures, propulsion, and trajectory simulation, allowing simultaneous optimization across multiple disciplines.
Typical workflows involve defining aircraft geometry, specifying design variables and constraints, then calling the optimizer to find the best configuration. You can also use AeroSandbox as a pure solver for nonlinear equations, boundary-value problems, or as a general optimization engine independent of aerospace. The package emphasizes ease of learning—built-in physics models are optional, and you can drop in arbitrary custom models. All inputs and outputs use SI units by default, with documented exceptions for angles (degrees for angle of attack and sideslip per aerospace convention).
Use it for
- Design and optimize complete aircraft from concept to first-flight, balancing aerodynamics, weight, propulsion, and mission range.
- Perform aerodynamic shape optimization of wings and airfoils subject to structural and manufacturing constraints.
- Explore design tradeoffs early in conceptual design—e.g., how solar airplane size varies with latitude and season.
- Solve nonlinear boundary-value problems with automatic discretization and differentiation.
- Interface with external tools (AVL, XFLR5, XFoil, CAD software) to augment or validate models.
- Optimize unconventional propulsion systems, weights estimation, and electric motor matching for aircraft.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
AeroSandbox is actively maintained, has no known vulnerabilities, and offers a rare combination of ease-of-use and power for aerospace design and general optimization. The low install friction, permissive MIT license, and broad applicability make it a strong choice for researchers, engineers, and students. Install the base package for core functionality, or add [full] for 3D visualization and CAD export if needed.
Install
aerosandbox on PyPI
Before you install
Low friction: pure Python wheel with ten runtime dependencies. Active maintenance—last release 40 days ago with 1301 GitHub stars and no known vulnerabilities. Requires Python 3.10+.
Requires Python 3.10 or later. The full feature set (3D visualization, CAD export) requires optional dependencies; core optimization and physics models work with the base install.
License in practice
MIT license (permissive): you can use, modify, and distribute freely in commercial and private projects with minimal restrictions, provided you include the original license notice.
Quickstart
pip install aerosandbox
import aerosandbox as asb
# Define and optimize an aircraft
airplane = asb.Airplane()
# Then use optimization methods on the airplane objectVerify before relying
- Whether casadi must be installed separately as a system dependency or installs automatically.
- Performance characteristics on problems with tens of thousands of decision variables on typical hardware.
- Whether automatic differentiation is compatible with all custom physics models users might provide.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 10 packagescasadidillmatplotlibneuralfoilnumpypandasscipyseabornsortedcontainerstqdm |
| Maintenance | Actively maintained 40 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 161,105 / month, #10,642 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Topic :: Scientific/Engineering :: Physics |
Evidence: aerosandbox-4.2.10-py3-none-any.whl
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