Aeronautical engineering calculations in Python.
|Author:||Juan Luis Cano <firstname.lastname@example.org>|
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.
>>> 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
This package uses distutils. To install, execute as usual:
$ python setup.py 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 . 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:
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.