Skip to main content

Aeronautical engineering calculations in Python.

Project description


Author:Juan Luis Cano <>

scikit-aero is a Python package for various aeronautical engineering calculations. It is based on several existing Python packages on the field, but intends to provide pythonic syntax, use of SI units and full NumPy arrays support among other things. scikit-aero is licensed under the BSD license.

It was started by Juan Luis Cano in 2012 and it is currently developed and maintained by him. The source code and issue tracker are both hosted on GitHub

Notice: This package is under heavy development and the API might change at any time until a 1.0 version is reached. It is stable but not feaure complete yet, and it might contain bugs.


  • Pythonic interface.
  • Use of SI units.
  • Full support of NumPy arrays.
  • Support for both Python 2 and 3.
  • Fully tested and documented.
  • Standard atmosphere properties up to 11 kilometers (troposphere).
  • Gas dynamics calculations.


  • Full COESA model.
  • Airspeed conversions.
  • Coordinate systems.
  • Most of the PDAS.


Atmosphere properties:

>>> from skaero.atmosphere import coesa
>>> h, T, p, rho = coesa.table(1000)  # Altitude by default, 1 km

Inverse computations allowed with density and pressure, which are monotonic:

>>> h, T, p, rho = coesa.table(p=101325)  # Pressure of 1 atm

Gas dynamics calculations:

>>> from skaero.gasdynamics import isentropic, shocks
>>> fl = isentropic.IsentropicFlow(gamma=1.4)
>>> p = 101325 * fl.p_p0(M=0.8)  # Static pressure given total pressure of 1 atm
>>> ns = shocks.NormalShock(M_1=2.5, gamma=1.4)
>>> M_2 = ns.M_2  # Mach number behind a normal shock wave


This package depends on Python, NumPy and SciPy and is usually tested on Linux with the following versions:

  • Python 2.7, NumPy 1.6, SciPy 0.11
  • Python 3.3, NumPy 1.7.0b2, SciPy 0.11.0

but there is no reason it shouldn’t work on Windows or Mac OS X. If you are willing to provide testing on this platforms, please contact me and if you find any bugs file them on the issue tracker.


This package uses distutils. To install, execute as usual:

$ python install

It is recommended that you never ever use sudo with distutils, pip, setuptools and friends in Linux because you might seriously break your system [1][2][3][4]. I recommend using virtualenv, per user directories or local installations.


scikit-aero recommends py.test for running the test suite. Running from the top directory:

$ py.test

Bug reporting

I am pretty sure I never introduce bugs in my code, but if you want to prove me wrong please refer to the issue tracker on GitHub.


If you use scikit-aero on your project, please drop me a line.


scikit-aero is released under a 2-clause BSD license, hence allowing commercial use of the library. Please refer to the COPYING file.

See also

Project details

Release history Release notifications | RSS feed

This version


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit-aero-v0.1.0.tar.gz (20.2 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page